Shipping LLM features to production: guardrails that actually work

Demos are easy; production is brutal. Before any LLM feature ships to real users at ByteDots client sites, it passes the same four gates.

Evaluation harnesses before prompts

Prompt tweaks without evals are vibes-driven development. We build golden datasets from real (anonymised) interactions, score every change against them, and treat regressions like test failures.

Injection defence by design

Anything retrieved from user content is untrusted input. Structured outputs, privilege separation between retrieval and action layers, and allow-listed tools keep prompt injection from becoming remote code execution.

Cost circuit-breakers

Token budgets per session, per user and per tenant, enforced in the gateway — not the application code. One runaway retry loop should never become a five-figure invoice overnight.

Honest fallback UX

Confidence-aware routing sends low-certainty answers to humans instead of hallucinating politely. Users forgive “I’m not sure, let me get someone” — they screenshot confident nonsense.

Ship AI features your customers can trust, and your support team will thank you at Christmas.