The definitive programme for professionals ready to lead, build, and ship AI-powered products in a world where autonomous agents are reshaping every industry. Master LLM-feature PRDs, RAG requirements, agentic workflow design, prompt engineering, AI evaluations, and Responsible AI governance — and walk away with 10 portfolio deliverables hiring managers actually open.
Most product courses teach Scrum once and call it done. Ours makes you ship 10 portfolio artefacts — PRDs for LLM features, agentic workflow specs, prompt libraries, ethics reviews, eval frameworks — the exact deliverables hiring managers across BFSI, healthcare, retail, enterprise SaaS, government, and logistics ask for on day one of the AI PO interview loop.
Modules 1–2 establish AI-first product thinking, Scrum for AI cycles, and stakeholder discovery enhanced by LLM-assisted personas and AI-facilitated workshops. Modules 3–4 build hypothesis-driven AI roadmaps with OKRs and agentic backlog automation. Modules 5–7 are the frontier — writing PRDs for LLM features, mastering prompt engineering, and designing autonomous agent workflows with MCP, CrewAI, and LangGraph. Modules 8–10 ship the final deliverable — AI UX, Responsible AI governance, and a complete evals + go-live framework.
Master AI UX design with Figma AI, v0.dev, and Lovable — confidence indicators, progressive disclosure, graceful failure, human override. Apply the four pillars of Responsible AI (Fairness / Accountability / Transparency / Explainability) and navigate GDPR, India’s DPDP Act, and the EU AI Act. Close with the most senior skill in the discipline — using AI to grade AI through eval frameworks for RAG and agentic workflows, MLOps handoff, shadow mode, gradual rollout, and the data flywheel that makes your product smarter post-launch.
Jump to any section on the left. Click a module to see topics, hands-on lab, and key technologies.
Not a shallow tour. You'll use every one of these in at least one graded exercise.
Three full-production projects, each threaded through the entire curriculum. By the capstone, you've built the whole stack around them.
Ingest learner events, build transformation layers, and publish executive and academic dashboards with AI-generated insight summaries.
Build secure ETL workflows for employee, payroll, and performance datasets with governed semantic models and decision-ready KPIs.
Create near real-time customer analytics with streaming events, automated anomaly flags, and AI-assisted executive reporting.
Pick a real partner data problem. Deploy a production data pipeline and an AI agent that explains metrics, detects risks, and accelerates business decisions.
Not a career trainer. A practitioner who still ships code.
Aarav started as a React engineer at an Indian unicorn before leading platform teams across three continents. He's shipped React + FastAPI products for a healthcare network with 80M users, trained NLP classifiers in production for a top-3 bank, and — most recently — deployed the first LangGraph agent into a Fortune-500 insurer's claims pipeline.
His cohorts get two things other programs don't give you: a real engineer who still ships code, and a curriculum rewritten every quarter to match what hiring managers actually ask about.
If the answer you need isn't here, book a 20-minute advisor call. No-slides, no-pitch — just your questions.
Book a 20-minute advisor call. We'll walk through the curriculum, match it to your current role, and show you two real capstones from cohort 022.
