9a9e58c935
Moved from maxwell/blog to standalone repository. - Next.js research journal application - Notes 001-005 with YAML/MD content structure - Claude Code configuration for blog development Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
49 lines
2.1 KiB
Markdown
49 lines
2.1 KiB
Markdown
## The Goal
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This note is about detailed planning and gut checking. Two questions:
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1. Can we get a detailed roadmap?
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2. Are we confident we can accomplish it?
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## Step 1: Hydrate the Planning Docs
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With research complete in `research/*`, apply it back to the planning documents:
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> Take all of the research in research/* and apply it to our *.md docs
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This updates `vision.md`, `architecture.md`, and `roadmap.md` with validated approaches, concrete numbers, and working code patterns.
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## Step 2: Expand Roadmap Steps
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Each step in the roadmap needs detailed implementation guidance. I used `/do-parallel` to expand all steps simultaneously:
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> /do-parallel for each step in roadmap.md, write it in steps/{name}.md. use the research in research/*
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This creates a detailed implementation guide for each step, incorporating the research findings. The `steps/` directory becomes a collection of actionable implementation documents.
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## Step 3: Confidence Check
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With the detailed roadmap and expanded steps, ask for a gut check:
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> Read through the roadmap and the steps, respond with a confidence score 1-100 of whether or not you think we will succeed, then list things that will make us more confident
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## Methodology: The Confidence Check
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There are many ways to do this confidence check:
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- **Ask for gaps** — What needs more specification?
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- **Ask for unknowns** — What needs more research?
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- **Ask for spikes** — Do we need smaller experiments to validate assumptions?
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- **Ask for risks** — What could go wrong?
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- **Ask for dependencies** — What are we waiting on?
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In this example, I kept it simple — just hunted for a confidence score and a list of things that would increase confidence. When the score came back high, I accepted it and moved on. This is risky. AI is often overconfident. A proper confidence check using the approaches above would surface more issues.
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## What I Did
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I ran the confidence check, got a high score, noted the suggestions for improvement, and moved on. The suggestions went into backlog items and future research topics.
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## Next Steps
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Start building.
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