Watch AI build on a real product — and get it wrong, live.

What happened

The session opened with the honest map: the cost of a first version has collapsed from months in 2019 to a weekend today, and tools like Lovable, v0, and Replit put prototyping in anyone's hands. The moat isn't the prototype anymore — it's making it production-ready, scalable, and secure.

Then the live part: a real internal product's codebase turned into something you can query in plain English, and a change request worked through an agentic pipeline — clickable dashboard filters plus a Clear Filters button — with test-driven development and human "Yellow Gates" at every decision point. The AI delivered. It also chose GET parameters for filtering where POST was the safe call — a security nuance no test flags, caught by a human and fed back into the org memory so it never happens again. That gap is the whole point.

Moments worth jumping to

• 09:42

  A codebase becomes conversational — the AI documents an internal project on request, in plain English.

• 14:31

  The Yellow Gates — the four points where a human must be in the loop: define, design review, business review, the final merge.

• 23:45

  Token economics — expensive models plan, cheaper models do the grunt coding. AI spend is now an engineering discipline.

• 38:53

  "AI is always confident — even when it's wrong." — why human re-checking isn't optional.

• 47:55

  The catch — AI used GET instead of POST for filtering. Technically correct, operationally risky — exactly what only judgment catches.

• 50:32

  The small-company advantage — why startups can adopt this faster than the giants.

What you'll take away

• Prototyping is genuinely yours now— and the business moat has moved to what comes after the prototype.
• Agents, not assistants— how AI teams execute whole tasks, and the pipeline (TDD, staged reviews) that keeps them honest.
• Org Memory— why AI makes better decisions when it holds your business context as well as your code, and how every human catch makes it smarter.
• Accountability stays human— in the CTO's words from the session:

  "Claude isn't responsible if there's a security breach; we are."

Full chapter list

• 00:00Introduction & the evolution of development
• 04:40Agentic AI & Org Memory
• 08:12Live demo — building with AI agents
• 14:31Human-in-the-loop & the stack agent workflow
• 25:01Security, accuracy & technical debt
• 44:01Demo results & final Q&A

Presented by Sanjay [surname, title] and Anoop [surname], CTO, Emvigo.