AgentSLA: Agent Outcome Verifier

Make coding agents not just finish, but truly succeed

Problem

When developers use AI coding agents, traces and logs show what the agent did but not whether it achieved the goal. A run can look clean yet miss key requirements, or 'finish' without actually completing the task. Finished and succeeded are not the same.

Solution

A lightweight service where users define success criteria in natural language (e.g., 'API returns 200 and data is written to DB'). After the agent finishes, it automatically runs configurable verification checks (HTTP requests, DB queries, file checks, CLI commands) and outputs a pass/fail report.

Users

Individual developers and small teams using coding agents like Claude Code, Cursor, Devin

MVP

YAML-based acceptance check definitions; webhook trigger after agent completion; CLI and simple web report; built-in checkers for HTTP, SQL, files, commands; detailed diff on failure

Revenue

Subscription per verification run (e.g., 1000/month) or one-time desktop license; team plan with private deployment

Why now

AI coding agents are widespread but result verification is still manual; indie developers can quickly build vertical verifiers without large model training