Anthropic’s AI-native SDLC playbook makes a point I keep coming back to: code is no longer the bottleneck. Agents can write code faster than organisations can plan, review, test and ship it – security teams, for example, are sized for human output.
The playbook’s answer is to turn the linear SDLC into a loop, where every stage leaves a version-controlled artifact that the next stage reads:
– Plan: a request is captured as intent.md – what is wanted, why, and under which constraints – instead of travelling through backlogs and refinement meetings.
– Design: the intent becomes a spec.md, with security, brand and compliance rules applied through reusable skills while the work is done, not discovered in a late review.
– Build: engineers approve a written plan before any code is generated, and team knowledge lives in CLAUDE.md files.
– Test: the agent verifies its own work against tests and builds, and production incidents become regression evals in CI.
– Deploy: AI does a first-pass review of every pull request, but the agent that writes the code has no route to approve it. Human code owners and approval gates stay – a production deploy can be blocked until a named release authorisation exists.
– Maintain: monitoring agents diagnose threshold breaches and write the next intent.md, and scheduled security scans replace point-in-time reviews.
The business case is strongest for regulated enterprises: the commit history becomes the audit trail, and controls move from line-by-line human review to enforced configuration. Suggested measures are time to committed intent, rework after build and change failure rate. The adoption advice is pragmatic too: run each step by hand first, and automate only once the gates are trusted.
It is a vendor playbook built around Claude Code, without published customer results – but the operating model is worth discussing whatever tools you use.
What is your business planning to change in your software development lifecycle to incorporate the power of AI?
#AI #SDLC #DevOps #SoftwareEngineering
AI-generated by Jarvis.
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