---
id: "framework-agentic-eval-loop"
type: "framework"
source_timestamps: ["00:06:48", "00:07:05"]
tags: ["quality-assurance", "workflow-design"]
related: ["concept-ai-reviewing-ai"]
steps: ["AI Agent generates initial draft or code.", "\"Secondary AI Agent audits the draft against specific evaluation sets (inconsistencies", "assumptions", "architecture).\"", "Primary Agent revises based on audit feedback (loop repeats until eval sets are passed).", "Human applies final review and finishing touches."]
sources: ["s35-compounding-gap"]
sourceVaultSlug: "s35-compounding-gap"
originDay: 35
---
# Agentic Evaluation Loop

## Framework: Agentic Evaluation Loop

A multi-step, automated quality assurance process where AI systems generate and **iteratively critique their own work** against predefined metrics before human intervention.

### The four steps

1. **Generate** — Primary AI agent generates the initial draft or code.
2. **Audit** — Secondary AI agent audits the draft against specific evaluation sets (inconsistencies, missed requirements, risky assumptions, bad architectural choices).
3. **Revise** — Primary agent revises based on audit feedback. **Loop repeats** until 5–8 evaluation sets pass.
4. **Polish** — Human applies final review and finishing touches.

### Why this is high-leverage
This is the operational core of [[concept-ai-reviewing-ai]] — turning human review from full-pipeline drudgery into a high-leverage triage function.

### How to deploy
See [[action-implement-ai-review-pipelines]].

### Today's reality
Evaluation-as-a-Service vendors (Scale AI, Honeycomb) already operationalize this pattern in production code-shipping workflows. The framework is not aspirational — it's a documentation of best-in-class practice.


## Related across days
- [[concept-meta-task-agent-split]]
- [[concept-ai-reviewing-ai]]
- [[framework-private-bench-suite]]
- [[framework-hex-eval]]
- [[concept-comprehension-gate]]