spike

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Use when the right approach is genuinely unknown and reality will teach faster than planning — a risky unvalidated assumption, an unfamiliar integration, "will this even work", "try something quick". The result is explicitly throwaway and does not ship.

AI & Automation 13 stars 2 forks Updated 3 days ago MIT

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# MasterMind — Prototype Tight feedback loops beat big plans when the path is unclear (`~/.mastermind/engineering/core/agent-loop.md`, `mindset.md` → design it twice). A spike buys knowledge cheaply — as long as you don't mistake it for the product. ## Method 1. **Name the question** — the ONE risky unknown this spike will answer ("can the Worker stream a >20 MB file?", "does this library handle X?"). If there's no question, you don't need a prototype. 2. **Build the smallest thing that answers it** — hard-code, skip error handling, skip tests, skip polish. Speed over quality; it's throwaway. 3. **Extract the learning** — what did reality teach? Write down the answer and any surprises. 4. **Throw it away and rebuild to standard** — the real version gets the full loop (design, rigor, tests, review). **Do not ship the spike.** ## Rules **Time-box: 5 build-and-run attempts, roughly 30 minutes** — one question needs a handful of tries, not a day; proportionality over ceremony. An *attempt* is one edit → run → observe cycle against the named question; count them out loud as you go, so the box is observable and not a vibe. Attempt 5 finished without an answer = the box is spent, whatever the clock says. **When it expires, stop — that's a result, not a failure.** Report: what you learned, what is still unknown, and one recommendation — *proceed* (answer is yes, build it properly) / *different approach* (this path is wrong, here's the next one) / *needs more investigati...

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Author
mehrad-dm
Repository
mehrad-dm/mastermind
Created
2 weeks ago
Last Updated
3 days ago
Language
Shell
License
MIT

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