Building Agentic AI Applications with a Problem-First Approach Reviews on Testimonial.to

Sohan Bandewar

Just completed Maven's Problem-First Approach AI course, and it's completely transformed how I approach AI projects at Grant Thornton. As someone working in data analytics and AI, I've built plenty of models demand forecasting, ML models, business intelligence solutions. But this course taught me something more fundamental: I was often solving the wrong problem, or solving it the wrong way. My key learnings: Starting with "Why?" – I used to jump straight into model selection and data prep. Now I spend more time understanding the actual business problem. For instance, in demand forecasting projects, I've learned to first ask what decision this forecast will drive, not just how accurate it can be. Breaking Down Complexity - I've started decomposing client challenges differently. Not every problem needs a sophisticated AI model. Sometimes a simpler AI solution (or even no AI) delivers better ROI and faster results. Speaking Business, Not Tech – The AI frameworks I learned help me explain what AI can and can't do to stakeholders without the jargon. Setting realistic expectations upfront has made projects run smoother. The course structure was perfect comprehensive without being overwhelming. The guest lectures brought perspectives I hadn't considered, and the Chai and AI sessions were honestly some of the best parts. I'm genuinely excited to keep learning from those conversations and different viewpoints in the AI field. Massive thanks to Aishwarya and Kiriti for the effort you've put into this!!!! Aishwarya Naresh Reganti Kiriti Badam

Nov 12, 2025

Rolando Perez

Passionate TypeScript Full-Stack Engineer (12 yr) specializing in React & Node. Transitioning into AI Engineering—learning to build coding tools & agents.

I decided to take Aishwarya Reganti and Kiriti Badam’s course on Building Agentic AI Applications with a Problem-First Approach because I wanted a no-hype, practical course on how to actually build with Generative AI. I wasn’t looking for another “prompt engineering” overview. I wanted to understand how to tackle problems, when to apply the right level of agentic complexity, and how to do it in a data-driven way. It delivered and more. I loved learning the fundamentals of AI from a new lens. Even as someone technical who has spent hours deep-diving into ML on YouTube, I found Aish and Kiriti’s explanations refreshingly clear. They made complex ideas like how LLMs work, how they’re built, and how to design applications on top of them for enterprise use accessible, structured, and actionable. We explored everything from iterating effectively on prompts, to the intricacies and first-principle view of RAG, and how to architect agentic and multi-agent systems with the right level of complexity. The guest lectures were outstanding, offering insights from people working directly at the forefront of AI engineering, while you build your own agentic system from scratch and apply everything you learn. I’m walking away from this course with a clearer approach to building agentic systems grounded in real problems, a stronger sense of how to evaluate solutions in a data-driven way, and a renewed energy to keep building and experimenting. Huge thanks to Aishwarya Naresh Reganti, Kiriti Badam, Sahana Venkatesh, and Ashwin Naidu for creating such a thoughtful and rigorous learning experience 🙌. Also grateful to guest speakers Aman Khan, Wafae Bakkali, PhD, and Tanmai Gopal for sharing their insights and real-world experience at the forefront of AI engineering.

Nov 12, 2025

Rohit Maheshwari

CEO/Founder& Learner/Builder at Videoreach.run

Just completed the "Building Agentic AI Applications with a Problem First Approach" (lnkd.in/gMKqJaJt) course with Aishwarya Naresh Reganti and Kiriti Badam — an excellent deep dive into building responsibly, pragmatically, and effectively with Generative AI. What made it special: - Balanced focus on principles, practice, and pragmatism - Thoughtful exploration of real-world trade-offs in enterprise AI - Fun and useful assignments - Stellar guest speakers who shared their lessons from the field - A collaborative, supportive and smart learning community - Helping you build a mindset that can navigate real problems with AI approaches I am looking forward to using what I learnt professionally and personally. If you’re looking to level up your GenAI understanding and apply it meaningfully in enterprise contexts, this course is a must-take. Grateful to the instructors and team for creating such a powerful learning experience 🙏

Nov 12, 2025

Farheen Mohammad (Farah)

Global Partner Integrations Manager | Stanford LEAD

Wrapping up the Problem-First AI course with a heart full of gratitude for Aish and Kiriti. It’s rare to find instructors who combine deep expertise with such genuine passion for teaching. You both pushed us to think differently, challenge assumptions, and apply AI meaningfully. Thank you for sparking curiosity, inspiring confidence, and building a community of learners who are ready to make a real impact with AI. Kiriti Badam Aishwarya Naresh Reganti

Nov 12, 2025

Rashmi Jayakumar Kare

The AI agent 🤖 hype is everywhere, but what does it actually take to build one that's secure, scalable, and reliable? 🧩 I’ve just completed a course that provided real, technical answers. It’s not about a single magic “brain,” but about architecting a workflow of components: Planning, Tool Integration, Memory, Vector DBs, MCP/A2A, and Fine-Tuning. ⚙️ What stood out most was the relentless focus on production realities - tackling the hard parts like robust evaluations and monitoring, security considerations, and the trade-offs between cost, latency, performance, and effort. The experiences and ideas shared by fellow learners were also incredibly insightful 💡. Huge thanks to Aishwarya Naresh Reganti and Kiriti Badam for curating a curriculum that truly cuts through the noise and focuses on what it really takes to build real-world AI agents. 🙌

Nov 12, 2025

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Amal Khursheed

Principal Software Engineer @ NETSCOUT | Designing Scalable Network Solutions

🎉 Thrilled to share that I’ve completed the Building Agentic AI with a Problem-First Approach course! What made this course truly stand out was its structured, practical learning journey — 🧠 Prompts → 📎 Context Engineering → 📚 RAG → 🔗 MCP → 🤖 Multi-Agent Systems → ✅ Evals All taught in a way that stayed grounded in solving real problems, not just chasing buzzwords. 💬 The mix of live sessions, hands-on assignments, well-timed guest lectures, and community discussions made the experience even more impactful. A heartfelt thank you to Aishwarya Naresh Reganti & Kiriti Badam for designing such a thoughtful, problem-first learning experience. 🙌 #BuildingAgenticAI #ProblemFirst #GenAI #AgenticAI #RAG #MCP #Evals #AIJourney

Nov 12, 2025

Dilshan Fernando

Principal QA Engineer @ Backbase | AI enthusiast | Master’s in Advanced Software Engineering

I’m happy to share that I’ve obtained a new certification: Building Agentic AI Applications with a Problem-First Approach from Maven! Throughout the course I learned to: 🧠 Develop AI Intuition for Business: About the "why" and "when" of using AI. - Identify good use cases: Pinpoint business challenges where AI agents can provide real value. - Understand AI vs. traditional software: Learn why building with AI is different (e.g., dealing with uncertainty vs. fixed rules). - Make smart tradeoffs: Decide between different AI models based on their cost, speed (latency), and accuracy for a specific business need. 📊 Build an "Evals-First" Mindset: Making sure your AI actually works reliably. - Focus on measurable outcomes: Define success by what the AI achieves (its evaluation score), not just what features it has. - Use evaluation as the core: Make testing and measurement the foundation of your design process. - Find failures fast: Use metrics to identify and fix problems early and iteratively. ✍️ Master Prompt & Context Engineering: "How-to" of controlling and guiding the AI models. - Write better prompts: Use advanced techniques like breaking problems down (decomposition) and using "meta-prompts" (prompts that help write other prompts). - Choose the right model: Understand when to use a powerful (but slower/pricier) reasoning model versus a simpler, faster one. - Build in safety: Use other AI models ("LLM judges") and semantic checks to act as guardrails, ensuring your AI's output is safe and accurate. 🤖 Build and Optimize Agentic Pipelines: where you build the full system, often with multiple agents working together. - Create complex agents: Combine components like retrieval (pulling in data), memory (remembering past interactions), and self-reflection (checking its own work). - Manage system tradeoffs: Balance the system's overall accuracy with its speed and ability to adapt. - Coordinate multiple agents: Learn how to make different AI agents "talk" to each other and work together on a single, complex task, and understand the protocols that govern them. Aishwarya Naresh Reganti, Kiriti Badam you didn't just teach us the subject; you taught us how to learn and how to grow. Thank you for being such an incredible instructors. What's next? Don't miss this one: lnkd.in/efW8PnAk #GenerativeAI #AI #AgenticAI #LLM #RAG #PromptEngineering #FineTuning #EnterpriseAI #AIApplications #AIEvaluations #ContinuousLearning #BusinessValue

Nov 12, 2025

Nayan Shah

Cutting Through the AI Noise – One Truly Valuable Read at a Time Came across this wonderful article shared in our cohort by Aishwarya Naresh Reganti and Kiriti Badam. One of the biggest advantages of being part of this group (amongst countless many) is the curated flow of high-quality reading material that helps us stay focused and not drown in the constant AI noise around. Everywhere on LinkedIn these days, there are endless lists of “must-read” AI links, sometimes 5 or 10 in a single post. 🙃 The result is that people collect more than they consume. So, going forward, I plan to share only one truly valuable link at a time which is carefully picked from already curated lists that stand out for their clarity and learning depth. My goal is simple: to make AI learning a little more meaningful and less overwhelming for everyone. Today's pick: The Illustrated Transformer by Jay Alammar It beautifully explains how transformers and attention mechanisms work in simple, intuitive language that anyone can understand. 🔗 lnkd.in/gUcPjwj6 A must-read for anyone trying to grasp the foundation of modern AI models. Would love to hear if you have other such gems that make complex topics simple. #ArtificialIntelligence #MachineLearning #DeepLearning #Transformers #LearningAI #AICommunity #Education #ContinuousLearning #TechLeadership

Nov 12, 2025

Rituraj Dixit

Attending Aishwarya Kiriti’s GenAI System Design Bootcamp' has been a truly transformative experience. After spending more than a decade in the tech industry with a strong, tool- and technology-first mindset, this program helped me make a profound shift toward a problem-first, design-oriented approach. It taught me to pause before diving into code or tools, to understand the "why" behind every system, and to design with clarity and intent rather than buzzwords. Beyond the learning itself, I gained something equally valuable a community of thoughtful, curious peers who constantly inspire and challenge each other. The discussions, feedback, and shared experiences within this group made the journey richer and more meaningful. I now approach GenAI solutions with greater strategy and purpose. I am genuinely thankful for how this bootcamp reshaped my thinking and connected me with such an inspiring community. lnkd.in/gTG_DWRa Kiriti Badam Aishwarya Naresh Reganti

Nov 12, 2025

Girish Nair

Ex-Senior Manager at Deloitte Consulting

Over the past few weeks, I’ve been diving deep into Agentic AI — exploring how LLMs can move beyond static prompt-response interactions to orchestrate goal-driven, multi-step reasoning, tool use, and collaboration. What stood out most was how effectively the instructors blended theory with hands-on exploration. Each concept — from architectures and retrieval augmentation to autonomous planning and tool invocation — was approached with clarity, real-world relevance and business impact. I am still in the journey and catching up, but Aishwarya Naresh Reganti and Kiriti Badam have made the journey meanigful

Nov 12, 2025

Ravi Sandhu (PST, CPCC)

I am a product leader who helps organisations design and deliver scalable platforms and human-centred digital products, with a focus on outcomes, agility, and impact.

I’m happy to share that I’ve obtained a new certification: Building Agentic AI Applications with a Problem-First Approach from Maven! Many thanks to my trainers Aishwarya Naresh Reganti & Kiriti Badam on genuinely delivering one of the most practical AI courses out there. lnkd.in/efhGSx8R What I liked most: The course doesn’t chase shiny AI features & tools. The course teaches you to design vertical, workflow-embedded AI that actually moves business metrics. The foundations were super clear: AI stack, pretraining -> SFT -> RLHF, when to use reasoning models, and how to avoid “model selection hell.” The part on applied evaluation was 🔥 -> focus on real tasks, real data, real latency/cost constraints. The RAG module was also very enterprise-ready: retrieval quality, hybrid search, chunking, guardrails, and how to treat memory as RAG. I also appreciated the guidance on agents: start with a simple basic version, add tools + evals, only go multi-agent if there’s an operational reason. And the production mindset (observability, traces, cost tracking) is exactly what teams building LLM apps need right now. If you’re a PM, architect, or AI lead trying to ship reliable LLM products, not just demos, this course is worth it. 👏 #genai #productmanagement #llm #rag #aiarchitecture #systemsdesign

Nov 12, 2025

Priyanka Vankadaru

Analytics Specialist at Opella (Formerly Sanofi CHC), Supply Chain Analytics

Just wrapped up the Building Agentic AI Applications with a Problem-First Approach course — and what an incredible learning journey it has been! lnkd.in/gp3gJebj This course does a fantastic job of breaking down complex GenAI concepts while keeping everything grounded in practical, problem-first thinking. I really loved how each module gently built on the previous one — it was exciting to see how everything started to click together. Coming from a non-AI background, I can now confidently say I’ve become AI literate — I even find myself understanding those fancy GenAI architecture flow diagrams on LinkedIn now 😄 Huge thanks to Aishwarya Naresh Reganti and Kiriti Badam for the thoughtful design, depth, and clarity that went into creating this course. The attention to detail and structure truly make learning feel natural and empowering. A big shout-out as well to the instructor team, who were incredibly helpful and patient in debugging our assignment issues — their support made a real difference in the learning experience! #AI #GenAI #ProblemFirst #LearningJourney #AIApplications #AgenticAI #ContinuousLearning

Nov 12, 2025

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Gaurav baid

Senior Manager, Data Science & Strategy

Thank you, Aishwarya Naresh Reganti and Kiriti Badam, for creating such a beautifully organized and insightful coursework. It was an absolute pleasure to go through the material - engaging, thoughtfully structured, and packed with valuable learning. The clarity, depth, and creativity you brought to it made the entire experience both enjoyable and enriching. Truly appreciate the effort and passion that went into designing it! The combination of practical projects, inspiring talks, and collaborative discussions made this experience both intellectually stimulating and deeply rewarding. Excited to take these learnings forward and apply them to real-world challenges and more of Chai and AI sessions!! 🚀🚀

Nov 12, 2025

Sankhadeep Bhattacharya

One of the most compelling , well crafted course on AI that you can do . Aishwarya and Kiriti’s approach of “problem first “ before we introduce any AI is an eye opener . Today if you see AI and agents as those unfathomable concepts look no further than this course . Aishwarya Naresh Reganti & Kiriti Badam have curated the content with the right details and assignments . You would be better off asking the right questions when you are asked to put AI to the problem. lnkd.in/gprATMws Aishwarya Naresh Reganti Kiriti Badam

