From scratch to production in three months: the AI-first delivery model
summary
A team rebuilds Travelopia’s lead‑scoring platform in 111 days, shipping 6 lambdas, 3 microservices and a frontend and running at 5,000 leads/month. Work centers on repo‑native PRDs, human‑owned architecture, doc‑indexed prompts and few‑shot coding; tests are generated separately and reviewed by humans. Daily flow uses mob planning, granular task splitting and detailed git commits that auto‑produce stakeholder reports. Guardrails (ESLint, unit tests, observability) keep LLM outputs bounded and reduce unallocated leads from about 40–50 per day to zero.
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chapters (11)
- 0:00AI-first delivery model
- 3:53Project background
- 7:38SDLC challenges with AI
- 14:09Redesigning SDLC for AI
- 20:11Daily workflow
- 23:17Key takeaways
- 26:28Q&A on C4 and PRD
- 28:34LLM limits with TDD
- 30:16AI line-by-line coding
- 32:43Code review priorities
- 34:51Monte Carlo on Git history
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