I just completed the AI Product Management class successfully.
Firstly, I did my due diligence before signing up for the class so my expectations were already set - Jyothi is a seasoned product professional, with tons of experience in the AI space at Meta; Netflix and other Fortune 500 companies so she brings this real life experience into her teaching approach.
The course material and pace was perfect - with some self effort with homework and projects, but it was fun.
I would recommend this class to anyone that wants to learn and understand the fundamentals of AI Product management. I'll be signing up for Jyothi's next Advanced Agentic class.
AL
Akash L.
This course offers extensive learning…
This course offers extensive learning opportunities combined with clear explanations, real-life examples, practical hands-on experience, and an outstanding capstone project, all designed to inspire confidence and foster growth.
HD
Hemangi D.
A Practical and Thoughtful Approach to Learning AI Product Building
I recently completed the AI PM cohort with Jyothi and wanted to share my experience for fellow experienced PMs as well as professionals looking to transition into Product or deepen their understanding of AI-driven product development.
Jyothi is an excellent instructor who has the rare ability to break down complex, rapidly evolving AI concepts into practical, easy-to-understand learning nuggets, especially for people newer to the space.
One of the biggest takeaways for me was developing stronger AI discernment — understanding when to use AI, when not to use it, and how to apply it thoughtfully instead of simply following the AI hype cycle. That required fresh thinking and a deeper grounding in AI fundamentals rather than surface-level experimentation.
As a product builder working across regulated industries and advising clients on if, when, and how to employ AI and Agentic AI to generate real ROI, this course became an important foundational building block for me.
What made the experience especially valuable was Jyothi’s real-world industry perspective and depth of AI knowledge, which strongly complemented my Classical AI and Machine Learning background while helping me bridge it into Generative and Agentic AI
I also appreciated that this was a fast-paced cohort. As a working professional, I personally did not want to spend months learning theory in isolation. The structure kept it engaging, practical, and immediately applicable. I still spent a few additional hours every week outside class reinforcing the concepts, which I believe was pivotal to getting the most value from the program. I will advice anyone thinking about AI to take this foundational class.
The hands-on projects and capstone work were another standout part of the cohort. They provided practical exposure, deeper insights into real-world AI product challenges, and most importantly the confidence to apply these learnings beyond the classroom.
ST
Shabarish T.
I came here to learn AI PM. I left as an AI builder in making.
I came into this course with one goal: transition into AI Product Management. Nine classes later, I have a live AI agent in production and the confidence to build more.
My capstone project, CareNav, is a healthcare navigation assistant that triages symptoms, finds affordable nearby clinics, and books appointments — built on Relevance AI, fully live, and portfolio-ready. That alone was worth the investment.
What makes Jyothi stand out is how she keeps everything grounded in product decisions. Every technical topic — ML, computer vision, NLP, agentic AI, RAG, Responsible AI, deploying models — was taught through the lens of: what does a PM actually need to know here, and what decision does this inform? Her FAANG experience shows in every example.
The breakout sessions were genuinely one of the best parts. Working through cases like TalentMatcher bias analysis and the EduLearn LLM architecture in real time with the cohort made the frameworks stick in a way that lectures alone never could.
If you are serious about AI PM and want proof of work — not just a certificate — take this course.
EK
Eric K.
Great course to learn Agentic AI development!
If you are a PM who wants to learn agentic AI development, this is the course for you. She efficiently covers the information you need to learn to get going on Agentic AI product definition and development, and the assignments give you practice in concrete AI development. If you pay attention and do the work you'll be an Agentic AI Product Builder by the end of this course.
RS
R S.
Jyothi’s enthusiasm + Hands on experience of building agentic workflows
Jyothi’s enthusiasm, combined with the hands-on experience gained through assignments that focus on building real-world products, is one of the standout aspects of this course.
SK
SIMRAN KAUR S.
I recently completed Jyothi’s AI PM…
I recently completed Jyothi’s AI PM course and had a very positive experience. The course was engaging, well-structured, and full of practical insights that helped build a strong understanding of core AI concepts. What I appreciated most was Jyothi’s ability to explain complex ideas in a simple and relatable way, making the sessions easy to follow and genuinely enjoyable. Overall, it was a highly valuable learning experience that I would definitely recommend.
MJ
Mathew J.
Completing the NextGen's Agentic AI Product Manager…
Completing the NextGen's Agentic AI Product Manager Cohort has been a transformative milestone in my AI product leadership journey. The program delivered a rigorous, future‑focused curriculum that pushed me to think beyond traditional product frameworks and into the emerging world of agentic, autonomous AI systems.
The coursework went far deeper than surface‑level AI concepts. It provided a comprehensive, hands‑on understanding of the technologies and strategies shaping next‑generation AI products:
Agent Architecture — Designing autonomous, multi‑step AI agents capable of reasoning, planning, and acting.
1. Context Engineering — Structuring and optimizing context windows for reliable agent behavior.
2. Retrieval‑Augmented Generation (RAG) — Building knowledge‑grounded systems with scalable retrieval pipelines.
3.Evaluations & Guardrails — Implementing safety, reliability, and performance frameworks for production‑grade AI.
4.AI Product Strategy — Translating technical capabilities into business value and defensible product roadmaps.
5. MCP Client–Server Architecture — Understanding modular, interoperable agent ecosystems.
6. Many practical hands-on lab exercises and breakout sessions have helped me to understand all the concepts and Agentic AI workflows.
On top of that my team's capstone project was selected as the Cohort Winner, a recognition I’m especially proud of. Thanks to Jyothi's mentoring and our dedicated team for their outstanding collaboration.
We built a Proactive AI Voice Agent for Travel Disruption Management, designed to autonomously assist travelers during airline, hotel, and rental car disruptions.
This program didn’t just expand my knowledge—it reshaped how I approach AI product development. I now think in terms of autonomous workflows, context‑aware systems, and AI‑driven decision loops, all grounded in responsible design and measurable outcomes.
I would encourage anyone who is new to agentic AI or wants to transition their role to an Agentic AI PM. This course will definitely stand out and enhance your resume, giving more weight to your earned skills. So go for it.