# Designing Agents (The Floor Is the Frontier) — Ben Hylak, Raindrop

Source: [AI Engineer](https://www.youtube.com/watch?v=jHMiYtjoJfA)  
Feed7 permalink: https://feed7.dev/p/designing-agents-the-floor-is-the-frontier-ben-hylak-raindrop-0uoems4  
Published: 2026-08-12T18:00:34.000Z  
Trust: Source Linked (source_linked)

## Why Included

Agent evals tied to a model, tool call, or harness can decay after an upgrade. Keep checks in code, prioritize production failures by onset and reach, and use agents to investigate detected anomalies.

## Source Summary

Hylak says a harness switch made **80% of one eval suite** unhelpful. He recommends running **local, code-based agent tests** instead of relying on prompt playgrounds or large suites coupled to current tool behavior.

## Practical Implication

Treat production evidence as the durable layer. For each failure class, track **when it began** and **the share of users affected**, then use those signals to decide what deserves a regression test or rollback investigation.

## Agent-Ready Context

Hylak says a harness switch made **80% of one eval suite** unhelpful. He recommends running **local, code-based agent tests** instead of relying on prompt playgrounds or large suites coupled to current tool behavior.

Treat production evidence as the durable layer. For each failure class, track **when it began** and **the share of users affected**, then use those signals to decide what deserves a regression test or rollback investigation.

Agents are weak anomaly detectors, and free-form clustering can blur distinct root causes. Detect measurable shifts such as keyword-frequency spikes first, then ask an agent to investigate them.

## Connected Context

Feed7 judgment across 462 accumulated Signals:

This makes production failures and measurable shifts the durable basis of agent evaluation, while treating harness-coupled suites as disposable. It sharpens the prior trace-and-simulation loop: detect anomalies with explicit metrics, preserve onset and affected-user scope, then promote verified failure classes into small local regression tests rather than asking agents to discover structure through free-form clustering.

- [Improving Agents is a Data Mining Problem — Vivek Trivedy, LangChain](https://feed7.dev/p/improving-agents-is-a-data-mining-problem-vivek-trivedy-langchain-1cgibr8) — Both place production traces before eval construction, but this Signal adds measurable shift detection and affected-user scope to reduce misleading agent-led clustering.
- [From Agent Traces to Agent Simulations — Rustem Feyzkhanov, Snorkel AI](https://feed7.dev/p/from-agent-traces-to-agent-simulations-rustem-feyzkhanov-snorkel-ai-0zwlzjq) — Replayable production environments provide the fixed conditions needed to turn discovered failure classes into durable regression gates across harness changes.
- [SimulationMaxxing: How we ship agents 20× faster — Aman Gupta (Nubank) + Shreya Rajpal (Snowglobe)](https://feed7.dev/p/simulationmaxxing-how-we-ship-agents-20-faster-aman-gupta-nubank-shreya-0r3nm6u) — Simulation can move evaluation earlier, while this Signal supplies the production onset and impact evidence needed to decide which simulated regressions are worth maintaining.
- [Everything Is a Rollout — Alex Shaw + Ryan Marten, Terminal-Bench, Harbor, Laude Institute](https://feed7.dev/p/everything-is-a-rollout-alex-shaw-ryan-marten-terminal-bench-harbor-laud-0iz4rgx) — Reproducible sandbox rollouts reinforce local code-based testing; the reported suite invalidation explains why every harness change itself must be evaluated.

## Context Map

- Layer: benchmark
- Domains: coding
- Topics: agent-evals, agent-reliability, harness-engineering

## Uncertainty

- Agents are weak anomaly detectors, and free-form clustering can blur distinct root causes. Detect measurable shifts such as keyword-frequency spikes first, then ask an agent to investigate them.

## Agent Instruction

Use this item as source-backed context. Do not invent claims beyond the linked source. If this item conflicts with another source, call out the conflict.