Rushing an LLM feature to production? Borrow a pragmatic engineering mindset. Sparked by Armin Ronacher’s dev-first ethos (via Simon Willison’s note), here’s a concise checklist you can run in a day to harden your LLM app without stalling velocity.
1) Scope the job and set a budget
- Define the narrow task your model must do well; defer “nice-to-haves.”
- Pick latency and cost targets (e.g., <2s p95, <$0.02 per call).
- Pin a model/version for the sprint; revisit only if targets fail.
2) Start with simple guardrails
- Separate system prompt from user input; never concatenate tools or secrets into user-controlled text.
- Allowlist tool/function calls and arguments.
- Block obvious jailbreak strings and file/URL access unless explicitly required. See the OWASP LLM Top 10.
3) Create a tiny golden dataset
- Write 20–50 representative prompts with expected outputs.
- Include adversarial and edge cases (tricky inputs, missing data).
- Run them before each deploy; log pass/fail for regression tracking.
4) Observe everything (privately)
- Log prompts, parameters, outputs, and latencies with trace IDs.
- Mask PII at the edge; store redacted copies for analysis.
- Tag outcomes (solved, needs review, unsafe) to close the feedback loop.
5) Control cost and speed
- Cache deterministic calls; batch or stream where possible.
- Prefer structured outputs (JSON/function calls) to reduce retries.
- Cap tokens; use smaller models for routing and bigger ones on demand.
6) Plan graceful failure
- Set timeouts and bounded retries with exponential backoff.
- Provide fallbacks: heuristic rules, search, or human-in-the-loop.
- Show users transparent errors, not silent failures.
7) Production hygiene
- Feature flags, canary rollouts, and a visible kill switch.
- Rate limiting per user/API key; rotate keys and audit usage.
- Pin model versions; record prompts along with model+params hash.
8) Measure what matters this week
- Quality: task success rate on your golden set.
- Safety: jailbreak/blocked attempt counts and false positives.
- Ops: p95 latency, error rate, and cost per successful task.
Sources and further reading
Context that inspired this checklist: Simon Willison’s note referencing Armin Ronacher. For security guidance, see the OWASP Top 10 for LLM Applications.
Takeaway: Ship small, instrument early, and let a tiny golden dataset be your truth. You’ll move faster with fewer surprises.
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