Nov 12, 2025

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Shriraj Salian

Software Development Engineer II at Amazon

Thank you Aishwarya Naresh Reganti & Kiriti Badam for the wonderful course! The course truly lived up to its promise. From day one, I discovered numerous developments in the AI space that I hadn’t known before. The structure was well thought out, with plenty of insightful reading material. It offered a clear, progressive understanding of how to think about and build GenAI systems—starting with model selection and simple workflow agents, then moving toward more complex designs. The assignments were engaging and hands-on, and the “Chai and AI” sessions provided a great forum to exchange ideas with people from diverse backgrounds. The community was welcoming and active, and the instructors engaged regularly on Slack, which made learning and discussions even more enriching. Overall, this feels like the perfect starting point for engineers entering the AI field. The instructors did an excellent job of creating a mental framework for evaluating key parameters when designing agents and making informed design choices. While there aren’t yet established design patterns (understandably, given the field’s early stage), the way they shaped our thinking process for approaching problems was spot on. For anyone who wants to join, please take a look! lnkd.in/gjZfYRJu

Nov 12, 2025

Prabha Markandan

Engineering & Delivery Leader | Driving Technology Transformation | AI enthusiast | Leadership Coach

Over the past year, I’ve been exploring AI hands-on through small experiments and real projects, realising a gap between what I built and how such systems scale - prompting me to move beyond curiosity toward designing AI systems that create lasting value. That’s what led me to "Building Agentic AI Applications with a Problem-First Approach" course by Aishwarya Naresh Reganti and Kiriti Badam on Maven. Both are true masters of their craft, combining deep technical expertise with exceptional clarity of thought. The outstanding effort they’ve put in shows in every lecture, discussion, and resource. I’m still midway through the course, but it's already one of the most thoughtful and practical AI courses I’ve taken, combining research depth with a clear systems mindset. What I’ve appreciated most so far is the problem-first philosophy, shifting from “what can I build with AI?” to “what problem deserves an agentic system?” Equally valuable is how the course unites everything in one place: frameworks, architectures, evaluation methods, and hands-on projects. It provides a strong foundation for connecting AI design, reasoning, retrieval, and deployment into systems that work in enterprise settings. A few 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 that have stayed with me: 𝗦𝗲𝗲𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗹𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲: The course demystifies the AI spectrum, from classic ML and deep learning to GenAI and agentic systems, showing how each layer fits into the modern enterprise stack. 𝗙𝗿𝗼𝗺 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 𝘁𝗼 𝘀𝘆𝘀𝘁𝗲𝗺𝘀: We’ve moved beyond prompt engineering into structured reasoning and workflow agents. Seeing how memory, orchestration, and tool use come together to form reliable AI systems has been an eye-opener. 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗶𝗺𝗽𝗮𝗰𝘁: The focus is on translating complex business problems into clear, agent-solvable components and bridging the gap between prototypes and scalable, production-ready systems. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝘆 𝗮𝗻𝗱 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲: Designing for evaluation, reliability, and guardrails from the start, including cost, latency, and safety, separates experimentation from enterprise deployment. The 𝗳𝗹𝗶𝗽𝗽𝗲𝗱-𝗰𝗹𝗮𝘀𝘀𝗿𝗼𝗼𝗺 format has been a huge plus. It makes it easy to follow sessions across time zones and catch up with the lectures in my own time. The course also includes rich materials to explore further, and I’m looking forward to diving into those over the coming weeks. For now, in the 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀 section, I’ll leave you with a few 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 the instructors have generously shared for free. They’re some of the best I’ve seen to understand agentic AI systems without the hype. I highly 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱 checking out the next cohort here: lnkd.in/eRTrFsEZ I’d 𝗹𝗼𝘃𝗲 𝘁𝗼 𝗵𝗲𝗮𝗿 from others exploring similar paths. How are you applying AI enterprise-wide in practice? What kinds of systems are moving from prototypes to production where you work?

Over the past year, I’ve been exploring AI hands-on through small experiments and real projects, realising a gap between what I built and how such systems scale - prompting me to move beyond curiosity toward designing AI systems that create lasting value. That’s what led me to "Building Agentic AI Applications with a Problem-First Approach" course by Aishwarya Naresh Reganti and Kiriti Badam on Maven. Both are true masters of their craft, combining deep technical expertise with exceptional clarity of thought. The outstanding effort they’ve put in shows in every lecture, discussion, and resource. I’m still midway through the course, but it's already one of the most thoughtful and practical AI courses I’ve taken, combining research depth with a clear systems mindset. What I’ve appreciated most so far is the problem-first philosophy, shifting from “what can I build with AI?” to “what problem deserves an agentic system?” Equally valuable is how the course unites everything in one place: frameworks, architectures, evaluation methods, and hands-on projects. It provides a strong foundation for connecting AI design, reasoning, retrieval, and deployment into systems that work in enterprise settings. A few 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 that have stayed with me: 𝗦𝗲𝗲𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗹𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲: The course demystifies the AI spectrum, from classic ML and deep learning to GenAI and agentic systems, showing how each layer fits into the modern enterprise stack. 𝗙𝗿𝗼𝗺 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 𝘁𝗼 𝘀𝘆𝘀𝘁𝗲𝗺𝘀: We’ve moved beyond prompt engineering into structured reasoning and workflow agents. Seeing how memory, orchestration, and tool use come together to form reliable AI systems has been an eye-opener. 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗶𝗺𝗽𝗮𝗰𝘁: The focus is on translating complex business problems into clear, agent-solvable components and bridging the gap between prototypes and scalable, production-ready systems. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝘆 𝗮𝗻𝗱 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲: Designing for evaluation, reliability, and guardrails from the start, including cost, latency, and safety, separates experimentation from enterprise deployment. The 𝗳𝗹𝗶𝗽𝗽𝗲𝗱-𝗰𝗹𝗮𝘀𝘀𝗿𝗼𝗼𝗺 format has been a huge plus. It makes it easy to follow sessions across time zones and catch up with the lectures in my own time. The course also includes rich materials to explore further, and I’m looking forward to diving into those over the coming weeks. For now, in the 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀 section, I’ll leave you with a few 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 the instructors have generously shared for free. They’re some of the best I’ve seen to understand agentic AI systems without the hype. I highly 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱 checking out the next cohort here: lnkd.in/eRTrFsEZ I’d 𝗹𝗼𝘃𝗲 𝘁𝗼 𝗵𝗲𝗮𝗿 from others exploring similar paths. How are you applying AI enterprise-wide in practice? What kinds of systems are moving from prototypes to production where you work?

Nov 12, 2025

Lasang Tamang, Ph.D

Senior Data Scientist | 13 yrs in Software + AI/ML | 20+ AI/NLP Publications | Enterprise-Grade ETL, RAG/Agentic AI, NLP & Analytics Delivery

Recently completed course “Building Agentic AI Applications with a Problem-First Approach” by Aishwarya Naresh Reganti and Kiriti Badam. I now feel confident designing and automating enterprise problems using Agentic AI — with thoughtful design, careful evaluation, and alignment to real business metrics. As someone balancing a full-time role, a startup, and parenting, it’s been a tough year trying to keep up with the rapidly evolving world of Agentic AI — despite having a solid foundation with a PhD in AI. The space is flooded with hype, buzzwords, and a majority of content generated by so-called “LinkedIn AI experts” using LLMs themselves. I’m very selective about what I spend time on and what I consume. This course turned out to be exactly the curated, research-driven, and practical learning I needed — no fluff, no hype, just honest, experience-backed insights. #lnkd.in/exa-D752

Nov 12, 2025

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Akhila Varghese

This week, I am concluding Aishwarya's and Kiriti's " Building Agentic AI Applications" and it has truly been one of the most insightful and enjoyable learning experiences. Over the last 6 weeks, I’ve been diving deep into building hands-on AI projects that explore the power of agentic systems and advanced retrieval techniques. The power of building hands-on is totally different, you uncover where the real challenges are, what to look out for, and how to make AI systems more resilient in practice. Few highlights from the course: 💡 Prompt & Context Engineering – refining prompt strategies, context windows, and retrieval flows to improve accuracy, coherence, and controllability across agentic workflows. 📊 Evals & Observability - building evaluation pipelines to measure performance, trace reasoning steps, and improve transparency across agents. 🎲 Managing Non-Determinism - experimenting with strategies to handle the inherently unpredictable nature of LLMs while maintaining reliability and reproducibility. 📂 High-Quality Datasets – curating and structuring datasets that drive better retrieval, reasoning, and evaluation, a critical factor in building truly effective agentic systems. A huge thanks to Aish, Kiriti, Sahana and @ashu for giving this cohort a wonderful learning experience and supporting us with queries throughout the clock. lnkd.in/ejtTzuSu

Nov 12, 2025

Umakant Sista

Applied AI & GTM Leader | Building AI-Native Solutions | Ex-Google (Applied AI), Adobe, Dell

Just completed a course on "Building Agentic AI Applications with a Problem-First Approach" on maven: lnkd.in/gzGVC3ey. It's a highly sought-after program ideal for aspiring Applied AI practitioners or experts. Aishwarya Naresh Reganti and Kiriti Badam excel in guiding participants through crucial concepts weekly. They reinforce these teachings with insightful assignments and a comprehensive final week capstone project. I highly recommend this course to those interested in delving into Applied AI and creating Agentic AI solutions for real-world issues.

Nov 12, 2025

Jacob Cheriathundam

Co-Founder at DocMe360

This was a phenomenol course on AI development: lnkd.in/etKWgmca Thank you to the instructors for the wonderful content and being so readily available for questions Kiriti: lnkd.in/e9K4jzGQ Aish: lnkd.in/eksHF5a4

Nov 12, 2025

Abhinav Kolhe

Senior Vice President - Automation, Data & AI, Travel and Hospitality

Completed the last session today for Building Agentic AI Applications with a Problem-First Approach. I have to say : this is next-level for anyone serious about generative AI in the enterprise. From start to finish it was a crisp, powerful experience that delivered both depth and practical application. The environment and learning culture, global cohort eco systems, guest lectures and hands on knowledge from practitioners Kiriti Badam and Aishwarya Naresh Reganti and their support staff is at different level. The cohort / capstone element adds serious value. You don’t just passively watch: you build an end-to-end project (and present it). That changes everything in terms of retention and real readiness. Huge thanks to Kiriti Badam and Aishwarya Naresh Reganti Preparing for my capstone project with a global community next week. lnkd.in/g46WW8ES

Nov 12, 2025

Akshay Ramesh

Director of Engineering, Implementation and Support: Innovative Application Specialist. Driving System Integration and Scalability with Cutting-Edge Tech to Enable Efficiency and Accessibility

I’m happy to share that I’ve obtained a new certification: Building Agentic AI Applications with a Problem-First Approach from Maven! This course by Aishwarya Naresh Reganti and Kiriti Badam helped me navigate through all the chaos and hype surrounding the world of AI and Agents and focus on what is truly important- "The problem". How do we breakdown the problem? And how do we use the most appropriate tool to solve the problem.

Sep 4, 2025

Swami Ganesan

Product Leader | Data | Analytics | Strategy

I recently completed the "Building Agentic AI Applications with a Problem-First Approach" course by Aishwarya Naresh Reganti and Kiriti Badam. The course emphasized iterative system design and helped me understand when to apply components like RAG, fine-tuning, guardrails, and Evals to improve AI products. I liked the flipped classroom format and the organization of content into CORE, BUILD, and GROW —balancing theory, hands-on practice, and deep dives into each concept. For the capstone project, I worked with a team on designing an AI compliance assistant, an area highly relevant to my work in regulated domains involving multimodal data and human subjects research. Our team iterated on a system that provided feedback on potential compliance violations and generated audit reports. This project offered practical experience in addressing privacy and security concerns through the use of guardrails, optimizing for high recall in compliance-sensitive applications, and evaluating the system’s operational, financial, and potential strategic impact for an organization.

Sep 4, 2025

Prateek Goel

I recently completed the Maven course "Building Agentic AI Applications with a Problem-First Approach" led by Kiriti Badam and Aishwarya Naresh Reganti . It's an excellent course for anyone interested in GenAI and agentic system design from first principles. This course really focuses on practical application not just theory. We built a Perplexity-style search agent step-by-step, which was a great way to understand the fundamentals of prompt and context engineering and the nuances of RAG. I learned to think strategically about when to use workflow versus multi-agents for different problems. I now have a much clearer understanding of why guardrails and evaluations are so essential for GenAI apps which often have non-deterministic outputs and how MCP solves those tricky context isolation problems The highlight for me was the week long capstone project. Our team developed 𝐖𝐞𝐂𝐚𝐫𝐞: 𝐀𝐈 𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭 to empower patients and families to make the right decisions—confidently, affordably and safely—by turning messy medical inputs and market complexity into clear, personalized, and explainable guidance. It was incredibly rewarding to build something with a real-world impact For anyone interested in exploring agentic system design, here’s the course: lnkd.in/eyBY9KEu

Sep 4, 2025

Shraddha M.

Senior Software Engineer

Working on hybrid search at eBay, I see how critical system design fundamentals are as AI transforms search. This course stands out for its problem-first approach. Aish and Kiriti don't just teach what to build, they teach you how to think. Their passion for teaching from first principles is evident throughout. Whether you're an experienced SDE or new to AI, this course develops the clarity of thought and deep understanding that separates good engineers from great ones. Highly recommend for anyone serious about building robust AI systems! 💯 Big thanks to instructors who clearly care about the craft and their students 🙌 lnkd.in/gaktMWc5 lnkd.in/gw9wxRit Course: lnkd.in/gBuCqPM2 #GenAI #ProblemFirst #SystemDesign #AIEngineering #MachineLearning #TechEducation

Sep 4, 2025

Ranjith Gonugunta

Data Engineering - Data Strategy @ Grainger

I recently completed the Maven course “Building Agentic AI Applications with a Problem-First Approach” with Kiriti and Aishwarya and could not recommend it more highly to anyone looking to enter the world of GenAI and Agentic system design. What stood out to me was the program’s focus: in today’s fast-evolving environment, no course can comprehensively keep up with the changing GenAI tech stack—and this course openly acknowledged that. Rather than chasing the latest tools, it emphasized structured thinking—how to approach and solve real-world problems first, before worrying about technology choices. That mindset is a game-changer. The live experiences were another highlight: regular office hours, interactive Chai Sessions, and candid discussions with industry experts and consultants truly enriched the curriculum. The most eye-opening aspect for me was learning from the capstone project presentations of fellow students. Each team tackled a different problem, and seeing how the “problem-first” methodology played out in diverse scenarios made me realize just how important it is to clarify the real need before designing an agentic solution. Separating noise from signal—this course teaches that well. Beyond the content, the sheer volume of knowledge exchange and community engagement over six weeks was phenomenal—enough to process for many months to come. Kiriti Badam and Aishwarya Naresh Reganti brought depth and clarity to every session, blending practical industry knowledge with a passion for teaching. Their guidance makes the daunting field of GenAI accessible and actionable. If you’re serious about building next-gen AI applications and want a pragmatic, principle-first foundation, enroll in this course. It will set you up for success in the agentic AI journey ahead. lnkd.in/gnquayCq #GenAI #AIApplications #AgenticDesign #MavenCourse #LifelongLearning

Sep 4, 2025

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Ryan Lustig

Director, Robot Software Engineering @ Brain Corp

This weekend, I completed the amazing course Building Agentic AI Applications with a Problem-First Approach taught by Aishwarya Naresh Reganti and Kiriti Badam. This six week course was practical, fast paced, and focused on building systems that work in the real world. My key takeaways: - AI changes too fast to memorize anything. The goal is to internalize core patterns and concepts then apply them across tools, models, and domains. - Enterprise agentic AI is still engineering. Treat it like ML and deep learning projects. Define metrics, write evals, measure performance, and only add/increase autonomy when the data says it helps. - Iterate, iterate, iterate. Start with the simplest possible system and add complexity only when a clear failure mode demands it. GenAI is non-deterministic, so every extra moving part increases the risk unless thoughtful guardrails are in place. For the capstone project, my team and I built an Agentic AI system for real estate valuation. Iteration 1 - A simple LLM using tools to gather zoning and comps data, then summarizing the findings with a yes/no recommendation. Iteration 2 - A workflow agent verifying data quality/freshness with clear human escalation paths. These cleaner inputs + few shot prompting allows the system to give a recommended price. Iteration 3 - Increased agency with a multi-agent planning, reasoning, and actioning system to improve on the data quality and refine its price valuations and key drivers. Overall, I now have a framework to design, test, and iterate agentic systems that will actually deliver on business value.

