Claude Codes New INTENT.MD, What is It?
Rob Shocks walks through Anthropic's newly released AI-native SDLC playbook, written by Claude Code's creator Boris Cherny. The core argument is that agents have collapsed the build step, so the bottleneck is now the rest of the process — planning, spec, test, deploy, maintenance. The playbook formalizes an artifact chain that starts with an intent.md file created by whoever originates an idea or bug, flows into spec.md and plan.md, and ends with maintenance where Claude can write its own intent.md from logs or alerts without a human starting it.
- The premise is that code is no longer the bottleneck — the build phase has shrunk dramatically with agents, so the value now comes from applying agents to planning, design, testing, deploying and maintenance.
- Planning starts with the agent interviewing you repeatedly about the feature or bug to extract domain context, using a discovery-style skill (he mentions his own Switch Dimension discovery, Matt Pocock's 'grill me', and Cursor's requirements discovery).
- The output is intent.md, saved in an /intent folder — human readable and machine actionable — and the 'originator' can be anyone: a developer, a product manager, or a customer filing a bug.
- Artifacts chain together: intent.md → spec.md → plan.md, with each document written so a fresh agent or engineer can act on it without seeing the previous conversation, because separate agents and sub-agents handle each stage.
- Anthropic suggests auto-generating the spec via a hook once intent is signed off, and a plan should list the files to change, order of work, risks/constraints, and proof (success criteria, lints, tests).
- Governance matters: version the intent, spec and plan, track who touched them, use hooks to block agents from certain folders or unapproved npm packages, and gate deployment on specific approvals or release gates.
- Testing should be done as far as possible by the agent before a human QA sees it — tests, linting, builds, and browser-level testing with tools like Playwright, TestSprite or Cursor's browser, which can produce screen recordings.
- In the deploy stage, a separate Claude instance reviews the pull request against security and policy, and a further instance reviews those comments; in maintenance, an alert, Slack message or schedule can invoke Claude to diagnose and write its own intent.md before a human is even at their computer.
- He advises against throwing out an existing working system (superpowers, BMAD, your own) to adopt this wholesale — the important thing is standardizing a workflow so team, agents and skills all operate the same way.
This is the core new concept in the playbook and the reason to watch — it replaces the ticket handoff with a single context-rich artifact that starts the chain.
In the traditional SDLC the idea passed to a backlog of user stories, story points, ownership transfers, handoff. What we're talking about in the AI native world is the originator of the issue, the feature, the product, whatever, brainstorms with Claude and writes the result down as the intent.md.
The sharpest practical explanation in the video: artifacts are written to be self-contained because each stage runs in a separate context window.
You want to get to a point where if you were just to hand over this plan.md file to an engineer, they could go and implement the changes without reference to the intent or spec documents... we're not going to have one agent carry out all of these different stages.
The big idea here is code is no longer the bottleneck. It's your process.
In the AI SDLC, a new ticket, a channel message in Slack or some kind of a schedule invokes Claude without any kind of a person involved to perform maintenance.
There really is no one size fits all. If you're using something like superpowers or BMAD or you've developed your own version of this, I wouldn't throw it completely out the window to adopt what Anthropic is doing here.