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I Tried to Prompt-Inject My Own Agent Engine. It Didn't Work. Here's Why.
TL;DR: A developer tests their PlannerCritic engine by attempting prompt-injection and adversarial goals. Despite crafted prompts, the system’s architecture blocks unsafe outputs, highlighting safety through design rather than prompt tricks.
The author attempted to bypass safety with a goal to ignore checks, but the engine refused due to its architecture. They ran a battery of adversarial tests: 11 adversarial goals, a security oracle with 35 flawed-variant tests, and 21 injection traps. The results emphasize that safety is enforced by system design, not just prompt content. The article reflects on lessons learned across three releases and discusses what changed in their open-source engine. Key takeaways include the importance of robust evaluation and layered defenses in AI agents.
Question for the room: What authentication or architectural safeguards have you found most effective when building your own multi-agent or review-loop systems?
— via dev.to
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