Sep 4, 2025

Arland Crandell

Senior Product Manager at Red Ventures | University of Chicago Booth MBA

Thrilled to share that I just completed the “Building Agentic AI Applications with a Problem-First Approach” course led by Aishwarya Naresh Reganti and Kiriti Badam! Link to the course: lnkd.in/gyBqbszC Over six weeks, I learned how to: 🖼️ Frame AI system design around real business constraints (latency, cost, compliance) 🏗️ Build effective RAG pipelines and context-aware memory systems 🚀 Coordinate multi-agent workflows and apply evaluation frameworks to measure success What really stood out to me (on top of the easily digestible and insightful content, and excellent teachers!) is the community. Can be intimidating asking questions or seeking advice/mentorship. People were welcoming, insightful, and collaborative, which was really impactful as these topics are nuanced/layered! I’m deeply grateful to Aishwarya and Kiriti for making advanced system design concepts accessible, practical, and engaging. The mix of structured content, live office hours, and the capstone project made this one of the most impactful learning experiences I’ve had recently. Excited to bring these learnings into my work at Red Ventures and keep on challenging myself!

Sep 4, 2025

Andrey Sazonov

Project Manager / Producer (3D & VR/AR) | Previz & Storytelling Enthusiast | Ex-Founder @ Lensman

Just completed the GenAI System Design course by Kiriti (lnkd.in/dytpgRz6) and Aish (lnkd.in/d7spsRRY)! The ocean of knowledge they’ve shared is so vast that I’m re-watching everything for a second time! It covers from fundamental principles to practical system implementation. What I loved most: real-world cases, comprehensive coverage, and the instructors’ passion for teaching. Highly recommend for anyone serious about AI systems! Check it out: lnkd.in/dmSnyZtn #GenAI #SystemDesign #Learning

Sep 4, 2025

Vinodh Subramanian

Enterprise SaaS Leader | Scaling Growth-Stage Products | Digital Transformation & AI Innovation

The outcome I was hoping for when joining this course was to get good at spotting the biggest headaches in my areas—like how we handle EA governance, IT M&A, or even just our Tech-Ops—and then figure out how to whip up some clever, Agentic AI solutions to make things run smoother and more efficiently. And let me tell you, this program totally delivered. It's not just a bunch of textbook stuff; it's super practical, all about starting with the problem, and everything you learn directly applies to the real world. Aishwarya Naresh Reganti, Kiriti Badam, and their entire crew are exceptional at taking complex ideas and breaking them down into easy-to-understand steps, providing frameworks that cut through all the buzz. The stuff on architectural patterns, multi-agent systems, and especially how to evaluate and observe things? Pure gold. Now, I actually feel confident enough to look at a challenge, figure out if Agentic AI can even help, and then actually build and scale solutions that work. This course seriously gives you the mindset and the tools to tackle those big-picture AI challenges in a real business setting. Heads up, October is the last group for this course (lnkd.in/gVy3S9Xh), so if you've been thinking about leveling up your AI game in a way that actually makes a difference, now's the time. Seriously, jump in and get those enterprise-ready Agentic AI skills!

Sep 4, 2025

Sai Dinesh Gurijala

Analytics Manager | Driving Growth Through Data | Gaming, Retail & E-Commerce

How to build enterpise AI applications that show data or insights based on user's NL query?? "Is it really possible/feasile/efficient?" - This isn't the question anymore. "It is needed!" - This is the consensus! So, I jumped into a course called "Building Agentic AI Applications with a Problem first Approach" provided by Aishwarya Naresh Reganti & Kiriti Badam. In the past, apprehensions have often led me to pause on similar opportunities. However, Maven’s course offering - (lnkd.in/gEvTVUgq) and its thoughtfully crafted curriculum sparked a genuine excitement that overcame my hesitation; so I took the leap. 6 weeks - 5 weeks of extensive learning, networking, guest talks, Chai & AI sessions, working on assignments and 1 week of super exciting capstone project with late night calls with team mates across the globe.. 🚀 As an analytics professional, I chose to build an “AI Powered Analytics Self Serve Platform” for my capstone project. While a few platforms have made progress in this area, significant challenges remain, including accurately interpreting complex queries, integrating diverse enterprise data sources, ensuring data accuracy, and maintaining user trust through transparent insights. Addressing these challenges is essential to unlocking the full potential of AI-driven analytics in enterprises. I’m grateful to have had the support of talented teammates Venkata Pakkala and muthuram natarajan. While the project is still evolving through iterations, I look forward to sharing a working demo soon. TL;DR - Building AI applications is more fun than using them :p

Sep 4, 2025

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Sreekutty Sreekumar

Digital Transformation | Automation | Generative AI | Strategy and Consulting

Just wrapped up the course "Building Agentic AI Applications with a problem first approach" on Maven. As someone who works in the Gen AI space, I was becoming increasingly aware of the need to understand the foundations of this technology and the various concepts around it to be able to keep up without drowning in the hype surrounding it. The course delivered what was promised and more and every concept introduced was from a lens of why it is needed/not needed for a problem and not because it is cool to know about it. From being confused by headlines like "RAG is dead" and "I built 2 agents that can replace the entire Finance team", the course has now prepared me to objectively look at the developments and think about what it means for the enterprise. Aishwarya Naresh Reganti and Kiriti Badam have put a lot of thought into the way the course is structured to take you from 0 to 1, assignments that let you apply what you learn iteratively and Chai and AI sessions with fantastic guest speakers from varied backgrounds. The final Capstone week pushed me out of my comfort zone and it was the cherry on the cake to be selected in the top 3. They have their next cohort starting in October and I highly recommend signing up for it if you are looking for a solid understanding of the Gen AI/Agentic AI space and set yourself up for life long learning.

Sep 4, 2025

Karthic Venkatesh

Proud Autism Dad | Site Reliability Engineering Lead @ Nike | Incoming UC Berkeley MIDS Student | Passionate about Scalable Systems, AI & Inclusive Tech

In today's world, it's becoming almost impossible to find an enterprise that isn't exploring AI in some way. But I think, as individuals, figuring out where to begin the AI journey can be overwhelming, considering how complex the technology is, the evolution of AI at a lightning speed, and the amount of noise on the internet. That's why I'm glad I enrolled in the Generative AI System Design course by Aishwarya Naresh Reganti and Kiriti Badam. What stood out to me the most was how the course emphasizes thinking about the problem first and then using AI iteratively to solve it, instead of jumping straight into tools and tech. Some of my key takeaways from the program: Provided me with solid foundational knowledge in Prompt Engineering, Tool Calling, Memory, RAG, Context Engineering, ReAct Prompting, MCP, and Autonomous and Multi-Agent systems. Connecting with peers from diverse industries, offering fresh perspectives. Insights from guest speakers actively building real-world AI solutions. Hands-on capstone project that made the learning truly practical. If you're looking for a structured, practical way to start your AI journey, I can't recommend this program enough. There's a strong reason why this course continues to remain in the Top 5 on Maven. Course URL: lnkd.in/gw2NQFmm

Sep 4, 2025

Govardhana Rao Chava

SDE 1 @Vyapar

I’m excited to share that I’ve completed the “Building Agentic AI Applications with a Problem-First Approach” cohort by Aishwarya Naresh Reganti & Kiriti Badam on Maven. Maven: lnkd.in/ewKF2cFg This six-week program gave me a clear, problem-first framework for thinking about AI systems — not just when and how to apply Agentic AI, but equally, when not to. 💡 What stood out for me: The content was well-curated, covering all key topics while giving the flexibility to dive deeper based on interest. It helped me build the habit of applying a problem-first mindset — realizing that not every problem requires Agentic AI. The assignments were fun and a great way to get hands-on with the LangGraph framework (special thanks to Sahana Venkatesh & Ashwin Naidu 🙌). The weekly Chai and AI sessions with industry experts gave fresh perspectives on the evolving AI landscape. A big thank you to Aishwarya Naresh Reganti and Kiriti Badam for designing such a thoughtful program, and to all my peers who brought energy, curiosity, and meaningful discussions throughout the journey.

Sep 4, 2025

Zhi Hui Tai

Product Leader | Currently tinkering with AI

Keeping up with AI right now feels like drinking from a firehose: a new jargon every week, and half of it just noise. As someone diving deeper into this space, I kept trying to figure out how to separate hype from what’s useful to build with. Learning from Aishwarya & Kiriti has made a real difference for me. From day one, they grounded us in a problem-first mindset: not every use case needs AI. That framing alone gave me confidence that they care about what actually works. What really clicked for me were the weekly build exercises that evolved iteratively. We moved from basic LLM calls to workflow agents to more autonomous systems, which finally made concepts like RAG and router LLMs make sense in practice. As a bonus, every week we had access to guest speakers from the industry, ranging from VC to practitioners in the field. For a space that’s evolving so quickly, hearing perspectives from folks deep in the trenches is a great way to cut through the noise. If you’re looking to sharpen how you think about AI while also getting hands-on, I’d recommend checking it out: lnkd.in/gitCfGvg

Sep 4, 2025

Felipe Morales

Leading Product at Ben | formerly Deel, Wise, AIESEC Intl. | Awarded Tier 1 UK Exceptional Talent

I’ve just finished the Building Agentic AI Applications with a Problem-First Approach course: lnkd.in/eTpw-x26, taught by Aishwarya Naresh Reganti and Kiriti Badam, after five weeks of after-work learning. What I got from it: a practical way to judge when agentic patterns help and when an orchestrated workflow is enough (the control–agency tension), the AI terms that flood X but applied in practice (evals, RAG, memory, MCP, etc.), a better grasp of latency/cost trade-offs, and hands-on experience using LangFlow and LangGraph to build these systems—not just slides. The course included a group capstone project, and ours was one of the Top 3 out of 18+ projects. AI Personal Medical Record Builder tapped into a personal problem: medical history scattered across scans and photos in Spanish. Through OCR and summarisation, it assembles a clinician-ready timeline with chat. If you’re unsure where to go next after learning the basics of AI, I recommend this one: hands-on, rich in content, and full of like-minded people who want to grow.

Sep 4, 2025

Andrei Ungureanu

Helping you use Gen-AI & Design Thinking to solve meaningful problems | Transformation & Capabilities Director for Coca-Cola Europe | Builder @aicreativeworkshops.com | Scribbler @ howmightweplay.com

How often is your mind buzzing with possibility after you finish a course? Better yet, how often do you feel you built some muscles you didn't even you had? I felt a bit anxious when I started this course on Building Agentic AI Applications with a Problem-First Approach as a non-programmer in my day to day. The Problem-first approach to agents drew me in - with its parallel to design thinking hinting this will be fun. Then, with every week, as we were going deep into technical aspects like workflows vs agents, context engineering, setting up a RAG system, short and long term memory, how to think about vector databases, AI Agents, MCP and tool usage, AI Eval Metrics, AI Guardrails and humans in the loop, observability, monitoring and optimization... ....there was something else I hadn't expected started settling in: Universal principles around how to apply and think about building agentic solutions. It was smart to design it with 3 layers: CORE for the main concepts, GROW to deepen your knowledge and BUILD to... put it in action. I liked the Reverse classroom approach too. Study and come for Q&A. Just one watch out: the more you put in this: the more you get out of it! If you want to understand and build Agentic solutions, I highly recommend you sign up for Building Agentic AI Applications with a Problem-First Approach on Maven: lnkd.in/dRc_mue3 by Kiriti Badam & Aishwarya Naresh Reganti BONUS if you read this far: This morning there were still 10 spots left with 15% off when you use the code DEMO15 at checkout. If those are taken, you can still use code AUG for $300 off.

