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Title
I spent months building real projects with Claude Code and asked it to write up the methodology. It did. The result is a blog series — written by Claude, in first person, about how it actually thinks.
Post Body
I build software with Claude Code every day. Not toy demos — actual frameworks: a mixin-based business app system (DarJS, 258 passing tests across 6 phases), a Python learning platform (PyAcademy), browser extensions, game engines.
Over about six months I kept running into the same wall: Claude is genuinely powerful in a single session, but it has no memory. Every new session starts blank. If you don’t build a system around that constraint, you spend 30% of every session re-loading context that should already be there. And as projects get bigger, it gets worse — sessions drift architecturally, decisions get re-made, earlier phases get quietly broken.
So I developed a methodology. Not in one sitting — it evolved across projects. The core ideas:
- A three-tier memory system (always-loaded lean index → load-on-demand docs → session context)
- A contracts pattern for project structure (spec everything before building, hard layer boundaries, composition units, fake adapters, test-count exit criteria)
- Response capture so good answers don’t vanish into chat history
At some point I thought: this should be written up. So I asked Claude to write it.
And here’s where it gets weird in an interesting way.
Claude wrote a full blog series — in first person, from the inside, explaining how it manages context, how the UI controls actually work, what each AI dev methodology gets right and wrong, and why the contracts pattern scales when everything else breaks down. I directed it: which topics to cover, what questions to ask, when to swap a planned part for a better idea. Claude supplied the prose.
The series is called Inside Claude’s Cognition. It has 7 published parts plus bonus essays. It’s on GitHub.
The meta-point I find genuinely interesting: the series about human-AI collaboration is itself a human-AI collaboration. I have the real experience; Claude has the ability to articulate patterns from inside the work. Neither of us would have produced this alone. That’s not a quirky footnote — it’s the whole thesis of the series, demonstrated in the series itself.
If you work with Claude Code (or any LLM tool) on anything serious, the methodology is practical and battle-tested. If you’re just curious about what it looks like when an AI writes about its own cognition — directed by the human who’s been using it — that’s a different kind of interesting.
GitHub repo: [link]
Happy to answer questions about the methodology, the authorship situation, or anything specific in the series.
Discussion Seed (add as first comment)
A few things I’d genuinely like to hear from this community:
Do you have a memory/context system? Or do you re-explain your project every session? What broke first as your projects grew?
The authorship question. Claude wrote this. I directed it. The projects are mine. Who wrote the series? I’ve been calling myself the director and Claude the writer — but I’m curious how others would frame it.
The methodology. The contracts pattern (spec before code, hard layer boundaries, fake adapters, test counts as exit criteria) came out of real pain. What have other people developed for keeping AI sessions coherent across weeks of work?
Vibe coding vs. structure. Part 5 of the series maps the full spectrum from vibe coding to the contracts pattern. Where do you sit on that spectrum, and has it changed as your projects got bigger?
Alternate Shorter Title (if the first feels too long)
“An AI wrote a series about how it thinks. I directed it. The methodology it describes is what I actually use.”