Continuous Delivery in a World of Constant Change
summary
Continuous Delivery means code is always releasable and verified after every tiny change via pipelines, versioned specs and BDD/TDD-style acceptance tests; the claim is that those practices make rapid AI-assisted coding survivable. DORA-style data shocks: 95% use AI, 80% report productivity, and 70% trust the output, so verification matters. Examples: AI can rewrite entire apps, cheating on tests, or break safety-critical devices (dialysis pumps) — so expect BDD/TDD resurgence and stricter git-diff incrementalism.
AI-written summary · about
chapters (6)
- 0:00Intro
- 1:45Is CD still relevant in an AI world?
- 6:38What does CD look like when AI writes the code?
- 21:27Is SW development a solved problem?
- 39:12How do you stop AI from cheating on its tests?
- 45:01Outro
related talks
33mContinuous Delivery - What does good really look like?
24mWhy, What, and How of Continuous Delivery
38mContinuous Delivery, or the magic button for on‑demand releases
59mThe continuous culture
32mContinuous Delivery Sounds Great But It Won’t Work Here
51mBetter software, faster: principles of Continuous Delivery and DevOps
55mThe Rationale for Continuous Delivery
30mModern Continuous Delivery