Sep 4, 2025

Ketan Dave

Thought Leadership, Strategy & Execution | Speaker, Panelist & Moderator | Specialist in AI, Data Management, Analytics , AI & Data Governance, Master Data Management ,CDP, MarTech, Data Science, Data Engineering

Learning Never Ends :) Just wrapped up the Problem-First GenAI course on Maven ( lnkd.in/eKcZiTeg) led by Aishwarya Naresh Reganti Aishwarya Naresh Reganti and Kiriti Badam Kiriti Badam—and it was an absolute game-changer. I had been looking for a program that cuts through the AI jargon and teaches how to architect , design and deliver real end-to-end solutions leveraging AI. This course delivered far beyond expectations, blending Problem First-principles thinking with hands-on practice across various topics LLMS, RAG, Vector DB, AI Agents, Ai Eval Metrics , AI Guardrails , Observability & Monitoring , Optimizations includes Cost / Latency considerations for enterprise-scale production ready use cases What stood out for me: - No fluff—just practical, pragmatic frameworks rooted in real-world AI projects. - Solid foundation + confidence through hands-on assignments & enterprise projects (No-Code and Full-Code options). - Well curated Content and good pace for learning with right balance of theoretical insights , wide array of resources and tools - Enables the structured thinking to solve each Ai Use Case/s right from AI Strategy , architecture, design to solutioning. - Fantastic guest speakers from Aish & Kiriti’s network sharing diverse perspectives. - A curious well engaged peer cohort—Slack debates and live sessions were as valuable as the content. - Well knowledgeable , readily available and very supportive learning partners Sahana Sahana Venkatesh and Ashu Ashwin Naidu - Lifetime access to updated material and ongoing community support across cohorts. - Lastly nail down your Ai learning journey with available Capstone Projects or Pick your own project , develop a real word AI product/solution with group of 6 people just within a week to be ready to demo to attendees "open for all not just cohort" on demo day. Oh Wow! What an experience that gets you ready for your Next AI -Use Case Big thanks to Problem-First AI team, Aishwarya, Kiriti, Sahana Venkatesh, Ashu, coordinators and my peers for making this such a valuable learning journey. Excited to keep the AI momentum going through post-course through Slack Channels and Chai sessions If you’re looking to ground your AI expertise in problem-first thinking (instead of hype), I highly recommend this course: lnkd.in/gdSgR7Jh #ai #aistrategy #ailearning #aisolution #aiproducts

Sep 4, 2025

Manpreet Arora

Software Development Manager @Amazon Payments | Driving AI Adoption, Hands-On & Strategic

In 2025, I kicked off my AI learning journey. I thought I could get there with articles, videos, and newsletters—but I quickly realized I was missing the real stuff: core concepts and hands-on practice. Even while driving an AI adoption program at work at senior manager level, it felt like I was guiding adoption without fully mastering the foundations myself. That’s when I signed up for “Building Agentic AI Applications with a Problem-First Approach” on Maven. This course was a turning point. No hype. Just clear, practical knowledge. I learned how to think about workflow agents, RAG, and multi-agent architectures—and when to use each. I even built my first agentic system: a search assistant powered by Langflow. The cherry on top? Guest lectures from industry experts who shared insights that one won’t find in blogs or videos. I couldn’t finish the capstone this time around due to circumstances, but I’m excited to pick it up in the next cohort. Thanks to Aishwarya Naresh Reganti and Kiriti Badam for creating such a impactful course! If you’ve ever thought AI learning feels overwhelming, this course will change that. And if you’ve coded even once in your life, you’re ready! #AILearningJourney #BuildingAgenticAI #AIAdoption #LearnAndBeCurious

Sep 4, 2025

Soumyasmita(Simi) Das

It's a wrap! The last few weeks have been an exhausting and fast-paced period of learning. To bring efficiency by applying AI or managing its risks, I needed to understand the technology beyond the buzz. "Building Agentic AI Applications with a Problem-First Approach" by Aishwarya Naresh Reganti & Kiriti Badam, has been the excellent choice. I chose the low-code track (Langflow) to navigate the complexities of AI. Whether you're an expert coder, a subject-matter expert, or in management, this course will enhance your approach to AI. Learned about : 🔹Solving business problems using problem-first approach to AI applications designing 🔹Architectural choices in building AI applications 🔹Concepts of Prompt Engineering, Meta prompting, Context Engineering, Multi-Agent Systems, Memory, Evals and Fine Tuning 🔹Implemented workflow agents, RAG, Corrective RAG, Deep Research Agentic RAG and MCP 🔹Insights from guest speakers who are the industry experts, VCs and AI strategist on their approach to AI, expectations and the future. 🔹 I experimented with vibe coding and collaborated with my fantastic team to build the capstone project, the AI Compliance Audit Assistant, which I hope to deploy soon. :) My key takeaways: 🚀Engineering AI-applications are not same as traditional software engineering as AI-applications are non-deterministic Read more here lnkd.in/g-ng_mtJ 🚀Evals, operational metrics, performance metrics are the real friends for quality response, cost, latency optimization and observability 🚀 Understanding guardrails, security risks and scaling constraints are crucial as you move towards production and building AI systems that are safe and within acceptable boundaries. I still have plenty to unpack and apply what I have learnt. If you’re interested here is the link to the course : lnkd.in/gxAvjQYv #AI #AppliedAI #Cybersecurity #GRC

Sep 4, 2025

Amit Kulkarni

Security Engineer | Cloud And Application Security | Exploring and Innovating using GenAI | Security Automation | AI Agents

I’m happy to share that I’ve obtained a new certification: Building Agentic AI Applications with a Problem-First Approach from Maven! Thanks to Aishwarya Naresh Reganti and Kiriti Badam for very well organised course along-with hands-on assignments and projects. The course goes beyond not just teaching tools and frameworks but covers problem-first mindset to focus on real business needs, practical constraints, and iterative solution driven design in building enterprise AI applications. This course has helped me solidify my understanding and gain confidence in building complex, agentic AI systems. I now have a solid foundation of Prompt Engineering, Tool Calling, Memory, RAG, Context Engineering, ReAct Prompting, MCP, Autonomous and Multi-Agents. Also, learnt Optimization techniques and AI Evaluation Metrics After weeks of learning, building, and applying that knowledge, I am excited to showcase our Capstone Project — AI Compliance Audit Assistant — developed with my team from the cohort. #AI #AgenticAI #RAG #MCP #PromptEngineering #ContextEngineering #Compliance #Audit #GRCEngineering #Cybersecurity #InformationSecurity

Sep 4, 2025

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Usha Prabhu

Product builder

It's been a blast going through an intense structured learning process over the last six weeks with the Building Agentic AI Applications with a Problem-First Approach course. Thanks for the amazing experience Aishwarya Naresh Reganti and Kiriti Badam, and for your help and support Sahana Venkatesh and Ashu Shekar. We are presenting our final capstone project tomorrow (August 30) morning 9-11am Pacific. Come join us and see what can be achieved in just 6 weeks - lnkd.in/gTxtp2HB

Sep 4, 2025

Sandeep Seshadri

Executive Vice President of Engineering @ Kasasa | Computer Science, Strategic Thinking

I really enjoyed completing “Building Agentic AI Applications with a Problem-First Approach”. Learned a ton and met so many passionate folks from different domains. The best part was the capstone project — AI-powered Spend Monitoring & Anomaly Resolution System. Big thanks to Aishwarya Naresh Reganti and Kiriti Badam for guiding us through the journey 🙏 For anyone interested in exploring agentic system design, here’s the course: lnkd.in/eyBY9KEu

Sep 4, 2025

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Mohan Khyadi (MK)

Digital | Execution Leader | Product Thinking | Vision to Value

🚀 From reading about GenAI to building real solutions—in just 6 weeks! For months, I spent countless hours reading articles, watching YouTube videos, and listening to podcasts to understand GenAI, LLMs, Agents, and Agentic AI. I knew the theory—but the real breakthrough came when I actually built things myself: 👉 Workflows, level 1 & 2 agents, RAG pipelines, connected tools, and prototypes solving real business problems. And all of this happened in just 6 weeks, through the top course on Maven: Building Agentic AI Applications with a Problem-First Approach. Here’s what made this journey a game-changer: ✨ Accelerated learning – 10x faster than self-study. ✨ Clarity – GenAI isn’t complex; it’s simply another way to solve problems. ✨ Impact – Rapid prototyping sparked meaningful stakeholder conversations (because working demos always win over words). ✨ Confidence – I can now contribute meaningfully to GenAI discussions in enterprise contexts. The course design (Core → Build → Grow) ensured every week was hands-on: assignments, slack debates, and office hours that challenged us to ask tough questions like “Why LLMs?”—often uncovering simpler, smarter designs. 🙏 Huge thanks to Aishwarya Naresh Reganti & Kiriti Badam for your depth, patience, and structured guidance. I truly feel I’ve found lifetime mentors. Gratitude to Ashu & Sahana for the constant support. 🙏 And to my amazing cohort—thank you for making this ride unforgettable. Special thanks to Ameet Savanur for introducing me to this course! If you’re curious about GenAI, this course is an excellent starting point—fun, practical, and transformative. 👉 Check out the course here:

Sep 4, 2025

Venkata Pakkala

Director, AI & Analytics, | Driving Data Driven Strategies| Expert in Transforming Customer Experience Through Advanced Analytics and AI solutions.

Aishwarya Naresh Reganti and Kiriti Badam made building Agentic AI systems genuinely approachable. The iterative design process, combined with their "problem-first" approach, took me from feeling confused to confidently designing agentic AI applications on my own. The capstone tied everything together beautifully, and the guest talks, chill Chai & AI chats, and open office hours made it feel more like learning with friends than just taking a course. The best part? This mindset shift was exactly what I didn’t know I was missing. It helped me cut through the noise during Vibe-coding and start building clean, thoughtful prototypes much faster. What once felt frustrating and scattered now feels focused, efficient, and genuinely fun. Appreciate all the effort from my Capstone Project team - muthuram natarajan & Sai Dinesh Gurijala for all the hard work, late-night meetings, and endless chats about 'Agentic BI' 👏 👏 . Really appreciated your energy, ideas, and collaboration—it made the whole experience way more fun and rewarding!

Sep 4, 2025

Ahmed Mohamed

Lead Data Scientist / Data Engineer @Fashion Digital / Peek & Cloppenburg Group | 5x GCP certified | MLOps

What makes this course stand out is how it teaches AI the way it should be built: problem-first, practical, and iterative. Instead of just theory, it focused on a mindset: start simple, let the problem guide the design, and refine through iterations with the right metrics. The assignments brought this to life, turning advanced ideas like RAG, MCP, and multi-agent coordination into hands-on practice directly applicable to real work. The curriculum went far beyond buzzwords: - 𝐏𝐫𝐨𝐛𝐥𝐞𝐦-𝐟𝐢𝐫𝐬𝐭 𝐬𝐲𝐬𝐭𝐞𝐦 𝐝𝐞𝐬𝐢𝐠𝐧 - 𝐒𝐦𝐚𝐫𝐭𝐞𝐫 𝐩𝐫𝐨𝐦𝐩𝐭𝐢𝐧𝐠 & 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬 - 𝐑𝐀𝐆 𝐝𝐨𝐧𝐞 𝐫𝐢𝐠𝐡𝐭 (𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆, 𝐦𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥) - 𝐌𝐂𝐏, 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐠𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬 & 𝐦𝐮𝐥𝐭𝐢-𝐚𝐠𝐞𝐧𝐭 𝐩𝐚𝐭𝐭𝐞𝐫𝐧𝐬 - 𝐀 𝐜𝐚𝐩𝐬𝐭𝐨𝐧𝐞 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐝𝐞𝐦𝐨𝐞𝐝 𝐥𝐢𝐯𝐞 𝐭𝐨 4000+ 𝐩𝐞𝐞𝐫𝐬, 𝐥𝐞𝐚𝐝𝐞𝐫𝐬, 𝐚𝐧𝐝 𝐕𝐂𝐬 After this journey, I feel equipped with a Swiss-knife of tools and concepts to tackle real-world AI challenges with confidence. Huge thanks 🙌 to Aishwarya Naresh Reganti and Kiriti Badam for building such a unique and practical program. The clarity and structure you brought made it one of the most valuable learning experiences I’ve had. October marks the final cohort, if you’ve been considering it, this is the moment to join the community and build enterprise-ready Agentic AI skills. Link to the course: lnkd.in/e8mPNpnj ✌ 😊

Sep 4, 2025

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Subhashini Gurumurty

I recently completed “Building Agentic AI Applications with a Problem‑First Approach” led by Aishwarya Naresh Reganti and Kiriti Badam. The course delivered clarity over noise, giving me the practical tools to think like an enterprise AI designer. Along the way, I had so many aha moments as abstract ideas turned into frameworks I can actually apply. Here’s what really resonated with me: 🔹 Understanding agentic AI means applying AI only when it’s needed, and recognizing when simpler solutions work better 🔹 Learning to design multi-agent systems that collaborate intelligently without over-engineering 🔹 Embracing a problem-first mindset - always aligning AI choices with real business constraints 🔹 Developing frameworks for evaluability and observability, ensuring AI remains measurable and interpretable 🔹 Internalizing a common language of agentic applications—making collaboration across teams smoother The low-code assignments were a game-changer - practical, hands-on learning that helped me quickly build prototypes while exploring everything from model selection and meta prompting to tool integration, memory design, and crafting evaluations. They gave me the right frameworks to not just experiment on my own, but also to meaningfully engage with data scientists and researchers when shaping AI applications. The Chai & AI sessions, a vibrant learning cohort, and the guest speakers (mind-blowing perspectives!) transformed the course into a truly community-powered experience. Good things should be shared - if you're looking to cut through the chaos and learn what really matters in enterprise AI, this is it. Join the last cohort starting October 2025 👉 lnkd.in/et9SVYWe #AI #AgenticAI #EnterpriseAI #ProblemFirst #LearningByDoing

Sep 4, 2025

Amar Solasa

Transformational Data Leader | Driving AI-Powered Analytics, Cloud Platforms & Scalable Innovation

I just finished the "Building Agentic AI Applications with a Problem-First Approach" cohort on maven.com, and it’s been one of the most practical and well-designed AI programs I’ve seen. What stood out to me: The instructors delivered more than they promised — with incredible attention to detail, thoughtfully structured content, and constant engagement with participants. The problem-first, evaluation-driven approach cut through the hype and showed how to apply AI in ways that truly matter. The mix of hands-on exercises, frameworks, and the capstone project turned concepts into skills you can apply immediately. Guest speakers and “Chai & AI” sessions offered unique industry perspectives that are rarely found in online programs. A huge thank you to Aishwarya Naresh Reganti and Kiriti Badam for creating such a valuable, real-world learning experience — and to the amazing community of peers who made the journey so enriching.

Sep 4, 2025

Dan Krysinski

AI & Automation Specialist at Hitachi Vantara

I try to avoid posting to social media when I can, but this one warrants it.... I'm currently wrapping up a cohort I've been part of for Building Agentic AI Applications with a Problem-First Approach through maven.com (lnkd.in/giW-8RYR), and I'd like to rave a bit. If you're working in the AI space and want something that goes beyond theory into real-world, practical system design, this course is gold. It’s packed with hands-on frameworks, thoughtful breakdowns of GenAI architecture patterns, and tons of insight into how to actually build and scale solutions that work. Huge shoutout to the instructors Aishwarya Naresh Reganti & Kiriti Badam, alongside their team — they do a phenomenal job making complex topics approachable and actionable. The content is engaging, the examples were relevant, and the community was full of smart, curious folks building cool stuff. Highly recommend this to anyone designing AI-powered systems or looking to sharpen their product + technical thinking.

Sep 4, 2025

Pradeep Kotha

Technology Leader | AI Solutions Consultant | Leader in Building Scalable, High-Quality Solutions and Geographically Diverse Teams

Just wrapping up the incredible Agentic AI course with Aishwarya Naresh Reganti and Kiriti Badam and I can't recommend it enough. This program was a masterclass in applying AI to solve real-world business challenges. It went beyond theoretical concepts, offering a practical deep dive into building effective, autonomous AI systems. As a member of the cohort, I'm currently finishing our final project—an AI solution for the real estate industry. The course's "problem-first, evaluation-driven" approach was a total game-changer. It taught me that the real power of AI agents lies not just in the technology, but in the strategic application to solve business problems. Here are my key takeaways: - Prompt Engineering is foundational. We moved past basic prompts to master advanced techniques like decomposition and meta-prompts for building smarter, more reliable systems. - RAG is a building block for agents. Retrieval-Augmented Generation (RAG) is far from dead; it's the bedrock for creating self-improving agents. We learned how to build robust RAG pipelines and explore advanced methods like Agentic RAG. - Practical Agent Development. We got hands-on with building autonomous agents, from dynamic tool use to understanding emerging communication standards like MCP and A2A. - Enterprise-Ready AI. The course tackled critical topics like security, multi-agent coordination, and how to decide between fine-tuning and RAG—all from an enterprise lens. The capstone project brought everything together, giving us the chance to design and implement a complete solution. A huge thank you to Aishwarya Naresh Reganti and Kiriti Badam for their expertise and for creating such a practical and valuable course! Course: lnkd.in/gMkrcvCF

Sep 4, 2025

Kaushik K.

