AI in SDLC at PyConf

[Anand S]

I was at a panel on AI in SDLC at PyConf. Here's the summary of my advice:

Process

• Make AI your entire SDLC loop. Record client calls, feed them to a coding agent to directly build & deploy the solution.
• Record your prompts, run post-mortems, and distill them into SKILLS.md files for reuse.

Prompting

• Ask AI to make output more reviewable. Don't waste time reviewing unclear output.
• Prefer directional feedback (feeling, emotion, intent) over implementational.
• Also give AI freedom to do things its way. Learn from that - you'll be surprised.

Learning

• Prefer interns / outsiders over experts. They don't slow the process with preconceptions and leverage AI better.
• Stop learning what I does well. Learn what AI fails at - using AI. Keep re-assessing these.

Adoption

• Developer using AI are still accountable for their code. (Agents might become accountable in the future.)
• Start with new projects: less competition, fewer preconceptions, lower risk.
• Start in domains where failure is OK, rather than making AI safe enough for high-risk domains.
• Create safe spaces where hallucinations don't matter and run experiments there to learn what AI can do.
• Plan for where AI'll be a year later. It's growing very rapidly.

The full details of the panel discussion are at Who Owns the Commit?