A mere mortal types in natural language, dreaming of building the next big thing like a toddler stacking blocks, then hits a complexity wall and wails, “Too hard!”—knocking it all down.
Great systems are engineered with discipline. Set design constraints, run ablations, measure effect sizes, and trim scope until you can ship something reliable—then iterate.
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Turn the fluff into action:
intent.md goal: triage claims for investigation capacity: 2,000 alerts/day constraints: fpr≈1%, region stability≤0.03, p95≤120ms limits: not for eligibility determination; training only on synthetic
contracts.yaml
inputs: {amount: decimal, code: string, region: enum}
outputs: {score: float, at_op: bool}
thresholds: {op_threshold: 0.73}
slos: {latency_p95_ms: 120}
ingest → normalise → join → validate → package → deploy → evidence
↘ tests & gates ↗
gate.utility@op.min = 0.75 gate.stability.region.max_delta = 0.03 gate.latency.p95_ms = 120 gate.privacy.membership_advantage_max = 0.05
Start small and smart:
Keep it clean and clear:
docs/intent.md docs/master_doc.md schemas/schema.yaml pipelines/pipeline.yaml ci/gates.yaml evidence/readme.md
1. Goals & constraints 2. Architecture & module contracts 3. Data schemas & vocabularies 4. Pipelines & artifacts 5. Evidence gates & thresholds 6. Rollbacks & incidents 7. Security & privacy 8. Runbooks & on-call 9. Templates & glossary
Watch out for these traps:
Fix it with these moves:
Make changes prove their worth:
factor, delta@op, ci_low, ci_high, decision adapter_specialized, +0.021, +0.014, +0.028, keep quant_int8, -0.006, -0.011, -0.003, keep (speed↑) prune_10pct, -0.015, -0.024, -0.008, revert
Keep it real-world ready:
Your action plan, copy-paste ready:
promotion: - ensure gates PASS; sign evidence; update change-control rollback: - revert; verify OP; open incident; attach dashboards incident: - snapshot; mitigate; root cause; prevention actions
COMMENT ON TABLE prod.ai.claims IS 'Purpose: triage; OP fpr=1%; Evidence: manifest 2025.01.';
Scenario: A founder’s tale of turning chaos into wins.
A founder kept “just prompting it better” for weeks, resetting thrice. They switched to a one-page intent, locked OP/stability at 1% FPR and 0.03 delta, and wired gates. Two weeks later, they shipped with incidents down 40% and adoption up 25%—all because proof rode with the product in a simulated rollout as of September 2025!
Ship it right:
[ ] Intent → constraints → contracts [ ] Small-scale validation green [ ] Gates automated in CI [ ] Rollbacks rehearsed [ ] Dashboards export HTML/PDF [ ] Catalog comments reference evidence IDs
Yep—use it for intent, then translate to specs and gates before building—keep it structured!
Version the master doc; re-validate on a small scale; then merge and promote—stay flexible!
Require effect sizes at OP; no evidence, no merge—make it earn its spot!
Nah—it’s discipline. You speed up by cutting rework and surprises—smart, not slow!
Freeze OPs and segments per release; version changes; re-validate small—hold the line!
Turn that wall into a ramp: constraints, contracts, gates, and evidence. That’s how intent becomes software that survives the real world.
Avoid this mess:
Do it this way:
intent.md → master_doc.md → schema.yaml → pipeline.yaml → ci.yaml → dashboards.html
utility@op.min: 0.75 stability.region.max_delta: 0.03 latency.p95_ms: 120 privacy.membership_advantage_max: 0.05
Test smart:
Prove the changes:
factor, delta@op, ci_low, ci_high, decision adapter_specialized, +0.021, +0.014, +0.028, keep quant_int8, -0.006, -0.011, -0.003, keep (speed↑) prune_10pct, -0.015, -0.024, -0.008, revert
Stay on track:
ingest → normalise → join → validate → package → deploy → evidence
↘ tests & gates ↗
promotion: - gates PASS; sign evidence; update change-control rollback: - revert; verify OP; open incident; attach dashboards