π You're viewing someone's saved eval plan β run your own.
Vibe Drop Β· interactive gift
Build your eval stack before your agent's failures get load-bearing.
Only ~52% of teams run offline evals. The gap between observability and judgment is where production agents die.
Built on "AI Agent Evaluation & Quality Measurement" β part 8 of the "AI Agent Systems in Production" series on aicry (anonymously authored; attributed to the publication). Figures are from the piece.
Feel it: the pass^k drop
pass@k is what demos report. pass^k is what users experience. Drag your single-run success rate and watch eight perfect runs evaporate.
Probability all 8 runs succeed
5.8%
"Every demo implicitly uses pass@k: run until success, present that run. Investors and prospects see the winner."
Production target for mission-critical flows: pass^8 β₯ 80%. Ο-bench: GPT-4o-class agents under 50% pass@1 on retail tasks, falling below 25% at pass^8.
The three-layer pyramid
Run all three simultaneously β each misses at least two failure categories alone. Tap a layer.
Layer 1 Β· Unit-Step
Why did it fail?
Isolated decisions: right tool? valid params? correct interpretation? Graders are code-based β string matching, schema validation, API response checks, tool-call argument validation. Fast, objective, brittle.
Layer 2 Β· Trajectory
Where in the chain did it fail?
Full sequence of reasoning steps, tool calls, states, retries. Graders: LLM-as-judge per step, expected-tool-sequence matching, step-efficiency checks. Coherence target >0.85 on traces with 4+ steps. Not optional β catches corrupt success (27β78% of benchmark "successes" bypass required steps or use unauthorized tools).
Layer 3 Β· End-to-End
Did it fail at all?
Black-box input β success. Graders: code-based output verification (DB state, API responses), model-based rubrics, human review. What leadership sees β and what hides everything underneath.
Plan it: your rollout
Two inputs β your week-by-week eval-stack build-out. Check items off as you ship them.
CI gate (from the blueprint): average score β₯ 0.85 and pass^8 β₯ 0.80 for mission-critical flows. Production: sample 5% of queries daily, alert on 2Ο deviation from the rolling baseline.
The eight blind spots
Ranked by frequency/severity. Tap one.
Select a blind spot to see what it is.
Share this eval plan
Replay link β anyone who opens it sees your inputs and rollout plan.