Co-founder and CTO | Strategic Advisor to CxOs | Architecting the future with AI, Data and Systems thinking

Six months ago, I felt overwhelmed by the rapidly evolving AI landscape. Despite working in Machine Learning since 2015 (starting with energy forecasting) and completing programs at Harvard, Carnegie Mellon, and MIT, the breakneck pace of AI developments in 2025 was challenging to keep up with. I needed a program that would cut through the noise and help me build a practical mental framework for Agentic AI. Enter "Building Agentic AI Applications with a Problem-First Approach" by Aishwarya Naresh Reganti and Kiriti Badam on Maven. lnkd.in/ewKF2cFg This six-week cohort-based program delivered exactly what I was seeking: a clear mental map for navigating Agentic AI solutions. The curriculum brilliantly combines foundational topics (LLMs, Prompt Engineering, RAG, fine-tuning, Evals, Multi-agents, planning and tools) with hands-on problem-solving using first principles. Three reasons why I highly recommend this program: 1) Perfect theory-practice balance – Aishwarya and Kiriti seamlessly blend foundational AI concepts with real-world applications and practice. 2) World-class guest speakers – Learn from former consulting CEOs, AI entrepreneurs, investors, and practitioners who share genuine front line experiences. 3) Vibrant learning community – The cohort model plus weekly "Chai and AI" sessions create invaluable peer learning across industries and roles. The transformation: I now confidently advise enterprises on when and how to deploy Agentic AI and crucially, when NOT to use them. The mental clarity I gained has been game-changing for my work. If you are planning, designing or deploying real-world Agentic AI systems, this is the program I recommend without hesitation. #GenAI #ArtificialIntelligence #AgenticAI #EnterpriseAI #Training

Sep 4, 2025

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Sandeep S

Technology and Transformation Leader | Principal, Client Engagements | Driving Value by Scaling Software Engineering, Agile, DevOps, Digital | AI/ML, GenAI, LLMs, AI Agents

🎉 Excited to share that I have completed the “Building Agentic AI Applications with a Problem First Approach” with Aishwarya Naresh Reganti and Kiriti Badam Both instructors bring tremendous real-world experience, and the program exceeded my expectations. What I valued most was the problem-first approach, cutting through the noise in the AI space and focusing on the concepts that truly matter. The curriculum was thoughtfully designed, building week over week, with the flexibility to go at your own pace, whether just the core content, assignments, or diving into the optional “grow” material. It is a program I will keep revisiting as a reference. For anyone looking to deepen their understanding of AI without getting lost in cluttered advice, I cannot recommend this program enough. Please check it out here at the course page on Maven. lnkd.in/eeEP5T-v #AI #Learning #ContinuousLearning #AITransformation #Certificate

Sep 4, 2025

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Rose M.

Data-Driven AI Strategist

I'm excited to share that I’ve received my certificate for the course, Building Agentic AI Applications with a Problem-First Approach. 🎉 A huge thank you to our instructors, Aishwarya Naresh Reganti and Kiriti Badam, for cutting through the noise and providing a foundational understanding of AI, agents, and optimization. 🔶 One of my biggest takeaways from the course is the importance of starting with the problem and optimizing smartly—not expensively. As a technologist, it’s easy to get distracted by the rapid evolution of AI tools, but this course reinforced the value of thoughtful, problem-driven solutions. 🔶 I also appreciated their reminder that no one person is an expert in all of AI. Instead, we can carve out our own niche and go deep—for ourselves, our clients, and our communities. A very big thank you as well to Deloitte for sponsoring me and leading the way in applied AI for business transformation. And a huge, huge thanks to GPS leadership for this opportunity. 🙌 Adarsh (AD) Desai, Andrew Derr, Aman Vij, Jitesh Rodrigues Prabhu, Aaron Silverman, Nina Gonzalez, Kurt Dassel, Kathleen O'Dell, Hemant Ramachandra, Olga Robinson, Alison Voss lnkd.in/eQfBPxxM

Sep 4, 2025

Saswat Priyadarshan

Software Engineer @ Microsoft

Excited to share my recent certification in Building Agentic AI Applications with a Problem-First Approach from Maven! The structured course has empowered me to tailor my growth in the realm of Agentic AI. It provided comprehensive resources, going above and beyond to enhance my skills. A highlight was the dedicated support from instructors and staff, ensuring our queries were addressed and leaving us with valuable insights after every discussion. The guest lectures, along with Chai and AI sessions, were truly enriching. I wholeheartedly endorse this course to all seeking to advance in this field. A big thank you to Aishwarya Naresh Reganti and Kiriti Badam for creating such a high-quality course. I am eager to apply all my learnings at work with a problem-first approach mindset. The next cohort is starting soon. If you want to register then here is the link - lnkd.in/gvdpd-BW

Sep 4, 2025

Akhil Eppa

ADOBE | CMU, School of Computer Science

"Always start small and let the problem guide the solution." That's one of my biggest takeaways from the course "Building Agentic AI Applications with a Problem-First Approach". The course was thoughtfully structured, building step-by-step in complexity, while keeping the focus on a problem-first and evaluation-driven design. Instead of rushing into using the various tools available, the emphasis was on thinking through the solution, learning, and iterating at every step. Some highlights from the course: ✅ Practical perspective on deploying agentic solutions in enterprise, accounting for non-determinism and debugging complexities. ✅ Critical factors for scaling applications: evals, guardrails, usage monitoring, and efficiency gains through caching. ✅ Perspectives from experts from various facets in the industry through guest talks. A few reflections that I'm carrying forward: ✨ The field is evolving quickly. Staying curious, digging deeper, and taking on challenges is the best way to keep learning. ✨ With generative AI's non-deterministic nature, starting simple and layering complexity while weighing costs becomes essential. ✨ With many AI tools available, implementation is becoming more accessible, but good solution design is going to become critical and the differentiator. Kudos to Aishwarya Naresh Reganti and Kiriti Badam for creating this environment to learn and share. Do check out the course here: lnkd.in/en-C9yu2

Sep 4, 2025

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Ravi Yenduri

CTO @ Sabanto | Strategic Leader in Technology Innovation & Team Development | Driving Business Transformation & Operational Excellence Across Full SDLC ☛ Partnering with C-Level Executives to Shape Technical Direction

For the past 4 weeks, it's been instilled in me that, always, Problem First. So, the Problem: After two decades of building and scaling systems, I've developed a healthy skepticism towards new technologies. I was wary of a course that promised to demystify AI. My concern wasn't necessarily the technical details, but it was more on finding a program that matched my level of experience and didn't gloss over the complexities. The Solution: What set the course Building Agentic AI Applications with a Problem-First Approach (lnkd.in/gd_wRW3K) apart was its attention to detail and commitment to candid, unfiltered conversations. Aishwarya Naresh Reganti and Kiriti Badam didn't shy away from the hard questions, and more importantly didn't try to hide the limitations of the technology. The round-the-clock support felt less like customer service and more like a collaboration with peers. The mystery speakers and honest discussions provided insight that one simply cannot get from a textbook. The multi-layered weekly assignments kept me engaged throughout. It truly was an elite learning experience. And finally, the Outcome: I no longer see AI as a buzzword. I see it as a set of tools with specific applications and constraints. I now have a refined framework for evaluating AI initiatives. I can confidently direct myself and my teams to start with a clear problem statement, which will lead to more focused discussions and better allocation of resources. This course gave me a new lens through which to view technology, and that's invaluable. Thank you Aishwarya and Kiriti. ☕

Sep 4, 2025

Chilann Chan

Product @GenAI | Humanic AI, ex-Adobe | AI in Martech, Media and Entertainment

I was looking for an advanced AI course that went beyond the hype and focused on dissecting problems from first principles. Building Agentic AI Applications with a Problem-First Approach (Course link here: lnkd.in/gdSgR7Jh) by Aishwarya Naresh Reganti and Kiriti Badam not only delivered on that promise but far exceeded my expectations. What I liked about the course: · To develop advanced thinking in AI and build a unique point of view, it’s essential to ground yourself in first principles, and then put them into practice. Aishwarya Naresh Reganti and Kiriti Badam shared deep, domain-specific insights on real AI problems. Even with prior industry experience, I learned a great deal from them and their impressive network of guest speakers. · A high-caliber cohort of peers tackling diverse AI challenges, who are curious, creative and ask insightful questions. The networking, brainstorming, and exchange of ideas with practitioners who approached similar problems from different angles were incredibly valuable. I’m looking forward to staying connected with Aishwarya, Kiriti, and my amazing peers through the post-course Chai sessions. I’d highly recommend this course to anyone in my network who wants to go deep into AI problem-solving with rigor and clarity!

Sep 4, 2025

Eric Cai

Bachelor of Computer Science at Washington University in St.Louis

Just wrapped up Building Agentic AI Applications with a Problem-First Approach — and I can honestly say this has been the most practical AI course I’ve taken so far. The coding assignments pushed me to actually interact with models instead of just passively learning theory. I loved the structure — clear separation between the core content (immediately useful for my work) and the growth modules I can revisit later. The guest lectures gave great insight into how AI is applied in industry today, and the instructors were consistently responsive, patient, and willing to clarify tough concepts. Slack support was impressively fast too. What really stood out was the balance between theory and practice. Alongside hands-on assignments, we also explored research papers and step-by-step design discussions that helped me understand how to build agentic systems in the real world. Even though I couldn’t complete everything due to work, I know I can go back and dive deeper into the advanced modules. Overall, the course overdelivered on every promise. Strong 10/10 from me. 🚀 Big thanks to Kiriti Kiriti Badam and Aishwarya Aishwarya Naresh Reganti for designing such a thoughtful learning experience! 👉 Check out the course here: Building Agentic AI Applications with a Problem-First Approach:

Sep 4, 2025

Harini Shekar

Payments - AI/Applied Machine Learning and Data Science

The Gen AI and Agentic era kicked off a rapid upskilling journey for me. While countless resources are available, this course on maven lnkd.in/g9gb_uKM really stood out as the one that could get me onto a structured learning path! But honestly, this delivered beyond my expectations! Key takeaways from the course: Building for Production: How to approach building Agentic AI applications for real-world, enterprise use cases, not just proofs of concept. Honest Insights: Aish and Kirti were candid about the common pitfalls and failure points of multi-agent systems, providing invaluable, practical knowledge you won't find in textbooks. Unmatched Support: The live, consistent support for all questions throughout the six-week course was incredible and truly sets this program apart. I enrolled for the structure, but left with a profound understanding of how to think like a professional about Gen AI systems. I am excited to apply these in real world applications to build scalable systems. Thank you so much, Aishwarya Naresh Reganti and Kiriti Badam, this course has genuinely exceeded all my expectations. Aish, your LinkedIn posts resonate so deeply with me. They are incredibly inspiring. #GenAI #AgenticAI

Sep 4, 2025

Vishwa Goudar

Strategic AI Automation & Integration Expert | AI Scientist | PhD in Computer Science

Just completed the Maven GenAI course (lnkd.in/eKcZiTeg) led by Aishwarya Naresh Reganti and Kiriti Badam, and I highly recommend it. Key highlights include: - The right balance of theoretical insights and hands-on application for builders - Nuanced and detailed discussions on trade-offs and best practices for enterprise use cases - A wide array of resources and tools - Engaging guest lectures from professionals across the AI ecosystem - Supportive teaching staff readily available for assistance For those seeking to enhance their GenAI expertise with a deeper understand of common tradeoffs and best practices in enterprise use cases, this course is an excellent starting point. A big thank you to Aish, Kiriti, and the entire team for crafting such a valuable and enriching learning journey.👏

Sep 4, 2025

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Sai Haritha Chalikonda

Vice President at JPMorgan Chase & Co.

I’m halfway through Building Agentic AI Applications with a Problem-First Approach by Aishwarya Naresh Reganti and Kiriti Badam, and it’s easily one of the most thoughtfully designed and impactful courses I’ve taken. One standout for me is the decision-making framework for designing AI agents — a clear, principled way to choose the right architecture based on cost, latency, and performance trade-offs. This is gold for anyone aiming to build production-grade AI systems. From day one, it’s a fully hands-on experience. Depending on your coding background, you design agent workflows using LangChain or LangFlow, working through a “Perplexity Light” example and culminating in a capstone project. It’s also my first flipped classroom experience — self-paced lectures followed by rich, interactive discussions. The format makes every session insightful, practical, and deeply engaging. This course is a must for Tech Leaders, Data Leaders, Architects, and Product Managers who want to go beyond theory and design scalable, agentic AI systems with confidence. The energy, clarity, and real-world expertise that Aish and Kiriti bring — plus guest speakers who’ve built these systems — make this a masterclass in AI agent design. Now's the time to join the October Cohort if Interested! Link - lnkd.in/dDhSCmpM Thank you Aishwarya Naresh Reganti and Kiriti Badam for making such a complex field feel so natural. #JPMorganChase #GuildEducation #AgenticAI #LLMs #AIagents #LangChain #LangFlow #ProblemFirstApproach #AIProduct #TechLeadership #HandsOnLearning #FlippedClassroom #CapstoneProjects #PerplexityLight #AIArchitecture #ContinuousLearning

Sep 4, 2025

Parthiban Srinivasan

Professor & Director | Centre for AI in Medicine | Vinayaka Mission’s Research Foundation | AV Medical College & Hospital

Thank you for a truly insightful and well-structured course! I particularly enjoyed the practical, hands-on approach to Generative AI System Design. To anyone interested in building robust GenAI systems, I highly recommend checking out this course! Course Link: lnkd.in/gzKDPhHm Kiriti: lnkd.in/gvwtRzXQ Aishwarya: lnkd.in/gPXJqQFq

Sep 4, 2025

Arun Kumar Parthasarathy

With so many things going around in generative AI its very difficult to read and categorized the real facts vs noise. In Fact more than 50% of the linkedin posts are AI generated. So even for someone who is having strong technical background its very difficult to identify which practices are truly being adopted in enterprises and which ideas may not work. To gain clarity, I joined the Maven course "Building Agentic AI Applications with a Problem-First Approach" after talking to the previous cohort members as they were impressed with the course and strongly recommended it. Now that I have nearly completed the program, I can confidently say it has been completely worth it. The course offers not just theory but also practical, hands-on ways to implement advanced AI concepts. To know more about the course please visit lnkd.in/geGHMeNh Thanks Aishwarya Naresh Reganti & Kiriti Badam for putting this course together. I will recommend this to anyone who is interested to understand and apply generative AI concepts in their enterprise or start something on their own. #ProblemFirstAI #AgenticAI #Generativeai

Sep 4, 2025

Nachadalingam (Lingam) Chockalingam

Innovator | Leader | Strategist | Advanced Analytics | AI/ML

Just completed the incredible “Building Agentic AI Applications with a Problem-First Approach” course by @Kiriti Badam and @Aishwarya Naresh Reganti! This program took my AI skills to the next level with its hands-on, problem-first approach and expertly guided multi-agent system design. The live sessions, iterative coding assignments, and supportive cohort made all the difference. Highly recommend for anyone serious about practical, enterprise AI! Check it out here: lnkd.in/egQVNvss Kiriti: lnkd.in/eXV8brRC Aishwarya: lnkd.in/euaVZU79 #AgenticAI #GenerativeAI #AIApplications #MachineLearning #AICommunity #EnterpriseAI

Sep 4, 2025

Nikhil Ravi

Product & Commercialization @ Google | Cloud | Ex-MSFT

I recently completed a course on 'Building Agentic AI Applications with a Problem-First Approach', led by Aishwarya Naresh Reganti and Kiriti Badam , and wanted to give a shout-out to them for curating a great course. There are two tracks, depending on whether you want a low-code/no-code or a code-first experience. I got some good hands-on experience in designing multi-agent AI systems that are tuned to business constraints like latency, cost, security, and compliance. The curriculum prioritizes a problem-first design: from assessing hallucinations, to building robust RAG pipelines and orchestrating multi-agent workflows with clear evaluation and guardrail mechanisms. Aish and Kiriti have created a well-structured format that mixes learning through pre-recorded lectures, office hours, Slack forums, and from guest speakers that they bring in. If you're someone that learns by building, and works in the Enterprise space, I'm sure you'll find value in this course.

