The latest articles on DEV Community by SafeRun (@saferunai). https://dev.to/saferunai https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3931836%2F6157d97e-3311-4f08-af60-43cb7b5faade.jpg https://dev.to/saferunai en SafeRun Thu, 14 May 2026 19:04:01 +0000 https://dev.to/saferunai/whats-the-worst-thing-your-ai-agent-has-done-in-production-6no https://dev.to/saferunai/whats-the-worst-thing-your-ai-agent-has-done-in-production-6no <h1> What's the worst thing your AI agent has done in production? </h1> <p>I'm building reliability infrastructure for AI agents, and I'm collecting failure stories from engineers who've shipped agents to production.</p> <p>If you've shipped an AI agent and watched it do something nobody could explain — this post is for you.</p> <h2> Why I'm asking </h2> <p>For the past few weeks I've been talking to engineers running AI agents in production. The same pattern keeps showing up.</p> <p>Their agent did something they couldn't predict. The damage was already done by the time they noticed. The tools they had only logged the failure after the fact.</p> <p>One engineer told me he spent a whole weekend rerunning an agent trying to reproduce one failure.</p> <p>Another watched his sales agent email the same lead twelve times in five minutes before anyone caught it.</p> <p>A third issued a $4,500 refund because the customer asked nicely and the agent didn't think to check.</p> <p>These aren't edge cases. This is what production AI agents do when they're given real tools and real money — and the current generation of observability tools tell you about it <em>after</em> the fact.</p> <p>I'm building <strong>SafeRun</strong> to close that gap.</p> <h2> What SafeRun does </h2> <p>SafeRun sits inline between AI agents and the tools they call.</p> <ul> <li> <strong>Validates</strong> every tool call against your policies before execution</li> <li> <strong>Blocks</strong> unsafe operations and runaway loops in real time</li> <li> <strong>Escalates</strong> ambiguous actions to a human approval queue</li> <li> <strong>Replays</strong> every agent decision frame by frame when something goes wrong</li> </ul> <p>The killer feature, based on what engineers keep telling me, is Replay. Step through every input, model reasoning step, tool argument, policy result, latency, and cost — for every decision the agent made. And rerun from any step with modified inputs.</p> <p>It's a flight recorder for AI agents.</p> <h2> What I'm asking for </h2> <p>Two things.</p> <p><strong>1. If you're shipping AI agents to production, join the waitlist.</strong> Early access is opening soon. We're onboarding the first batch of teams over the coming weeks.</p> <p>→ <a href="https://saferun.dev" rel="noopener noreferrer">saferun.dev</a></p> <p><strong>2. Tell me your worst agent failure story.</strong> Drop it in the comments below, or DM me. I'm collecting them — anonymized — to make sure SafeRun actually solves the real problems engineers have.</p> <p>The weirder, the better. Hallucinated tool args. Runaway loops. Unauthorized actions. Cost spirals. Customer-facing incidents you can't talk about publicly. All of it.</p> <p>The pattern across these stories is what shapes what gets built first.</p> <h2> What's coming </h2> <p>The early SDK ships as a Python decorator first, then TypeScript. Native integrations for LangGraph, OpenAI Agents SDK, Anthropic Claude Agent SDK, Vercel AI SDK, CrewAI, and Mastra. MCP-layer proxy for framework-agnostic coverage.</p> <p>If you want to be in the first batch, the waitlist is at <a href="https://saferun.dev" rel="noopener noreferrer">saferun.dev</a>.</p> <p>And if you've lived through an agent failure that still haunts you — please, tell me about it. I'd genuinely rather build the right thing than the impressive thing.</p> <p>— Tidiane<br> Founder, SafeRun<br> <a href="https://x.com/saferunai" rel="noopener noreferrer">x.com/saferunai</a></p> ai tutorial automation agents