Skipping evals is a short-term saving and a long-term tax
Teams skip evals because evals look expensive. Annotation is slow. Judge calls cost money. Building a dataset feels like overhead before "real" work. The actual cost equation is the opposite — every shipping cycle without evals creates compounding debt.
What untested LLM systems cost
- Silent regressions. A prompt edit on Tuesday breaks a 4% user segment; you find out on Thursday from a support ticket. Customer-facing damage already done.
- Model migrations stall. When a new model release lands, you cannot upgrade because nobody knows which behaviors will break. The only safe move is "stay on the old version forever."
- Vendor lock-in. No evals means no portable evidence of quality. Switching providers is a rebuild, not a swap.
- Stakeholder distrust. When asked "did this change help?" you say "users seem happy" and watch your influence shrink.
- On-call burnout. Production incidents you cannot reproduce, debug, or prevent. Engineers leave teams that ship from vibes.
- Slow improvement. Without evals you cannot tell which prompt change worked, so iteration becomes guess-and-revert.
Principle: Evals are not insurance. They are the only mechanism that converts "we made a change" into "we know what the change did." Without them you do not have a system; you have a fog.
The cost flip
Once evals exist, every cost in the list above flips. Regressions are caught at PR time. Model upgrades become routine. Vendor switches become benchmarks. Stakeholders see numbers. On-call calms down. Iteration accelerates. The eval suite — the thing that looked like overhead — is the thing that lets the team move fast.