Sep 4, 2025

Ravi Kiran Ganji

Senior Delivery Consultant @ AWS | Leading Cloud Architecture & Application Development

Grateful for the excellent course led by Aishwarya Naresh Reganti and Kiriti Badam - lnkd.in/d4DaBdBt Three standout takeaways that will shape how I approach AI projects moving forward: - Design thinking for production AI: Understanding the nuanced considerations that separate prototype from production-ready AI applications. - Diverse perspectives: Learning alongside cohort members from different industries and technical backgrounds provided invaluable insights. - Industry insights from the frontlines: Engaging sessions with guest speakers like Francisco D'Souza and Jaya Gupta, along with other industry experts, offered real world perspectives on AI implementation challenges and opportunities across different sectors. The intersection of technical depth and real-world application made this course particularly valuable. Highly recommend for anyone looking to bridge the gap between AI concepts and practical implementation. #ProblemFirstAI #AgenticAI

Sep 4, 2025

Senthilvel Rajan Kumaresan

Experienced data engineer with a proven track record of empowering machine learning algorithms to drive insights and value for businesses. #DataScience #MachineLearning #AI #DataEngineer

I've recently been working on a captivating course (lnkd.in/en39Yvrz) on building AI agents in the enterprise, which has been a remarkable experience. The course stands out as one of the most meticulously crafted and structured programs available for mastering AI, particularly AI agents, while steering clear of the hype often associated with such technologies. Aish(Aishwarya Naresh Reganti) and Kriti , the course instructors, adopt a problem-first approach throughout the curriculum, offering invaluable insights on the strategic application of AI solutions in real-world scenarios. Their incorporation of copyrighted materials derived from practical enterprise implementations adds a unique and enriching dimension to the learning experience. It's evident that both Aish and Kriti are not just experts in their field but also enthusiastic about imparting their knowledge and shaping the future of AI. I am genuinely grateful for the opportunity to be part of this educational journey and eagerly look forward to any upcoming initiatives from this dynamic team.

Sep 4, 2025

Sharas Vitalapuram

Product Manager, Operational BI Solutions

3 things about "Building Agentic AI Applications with a Problem-First Approach" that are changing how I think about building AI products: 1/ The Frank D'Souza insight that's keeping me up at night Former CEO of Cognizant predicted: AI-driven software development will fundamentally reshape SaaS. When custom software becomes cost-competitive with SaaS subscriptions, everything changes. Why accept 80% fit when you can have something built specifically for you? This transforms product strategy from "What features satisfy the majority?" to "How do we create tailored experiences for individual users?" 2/ The buzzword trap vs. real problem-solving I've noticed a clear pattern when evaluating AI talent and approaches. Some teams immediately jump to LangGraph, multi-agent systems, agentic RAG - pure buzzword theater without understanding the core problem. The better teams focus on user feedback loops, measurable outcomes, and real-world constraints first. This course reinforces that mindset: Start with the problem, not the shiny tools. Understand when agents add value vs. when they introduce unnecessary complexity. 3/ A systematic framework that cuts through noise with production-ready thinking The difference between impressive demos and systems that actually work in production? Systematic thinking about fallbacks, audit logging, security, user feedback loops. For PMs drowning in options, this framework provides clarity to go from problem identification to confident deployment decisions. Midway through but I'm already seeing clearer paths from problem to production. Guest insights like Frank's complement the problem-first approach beautifully. Course link: lnkd.in/gfBWEBZx Shoutout to Aishwarya Naresh Reganti & Kiriti Badam for building something this valuable. #AgenticAI #ProductManagement #ProblemFirstAI

Sep 4, 2025

Harsh Khatri

ML Engineer | Computer Vision | Gen AI

Hey LinkedIn fam. Thrilled to announce I've officially started "Building Agentic AI Applications with a Problem-First Approach" with Aishwarya Naresh Reganti and Kiriti Badam! Having followed their work and seen the incredible results from previous cohorts, I knew this was the right move. This course is a game-changer – truly cutting-edge and invaluable for navigating the complex world of agentic AI. It dives deep into essential concepts like RAG, advanced RAG, memory, agentic RAG, MCP, and much more, all with a practical, implementation-focused approach. If you're looking to cut through the hype and build a foundational understanding that does not expire with time, this is it. Plus, a little insider tip: the October cohort might be their last, so now's the time to join! Link - lnkd.in/dDhSCmpM

Sep 4, 2025

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chiheb dkhil

Practice Lead Cloud Platforms | DevOps | SRE | Observability

Just completed an incredible course on Agentic AI that completely transformed my approach to building AI systems: lnkd.in/e9bqCNk4 The Before: I was drowning in questions about AI agents—when to use them, which tools to choose, what architectures actually work in production. Despite hours of research, I felt overwhelmed and lacked the confidence to move forward. The After: This course gave me a systematic framework to: Assess whether agents are the right solution Design effective AI systems that deliver real value Navigate complexity while minimizing risk Confidently deploy agents to production The game-changer? It's not just about the technical details. This course taught me the critical skill of knowing when agents add value versus when they introduce unnecessary complexity—and how to demonstrate clear business impact. If you're working in AI and feeling lost in the sea of agentic AI options, this is the clarity you need to go from problem identification to production deployment with confidence. Highly recommend for anyone looking to level up their AI implementation skills! 💡 #AgenticAI #ArtificialIntelligence #AIAgents #ProfessionalDevelopment #TechSkills #MachineLearning Aishwarya Naresh Reganti Kiriti Badam

Sep 4, 2025

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Senthil Thyagarajan

Director Intelligence at Mekanism

Just completed “Building Agentic AI Applications with a Problem-First Approach” by Aishwarya Naresh Reganti and Kiriti Badam. Practical , more than theoretical - it pushed me beyond vibe-coding to building agents that are measurable, reliable, and useful. Building an agentic search system through iterations + early eval datasets changed my implementation playbook. The weekly Chai & AI sessions were especially valuable for pressure-testing ideas with practitioners. I wrote about it here: lnkd.in/en9Ap2v4

Sep 4, 2025

Vijay Kodam

I have spent 6 months learning Generative AI on my own before this course, so I was not starting from zero. As part of my learning, created my own Model Context Protocol and created couple of AI Agents as well. All this was done before the course. I joined the Maven course "Building Agentic AI Applications with a Problem-First Approach" after talking to the previous cohort members as they were mighty impressed with the course. Now that I have joined the course and almost completed it, I can 100% say that this has been totally worth it. After this course, I started thinking in first principles, and now have a solid foundation of Prompt Engineering, RAG, Memory, Tool calling, AI Agents, and MCP. I have also started reading research papers related to Gen AI. All thanks to Aishwarya Naresh Reganti and Kiriti Badam. On top of all that, there is an amazing network of alumni from the cohort and super-awesome guest speakers Pritika Mehta and Andre Kerr from the Industry. Icing on the cake is Chai & AI which is super hot with it's hot takes. It was great to learn from Francisco D'Souza and Jaya Gupta. Course URL: lnkd.in/db3sP4r5 Feel free to reach out to me if you have any questions choosing this course. Even though this is a GenAI course, this feedback and all it's grammatical mistakes were typed by my own fingers :) #ProblemFirstAI #LLM #GenAI

Sep 3, 2025

Nandhini Gunalan

Director of Quality Assurance / AWS Certified Solutions Architect Associate

Just wrapped up the Building Agentic AI Applications with a Problem-First Approach course on Maven — and what a ride! 🚀 I gained practical insights into designing AI agents that start with real-world problems, not just shiny tools. The hands-on approach and the Capstone project really changed how I think about deploying AI effectively. Huge thanks to the amazing instructors Aishwarya Naresh Reganti and Kiriti Badam for their guidance and clarity throughout. 🙏 Excited to apply these learnings to build smarter, more purposeful AI solutions! #AI #AgenticAI #AIApplications #LangChain #RAG #WorkflowAgents #AIProductThinking lnkd.in/eHrpWnjC

Jun 28, 2025

Ginger Hildebrand

from zeroes to ones | digital executive driving scalable impact | transforming energy through digital

Digging into Agentic AI: Problem First, Technology Next I am wrapping up the “Building Agentic AI Applications with a Problem-First Approach” course by Aishwarya Naresh Reganti and Kiriti Badam—and it’s been a refreshing reset from the noise around GenAI. This course didn’t focus on the latest hype, tool or technique. It focused on how to think. How to frame problems clearly. And how to make intentional design choices in a space that’s evolving faster than most organizations can absorb. A few reflections that stuck with me: ✨Start with the problem, not the tech. The problem that you are trying to solve determines what technical approach to take. Use the simplest technology that solves the problem. ✨Use GenAI and agents where deterministic tools break down. These non-deterministic technologies are not magic. It takes work to use them safely and effectively in enterprise solutions. ✨Context is important. There are no absolutes in this space. The answer is often “it depends”. Focus on understanding the Whys over the Hows. Ask lots of questions – about the data, the environment, the constraints. Thinking is still required with AI. ✨The hard part is not the implementation. With AI solutions designing the solution is the hard part – even with full access to AI. ✨Most successful AI products have a well defined evaluation loop and an iterative design. Design a v0 quickly and iterate. Solve problems in the simplest possible way and then evaluate what you have. Use that evaluation to determine next steps. What set this course apart was its focus on decision scaffolding—helping leaders design with clarity, not just implement with speed. It emphasized foundational thinking that will not expire with the next release cycle. No affiliate links here—just appreciation for a learning experience that respected the complexity and potential of this space. #AI #AgenticAI #DigitalTransformation #AILeadership

Jun 26, 2025

Jasen Lew

AI Entrepreneur, CEO, Investor, Advisor and Speaker. YC W18.

🎉 Proud to share that I've completed "Building Enterprise Agentic AI Applications with a Problem-First Approach"! 🤝 Learning and working alongside exceptional professionals from around the globe made this experience truly enriching - thanks to all my cohort colleagues. 🏆 I'm also truly honored and humbled to have earned 1st place in our final capstone project. 📣 A huge shoutout to our world-class instructors Aishwarya Naresh Reganti and Kiriti Badam who designed an incredibly thoughtful and challenging curriculum that built upon existing knowledge and elevated it to a deeper understanding of what's possible. 🚀 Excited to apply these learnings and continue pushing the boundaries of what's possible with enterprise AI applications for hospitality and beyond! #AgenticAI #EnterpriseAI #ProfessionalDevelopment #AIApplications #AIStrategy #ContinuousLearning #DigitalTransformation #HospitalityTech

Jun 29, 2025

Akshay Menon

Manager ML & AI - Finance @ HubSpot

Had an absolute blast this past month learning from some of the best in the enterprise AI agents space — Aishwarya Naresh Reganti and Kiriti Badam. Thank you both! Getting to learn and collaborate with exceptional Tech professionals from around the globe made this experience truly enriching. This course fundamentally rewired, how I think about building enterprise-ready AI agents and solutions. The emphasis on obsessing over the problem, the persona, and evaluating every interaction before jumping into code was a core takeaway. The AI space(mcp/a2a/evals..) evolves every day, but these fundamentals remain constant. For those who know how passionate I am about competitive intelligence space - I had an incredible time building a CI autonomous agent with Nirnay Patel as part of our capstone project in the final week. Excited to bring these insights back and help supercharge HubSpot Finance's AI journey!

Jul 2, 2025

Abhijith Neerkaje

I’m halfway through Building Agentic AI Applications with a Problem-First Approach, taught by Aishwarya Naresh Reganti and Kiriti Badam, and it’s been one of the most thoughtfully designed and insightful courses I’ve taken. A key highlight is the decision-making framework for designing AI agents — a principled approach to choosing between architectures based on cost, latency, and performance. It’s super valuable for anyone building production-ready AI systems. The course is hands-on from the start. Depending on your coding background, you build agent workflows using LangChain or LangFlow. There’s a running example where we build a “Perplexity Light”, and we end with a capstone project that brings everything together. It’s also my first experience with a flipped classroom format — we go through lectures at our own pace, and then meet to discuss the content and assignments. I’m really enjoying the depth and engagement this structure brings. This course is ideal for Tech and Data Leaders, Architects, and Product Managers who want to move beyond theory and build scalable agentic systems with confidence. The energy, clarity, and experience that Aish and Kiriti bring to the course — along with guest speakers from industry who’ve built real-world agents is very valuable. Great work guys. #AgenticAI #AIagents #LLMs #LangChain #LangFlow #TechLeadership #ProductManagement #AIArchitecture #HandsOnLearning #FlippedClassroom #CapstoneProjects #PerplexityLight #ContiniousLearning

Jun 12, 2025

Trupti Veer

Senior Technical Specialist | Generative AI & LLM

The GenAI System Design course led by Aishwarya Naresh Reganti and Kiriti Badam stands out as an exceptional, hands-on program for anyone serious about building real-world Generative AI systems. Unlike many theoretical overviews, this course dives deep into the practicalities of designing, deploying, and scaling effective GenAI applications for business needs Key Learnings and Takeaways: 1. Start Simple, Build Vertically: One of the most valuable lessons was the importance of starting with simple solutions and iterating vertically, focusing on depth and refinement rather than spreading efforts too thin. 2. Context is King: The course stressed that the real challenge in GenAI isn’t just model selection—models will increasingly become commoditized—but in providing the right context. Techniques like Retrieval-Augmented Generation (RAG) were explored in depth to address this. 3. Efficiency and Optimization: Practical strategies for cost and performance optimization, such as semantic caching and chunking strategies, were covered, along with advanced RAG variants like Graph RAG and Corrective RAG. 4. Workflows vs. Agents: The distinction between simple AI workflows and more complex agent-based approaches was made clear, including criteria for when to use multi-agent systems (only when a single agent cannot solve the problem). 5. Observability and Guardrails: The importance of observability for non-deterministic agent systems was emphasized, as well as the need to always consider cost, latency, and robust guardrails in production systems. Iterative Design: The course reinforced that effective GenAI system design is inherently iterative, requiring ongoing evaluation and adjustment. I would highly recommend this course to each and everyone who wants to take a deep dive into building Agentic AI applications with a problem first approach lnkd.in/dP3Rj5WB Thanks a lot Aishwarya Naresh Reganti and Kiriti Badam for this amazing course. Its very unique course with well thought out and structured content. Kudos to you for making these complex topics so easy to understand!

