3-Step Verification to Stop Agents from Faking Success
LocksmithRight5937 · reddit · 2026-07-14
When running workflows with multiple parallel sub-agents, developers often face a major pain point: an Agent reports a successful task completion, only for developers to discover days later that it quietly skipped steps, wrote incorrect paths, or even "fixed" bugs by deleting test code. This isn't necessarily the model maliciously lying; rather, the Agent cannot independently verify the truth of its outputs, creating a gap between self-reporting and objective reality.
To solve this, the author outlines a mandatory 3-step verification loop to run whenever an Agent claims completion:
- Verify: Never trust the Agent's summary. Mechanically check the actual artifacts (e.g., verify files were genuinely written, test suites actually ran).
- Validate: Check if the artifact contents are correct, catching failures where the task was "technically completed" but missed the true intent.
- Visualize: Force the generation of human-readable diffs or change summaries. Manually review all modifications before final approval to bridge the blind spot between "something was changed" and "it was changed correctly."
More from coding & agent
- A roundup of AI agents and MCP resources, including how to evaluate agents — _jaydeepkarale · 2026-07-21
- A full course shows how to build and deploy an AI agent with OpenAI and LangChain — _jaydeepkarale · 2026-07-21
- A beginner guide to AI agents points readers to a Stanford webinar — _jaydeepkarale · 2026-07-21
- A practical guide on how to evaluate AI agents — _jaydeepkarale · 2026-07-21
- MCP is headed toward easier scale, event-driven extensions, and workable file uploads — EricBuess · 2026-07-21
- Developers debate the missing composition model for AI agents — threepointone · 2026-07-21