Jul 1, 2025

Hemant Barai

Agentic AI certified , Data enthusiast, Problem solver

🎓 Just wrapped up an incredible learning journey — officially certified in the Problem-First Approach to AI by Aishwarya Naresh Reganti and Kiriti Badam! 🚀 Before this, I was mostly focused on the tech side—playing with prompts, models, and tools. But this course made me step back and ask a simple yet powerful question: What problem am I really trying to solve? That shift in perspective made all the difference. One moment that really stuck with me was early on when I built a simple router to decide whether to answer a question with a calculator or a factual response. I tested it with “What is 2+2?” and the system kept choosing the factual answer instead of calculating. At first, I thought something was broken. But then I realized: it was about context and intent—how the AI interprets the prompt matters as much as the code behind it. That was a real lightbulb moment. It taught me that building AI isn’t just about coding or using models. It’s about designing how AI understands and interacts with real people and their problems. That mindset has changed how I approach AI projects since. The course also gave me a community and real-world insights from guest speakers, which made the whole experience richer. The live sessions and “Chai & AI” hangouts felt more like conversations with peers than lectures. If you want to build AI that actually helps solve problems instead of just tinkering with technology, I’d highly recommend this course. It’s practical, thoughtful, and eye-opening. #AgenticAI #EnterpriseAI #AIForGood #ProblemSolving #DigitalTransformation #Teamwork #ContinuousLearning

Jul 1, 2025

Edward Un

AI Product Leader | ex-Microsoft, former Head of Product at Resemble AI

Excited to share that I’ve completed the Maven course Building Agentic AI Applications with a Problem-First Approach! It was a great foundation for designing AI Agents grounded in real user problems, with practical focus on RAG, LangGraph, and tool use with MCP. For the Capstone project, I proposed the idea and collaborated with the team to build an AI Agent that leverages reading and podcast highlights (collected with Readwise) and turns them into a personalized experience that promotes long-lasting learning and behavior change. Big thanks to Aishwarya Naresh Reganti and Kiriti Badam for the well-designed course structure and hands-on focus. Always be Learning. The gap year is for growth, not standing still. #AlwaysBeLearning

Jul 4, 2025

Luca Mastrini

Global Vice President Engineering Services @ Backbase | Master's in CS

For those seeking to determine if AI is the solution they need and how to best put it to work, this course will show you how. Thank you Aishwarya Naresh Reganti and Kiriti Badam for sharing your time and knowledge. lnkd.in/d4-hgrrD #AI #AgenticAI #ProblemSolving #Engineering #TechEducation #Innovation #ContinuousLearning #BusinessValue

Jun 30, 2025

Arthi Subramanian

Agentic AI, Generative AI, Machine Learning | Government & Public Sector

Just wrapped up the "Building Agentic AI Applications with a Problem-First Approach," taught by Aishwarya Naresh Reganti and Kiriti Badam. It stands out as one of the most thoughtfully designed and insightful courses I've experienced. A key highlight was learning how to use a "problem first/tool second" decision-making framework for designing AI agents. This principled approach helps in selecting stack and architectures based on cost, latency, and performance, making it invaluable for those developing production-ready AI systems. What I liked the most about the course style however was it was designed to work with both functional and technical skillsets. Depending on your coding background, you can build agent workflows using LangChain or LangFlow. A running example involves creating a "Perplexity Light," culminating in a capstone project that integrates all learned concepts. This was also my first encounter with a flipped classroom format, where we independently go through lectures at their own pace, try hands-on assignments, and later meet to discuss as needed. It was one of the best examples of "Learning By Doing" which really allowed the content to resonate. The guest speakers (some of whom had actually build real-world Agentic and Autonomous AI solutions) and "Chai and AI" discussion sessions were enlightening as well. The course is ideal for Tech and Data Leaders, Architects, and Product Managers aiming to move beyond theory and confidently build scalable agentic systems. Special thanks to Deloitte and Brook Russi for this opportunity and Alayna Ruberg, Ben Dizon, Bhavani Singh, M.S., Samantha Chill, Tyler Wallace, and Whitney Leet Do for being such a great capstone project team! #AgenticAI, #GenerativeAI #MavenLearning #ProblemFirstDesignSecond #Agents #AutomonousAI, #AIinEverything lnkd.in/gSAsrf7m

Jun 28, 2025

Sumedha Saini ✨

Head of Engineering | Senior Technical Leader| People and Team Excellence

I'm officially past more than halfway through Maven's Building Agentic AI Applications with a Problem First Approach course 🐢 , and honestly, it's less a course and more a series of profound "aha!" moments. So much of the AI world is shrouded in hype, but Aishwarya Naresh Reganti and Kiriti Badam, the brilliant Cohort Instructors, are absolute masters at stripping it all away. They're teaching to build Building Agentic AI Applications from first principles perspective, which is relatable and fundamental to my own approach to learning and solving real world problems. Throughout the course, their focus has been simplifying complex concepts and making advanced topics genuinely accessible. Some key concepts covered in the course: Demystifying the AI Landscape systematically: This course expertly unpacks the entire AI spectrum, from core ML to Deep Learning, GenAI, and Agentic AI. It doesn't just define them, it clarifies their interplay and when to strategically apply each, providing a rare, holistic perspective on the modern AI stack. Engineering GenAI for Reality: We're learning to design robust AI solutions that thrive amidst real world challenges like non determinism, prioritising data's critical role, and making astute setup choices. It’s about building iteratively, ensuring solutions are practical and effective from day one. Beyond Basic Prompts: The evolution of prompt engineering is thoroughly explored, moving from simple commands to advanced reasoning models and workflow agents with tool calling capabilities. This is key to architecting sophisticated AI interactions, not just generate text. Mastering Deployment : Launching AI isn't just about building. The course provides crucial insights into strategic guardrails, MCP, comprehensive evaluation methods (including LLM judges), and cost optimisation. It’s about ensuring AI systems are not only performant but also production ready. Building Scalable & Smart Architectures: We're diving deep into advanced RAG techniques, selecting the right embeddings and vector databases, and understanding various Agent memory types. Crucially, it clarifies the leap from single to multi agent systems, offering clear comparisons like RAG vs. Fine Tuning for real world enterprise ecosystem. If you're tired of buzzwords and ready to truly understand how to design, build, and reason about Generative AI systems and effective workflow agents for the enterprise with clarity, depth, and an enterprise mindset, check out the next cohort of this course. "This isn't just theory, it's tangible, high value learning that prepares you for real impact." Their next cohort is running on a special for a very limited time. So grab your place now : lnkd.in/g27CKWR7

I'm officially past more than halfway through Maven's Building Agentic AI Applications with a Problem First Approach course 🐢 , and honestly, it's less a course and more a series of profound "aha!" moments. So much of the AI world is shrouded in hype, but Aishwarya Naresh Reganti and Kiriti Badam, the brilliant Cohort Instructors, are absolute masters at stripping it all away. They're teaching to build Building Agentic AI Applications from first principles perspective, which is relatable and fundamental to my own approach to learning and solving real world problems. Throughout the course, their focus has been simplifying complex concepts and making advanced topics genuinely accessible. Some key concepts covered in the course: Demystifying the AI Landscape systematically: This course expertly unpacks the entire AI spectrum, from core ML to Deep Learning, GenAI, and Agentic AI. It doesn't just define them, it clarifies their interplay and when to strategically apply each, providing a rare, holistic perspective on the modern AI stack. Engineering GenAI for Reality: We're learning to design robust AI solutions that thrive amidst real world challenges like non determinism, prioritising data's critical role, and making astute setup choices. It’s about building iteratively, ensuring solutions are practical and effective from day one. Beyond Basic Prompts: The evolution of prompt engineering is thoroughly explored, moving from simple commands to advanced reasoning models and workflow agents with tool calling capabilities. This is key to architecting sophisticated AI interactions, not just generate text. Mastering Deployment : Launching AI isn't just about building. The course provides crucial insights into strategic guardrails, MCP, comprehensive evaluation methods (including LLM judges), and cost optimisation. It’s about ensuring AI systems are not only performant but also production ready. Building Scalable & Smart Architectures: We're diving deep into advanced RAG techniques, selecting the right embeddings and vector databases, and understanding various Agent memory types. Crucially, it clarifies the leap from single to multi agent systems, offering clear comparisons like RAG vs. Fine Tuning for real world enterprise ecosystem. If you're tired of buzzwords and ready to truly understand how to design, build, and reason about Generative AI systems and effective workflow agents for the enterprise with clarity, depth, and an enterprise mindset, check out the next cohort of this course. "This isn't just theory, it's tangible, high value learning that prepares you for real impact." Their next cohort is running on a special for a very limited time. So grab your place now : lnkd.in/g27CKWR7

Jun 23, 2025

Venkat Krishnamurthy

Digital and Enterprise Applications | Delivery and P&L | GenAI and Agentic AI | Low-Code Passionate about enabling enterprises through technology and process-aligned transformations

If anyone had spoken to me a month ago about Langflow, I would have thought of it as a language-enabler tool [pun intended] However, 3 weeks into the "Building Agentic AI Applications with a Problem-First Approach" by Aishwarya & Kiriti, I’ve already built my first working GenAI workflow using Langflow I’d definitely not call myself a GenAI or Agentic AI expert right now, however, being part of this cohort has helped me get over the FOMO A few highlights from the course: 1) Clarity of thought, amazing articulation and intonations, and seamless flow in the session lectures and discussions (pre-recorded, and live Office hours) 2) Well-defined scope and structure for the core content – not too vast trying cover everything under the sun, while still following a neat and clear structure from basic prompting to LLMs, LRMs, RAG, MCP, A2A all the way to building Agentic AI solutions 3) Lectures and courseware that covers real, hardcore design frameworks, considerations, explained in great level of detail. Many of the lessons deserve repeat watching to absorb & internalize the depth of the content and spin up thoughts around them · Alert: This is not the "Build and Launch your first Agentic AI app in 10 days" kind of course. You need to let it seep in, depending on where you start from. 4) Lot of emphasis on practical design and solution considerations focusing on the problem to solve rather than thrusting an AI solution into the mix 5) Structured lectures, with weekly office hours to discuss questions on the lecture content and assignments 6) Weekly banter room, titled “Chai and AI” wherein the latest in the world of AI, GenAI, etc. are discussed. This is one of the forums where everyone gets lit up :-) 7) Regular sessions with practitioner-leaders from the industry 8) Weekly assignments to get your hands dirty, with follow-up clarification sessions 9) An effective support team that is always happy to help you (Ashu, Sahana, Mel, et al) 10) Options to build with Low-Code as well as regular coding platforms (Langflow vs LangChain/ LangGraph), though it’s quite evident that the code-based platforms beat the low-code hands-down for building enterprise-scale solutions 11) Last but not least, an amazing cohort of geeks, intelligent students, battle-hardened pros, and then, myself 😉 I’m still finding my way past the one-third mark, but I’m loving it and looking forward to the Capstone project starting in the next couple of days. If you are the kind that loves to understand the core concepts, build hands-on and dig in further, you should sign-up for their next cohort - Link in Comments: [link includes Maven’s ongoing, limited-time promo offer that ends Sunday, the 22nd of June] Aishwarya Naresh Reganti Kiriti Badam Not a Sponsored post! In Pic: A screenshot of my first working Langflow application. Learning to build what I love ✌

If anyone had spoken to me a month ago about Langflow, I would have thought of it as a language-enabler tool [pun intended] However, 3 weeks into the "Building Agentic AI Applications with a Problem-First Approach" by Aishwarya & Kiriti, I’ve already built my first working GenAI workflow using Langflow I’d definitely not call myself a GenAI or Agentic AI expert right now, however, being part of this cohort has helped me get over the FOMO A few highlights from the course: 1) Clarity of thought, amazing articulation and intonations, and seamless flow in the session lectures and discussions (pre-recorded, and live Office hours) 2) Well-defined scope and structure for the core content – not too vast trying cover everything under the sun, while still following a neat and clear structure from basic prompting to LLMs, LRMs, RAG, MCP, A2A all the way to building Agentic AI solutions 3) Lectures and courseware that covers real, hardcore design frameworks, considerations, explained in great level of detail. Many of the lessons deserve repeat watching to absorb & internalize the depth of the content and spin up thoughts around them · Alert: This is not the "Build and Launch your first Agentic AI app in 10 days" kind of course. You need to let it seep in, depending on where you start from. 4) Lot of emphasis on practical design and solution considerations focusing on the problem to solve rather than thrusting an AI solution into the mix 5) Structured lectures, with weekly office hours to discuss questions on the lecture content and assignments 6) Weekly banter room, titled “Chai and AI” wherein the latest in the world of AI, GenAI, etc. are discussed. This is one of the forums where everyone gets lit up :-) 7) Regular sessions with practitioner-leaders from the industry 8) Weekly assignments to get your hands dirty, with follow-up clarification sessions 9) An effective support team that is always happy to help you (Ashu, Sahana, Mel, et al) 10) Options to build with Low-Code as well as regular coding platforms (Langflow vs LangChain/ LangGraph), though it’s quite evident that the code-based platforms beat the low-code hands-down for building enterprise-scale solutions 11) Last but not least, an amazing cohort of geeks, intelligent students, battle-hardened pros, and then, myself 😉 I’m still finding my way past the one-third mark, but I’m loving it and looking forward to the Capstone project starting in the next couple of days. If you are the kind that loves to understand the core concepts, build hands-on and dig in further, you should sign-up for their next cohort - Link in Comments: [link includes Maven’s ongoing, limited-time promo offer that ends Sunday, the 22nd of June] Aishwarya Naresh Reganti Kiriti Badam Not a Sponsored post! In Pic: A screenshot of my first working Langflow application. Learning to build what I love ✌

Jun 19, 2025

Shrey Datta

Analytics @ Hinge Health

🚀 Week 3 into "Building Agentic AI Applications with a Problem-First Approach" by Aishwarya Naresh Reganti & Kiriti Badam, and I’ve already experienced a major mindset shift. One of my biggest takeaways? 👉 I’ve finally overcome the fear of the complex AI jargon I used to see on LinkedIn. Aishwarya and Kiriti do a phenomenal job simplifying even the most intimidating GenAI concepts — making them not just understandable, but actionable. The course blends: 🔹 A problem-first lens to agent design 🔹 Decision-making frameworks for choosing the right AI architecture 🔹 Hands-on projects every week (yes, I’m actually building with LangChain + LangGraph!) 🔹 A flipped-classroom format that encourages deeper learning 🔹 A super-engaged, curious cohort that makes learning fun and collaborative If you’re someone who’s been curious (or overwhelmed) about building AI systems that are scalable, contextual, and production-ready — I couldn’t recommend this course more. 💡 The next cohort is live — check it out here: lnkd.in/gWsFbkEM Thank you Aishwarya Naresh Reganti and Kiriti Badam for making such a complex field feel so human. #AgenticAI #LLMs #AIagents #LangChain #LangFlow #ProblemFirstApproach #AIProduct #TechLeadership #HandsOnLearning #FlippedClassroom #CapstoneProjects #PerplexityLight #AIArchitecture #ContinuousLearning

Jun 14, 2025

Dev Jadhav

ML & Data Ops Architect | Transforming Data into Business Opportunities | Proven Track Record in DevOps, MLOps and DataOps Execution | I help Startups Build End-to-End ML and Data Platforms for Scalable Growth

🚀 I'm currently in the middle of the Building Agentic AI Applications with a Problem-First Approach course by Aishwarya Naresh Reganti and Kiriti Badam, and it’s been an incredible learning journey so far! As someone who’s a bit more introverted and usually doesn't speak up much, I’ve still found myself deeply engaged—thanks to the clarity, depth, and practical insights shared by both the instructors and fellow participants. The course dives into not just the “how” but the “why” of Agentic AI system design, with a strong emphasis on solving real business problems. My understanding of techniques like RAG (Retrieval-Augmented Generation), agentic workflows, and evaluation frameworks in enterprise environments has improved tremendously. 💬 What’s truly unique is the community aspect—hearing how others are approaching similar challenges across industries has been just as valuable as the structured content. 💡 If you're looking to move beyond the hype and actually build scalable, responsible Generative AI applications with a strong architectural foundation—this course is for you. There’s currently a 20% discount available until Sunday with the code MAVEN100. 👉 Enroll here: lnkd.in/eJUYAbmp #GenAI #AgenticAI #SystemDesign #EnterpriseAI #RAG #AIEngineering #AIApplications #Maven #LearningJourney #AICommunity

Jun 17, 2025

Gary Wong

GenAI Transformation Leader | Volaris AI/ML Center of Excellence Member | Champion of Augmented Intelligence | Driving AI-Powered Innovation & High-Performance Teams

I’ve been getting a few DMs asking me to share the Chai & AI session or forward the invite. So here’s the deal: What happens in Chai & AI, stays in Chai & AI. There’s no recording, and I can’t forward you the meeting invite. 🙅‍♂️ The only way to join is by enrolling in the Maven course: “Building Agentic AI Applications with a Problem-First Approach” by Aishwarya Naresh Reganti and Kiriti Badam. And trust me, it’s one of the best investments I’ve made in myself earlier this year. Not just for learning how to build AI applications with purpose, but also for surrounding myself with an incredible community of curious, talented, and inspiring people. So if you're serious about AI, strategy, and building what’s next, here is the link to join the cohort. Next Cohort start July 26. maven.com/aishwarya-kiriti/genai-system-design …more

Jul 8, 2025

Gary Wong

GenAI Transformation Leader | Volaris AI/ML Center of Excellence Member | Champion of Augmented Intelligence | Driving AI-Powered Innovation & High-Performance Teams

So grateful to be part of this incredible #Cohort1 journey! 🙌 Thank you, Aishwarya Naresh Reganti and Kiriti Badam, for creating such a powerful learning experience. I loved your clear, direct teaching style — it made everything click. Looking forward to revisiting the materials and getting even better at it! 💪

Jul 8, 2025

Michèle Notice

Product Management | Global Digital Service Delivery Management | Product Development | Tennis enthusiast and unapologetic Venus Williams and Rafa Nadal fan!

I’m happy to share that I’ve obtained a new certification: Building Agentic AI Applications with a Problem-First Approach from Maven! As a Product Manager, I found the problem-first approach particularly valuable: it grounded the learning in real-world use cases while introducing technical concepts in a way that made sense. Many thanks to Aishwarya and Kiriti for creating a fun learning environment that encouraged curiosity, clarity, and collaboration. It was over too soon! :-)

Jul 4, 2025

Abdul Khader Abdul Hanif

Cloud Security and Platform Architecture | Cloud Advisory | Blockchain audits

🎓 Excited to share our capstone project demo: Complychain for Regxperience - an agentic system that helps SMBs navigate the complex world of AI compliance! Just completed my certification in Building Agentic AI Applications: A Problem-First Approach, and as part of the project demo we took on the Complychain idea proposed by one of our Cohorts - how organisations can keep pace with rapidly evolving AI regulations while proving ongoing compliance. Our solution: A three-agent system that: 🔍 Provides visibility of AI assets across organizations 🗺️ Maps them to live regulatory obligations (NIST AI RMF, EU AI Act) 📝 Perform Compliance assessment with Human-in-the-loop feedback based on documentation and evidence packs The MVP demonstrates the power of agentic AI in regulatory technology - turning compliance from a reactive burden into a proactive advantage. Huge thanks to my project team mate Divya Venkatraman, PhD and to our instructors Aishwarya Naresh Reganti and Kiriti Badam for their insights throughout this journey. The depth of learning and practical application in this program has been exceptional. Demo slides attached! Would love to hear thoughts from the community. For anyone considering similar training in AI/ML applications - highly recommend exploring these hands-on programs that bridge theory with real-world implementation. #AICompliance #RegTech #AgenticAI #MachineLearning #Capstone #ProfessionalDevelopment

Jul 3, 2025

Arun Mandhania

Looking for AI related roles (Consulting/FT/PT) | server-style leader | learner

If you are excited about the AI wave, and want to move beyond the POCs and demos, I highly recommend enrolling in this “Building Agentic AI Applications with a Problem-First Approach" bootcamp by Aishwarya Naresh Reganti and Kiriti Badam I am part of the current cohort, and this course has been amazing. I have learnt a lot about “behind the covers” aspects of Enterprise AI solutions: how to build them, what could go wrong and how to design solutions for them. While the course is a bit fast-paced, the material is very well organized, detailed and also covers an overview of how we got here so that we can appreciate the changes. It covers prompt engineering, RAGs, MCP, model selection, Observability, and many related topics. And, there is life time access to the course materials. In addition to the materials, the setup is highly cooperative with plenty of opportunities to ask questions in live meetings as well as via Slack. The discussions have been very rich and invaluable with participants from many different industries, roles and locations. An added bonus is many guest lectures and presentations by the practitioners, and builders from the industry. They share their challenges as well as approaches they are taking to solve them. A key aspect I appreciate is the emphasis on thinking of the problem first, and evaluating if Agentic AI is the right solution for it, instead of focussing on how you can use the cool technology. Next week promises to be even more exciting as we will be applying the learnings to build a capstone project. If you want to know more about my experience, please DM me. BTW, there is a special discount that lasts till Sunday. Here is the registration link: lnkd.in/gTPyZka3

Jun 19, 2025

Alicia Miller

Strategy | Analytics | AI Readiness and Org. Change grounded in expertise in human behavior and mixed-method research

AI Course Reviews! Coming out of CincyAI week, I had several people ask about courses to skill up in AI, so I'm sharing one course for anyone looking to learn how to build agents and personal co-pilots. AI developments are rapidly expanding, with a plethora of AI tools that you can use. Many people are stuck feeling overwhelmed, trying to figure out where to start and putting things off for later. Is that you? If this has been a goal that you haven't moved forward, this may be a class for you. Here's what I liked: - Sequenced, structured content to build core understanding and foundations - Hands-on assignments to build technical competencies (including Low-Code options) - Knowledgeable instructors with live Q&A (They also stay abreast of changes and are updating the content so that the course content remains current.) - Cohort focused, providing an extended professional network to learn with and learn from - Opportunity to attend guest lectures with leaders and professionals driving AI solutions in the market and at well-known organizations pioneering use cases Aishwarya Naresh Reganti Kiriti Badam lnkd.in/d2YufuyR

Jun 19, 2025

Maximo Pacheco

Machine Learning Developer @ GlobalLogic | AI Engineering student at UNL

Continuing with my learning journey, I am at week 3 of "Building Agentic AI Applications with a Problem-First Approach", a really good course and what was a plus to me was the idea of doing a project for every week in the course which makes you learn more since you are recurrently putting your hands dirty 😂. Thanks to Aishwarya Naresh Reganti and Kiriti Badam for giving such amazing lessons and to GlobalLogic for bringing this course to the table and promote continuous learning in such a changing field 💡 .

Jun 12, 2025

Anil Yanamandra

Engineering Leader | Mobile | Gen AI | Agentic AI | Lead 50+ Mobile apps including multi-million user chart toppers

How is your AI learning journey going? Does it feel like everyone and their dog has an AI course to sell to you? Not sure where to start? Or how to keep up? Been there! After a lot of exploration, failed personal learning plans, online resources/courses, I found myself in the second cohort of the chart-topping Maven course - Building Agentic AI Applications with a Problem-First Approach, taught by Aishwarya Naresh Reganti and Kiriti Badam (lnkd.in/gTPyZka3) I am already in week 3 of the course and a few things I can vouch for: - Focus on Enterprise Thinking from the start - Well curated, well-structured, thorough, and relevant content, and a distilled thought framework. The When, Why, and How of Enterprise AI - Guest Speakers that have executed large-scale enterprise GenAI apps in production - Amazing cohort and alumni community! A diverse mix of professionals from various functions, domains, industries, and timezones, approaching from distinct POVs, amplifying the collective learning experience - Hands-on projects every week I will share my reflections from the course over the coming weeks but wanted to quickly highlight that registrations for the next cohort are now open. 10/10 will recommend! 🚀 DM me for any additional questions on the course.

Jun 12, 2025

Preetam Shingavi

> Staff Software Engineer @ Walmart Global Tech > Exploring Generative AI & sharing what I learn

Thrilled to be in Week 3 of the ‘Building Agentic AI Applications with a Problem-First Approach’ course with Aishwarya Naresh Reganti and Kiriti Badam at Maven! 🚀 The course has been incredibly insightful, sparking new ways of thinking about AI. The discussions and insights shared by the cohort have been truly energizing. Major thanks to Aishwarya and Kiriti for creating such an engaging learning environment. #AI #AgenticAI #MavenCourses #Learning #Technology

Jun 12, 2025

Francesco Maiorano

Machine Learning & AI Innovation | Railway & Manufacturing Specialist

🚀 Strengthening Expertise in Agentic AI Thrilled to have completed the Building Agentic AI Applications with a Problem-First Approach certification from Maven! A big thank you to Aishwarya Naresh Reganti and Kiriti Badam for an outstanding course. The structured approach, deep dive into research papers, and hands-on coding exercises made it a valuable experience—even for those already applying these concepts. One of the most interesting challenges was refining multiple agents orchestration, balancing autonomy and collaboration in complex workflows. Putting this into practice with LangChain and LangGraph allowed me to push my implementations further, testing new ideas and optimizing agent interactions. Always room to improve, always more to explore—looking forward to continuing the journey. 🚀 Thanks to all who made this possible Gianfranco Messina #AI #MachineLearning #LangChain #LangGraph #AgenticAI #Innovation #ContinuousLearning

Apr 22, 2025

Fikayo Adepoju Oreoluwa

Author at LinkedIn | Technical Writer | Software Developer

Start with the Problem, not the AI I’ve been following Aishwarya Naresh Reganti's 10-day Agents email course (super amazing by the way) for some days now and this really stood out for me. While planning to integrate AI into your workflow, it’s common to make the mistake of trying to pick “the best Agent framework” or “your favourite Agent Architecture”. This foundational mistake can derail your agent adoption quickly. To avoid this early pitfall, consider the problem at hand, understand it’s requirements, then pick the Agent implementation type that best suites the problem you’re out to solve. Below is a cool guide that came with the email course to help you pick which agentic implementation strategy best suites your use case.

Apr 12, 2025

Govind Manoharan

Technical Architect

💥 Wrapped up the “Building Agentic AI Applications with a Problem-First Approach” course — easily one of the best I’ve taken. 💥 Great content and awesome instructors (shoutout to Aishwarya Naresh Reganti and Kiriti Badam 🙌). I went in slightly intimidated by Gen AI and came out a lot more confident—and a lot less likely to just smile and nod in AI conversations 😅. If, like me, you’ve been reading about Gen AI from all corners of the internet, dabbled with a few PoCs, and felt overwhelmed, I highly recommend giving this course a shot. With the pace at which the field is evolving, it does a great job of keeping you focused on what really matters—not just the latest flashy headline 🚀. Guest lectures from industry experts gave real-world perspective, and the assignments were genuinely well-designed—challenging, practical, and enjoyable 💯.

Apr 10, 2025

Vasanthi Jagatha

Sr. Manager, Product Management & Marketing

Really enjoyed this course! It gave me the framework to critically think through the benefits and trade offs of using AI components (Prompt engineering, RAG, Agents, Fine tuning) to solve Enterprise challenges. I particularly valued the talks by leaders in this space who dropped the hype and kept it real.

Apr 1, 2025

Nadia V. Gil

Chief Strategy M&A /Corporate Development and Operations Officer | AI, ML, Cybersecurity & Cloud innovator | Early seed investor

Sharing my #certification on "Building #GenAI / #Agentic #Apps with a Problem-First Approach" from Maven As a senior executive in #strategy, this training provides a unique edge when guiding AI use cases and strategic #investment decisions (e.g. use cases, #MandA, #CVC, early seed investing and due diligence). I have found that, knowing first hand how these agents/applications are built and function is a unique insight that helps cut through the misconceptions many C-level executives and #Boards have about what GenAI and agents can and cannot do. I've taken a few of #AI and agentic #trainings with mixed results (too theoretical, too basic, or lacking sufficient theory), I found Aishwarya Naresh Reganti and Kiriti Badam's program to be exceptional. They strike the right balance between theory, complexity and resurfacing our seldomly used #coding skills. The highlights of this experience included: * Learning how to #build GenAI agentic #products that solve corporations #strategic problems that *actually matter* * Gaining practical #insights into business strategy AI applications; and above all: * Working with an amazing #cohort of competitive, yet generous, supportive, and enthusiastic fellow AI students (I'm going to miss this cohort!) This certification equips me to better evaluate strategic AI opportunities and implement solutions that deliver genuine business value. I'm grateful for the experience and looking forward to applying these skills! #earlyseedinvesting #AIusecases #AIagents #agents cc Ravi Kiran Nukala Roopa Prakash Vasanthi Jagatha Shabareesh Raj Sahana Venkatesh Diana Gutierrez Lopez, PhD

Apr 1, 2025

Wall of love for Building Agentic AI Applications with a Problem-First Approach