We have all been there. You run the agent in the playground. It works. You give it a complex task: “Refactor the auth service.” It generates pristine code. You merge it.
Ten minutes later, PagerDuty is screaming.
The agent imported a library that doesn’t exist. Or worse, it refactored a function that looked unused but was actually called dynamically by a legacy cron job.
Welcome to 2026. The “Works on My Machine” meme is dead. Long live “Works on My Prompt.”
The Determinism Gap
The core problem is not that your agent is stupid. It is that your environment is static, but your agent is probabilistic.
In 2024, we thought the solution was “better evals.” If we just ran enough benchmarks, we could trust the model.
We were wrong.
Evals test reasoning. They do not test reality. An agent can reason perfectly about how to write a SQL query, but if the database schema changed five minutes ago, that query will fail.
You cannot prompt-engineer your way out of a runtime error.
Optimizing for MTTR (Not Accuracy)
The most successful “Agentic Reliability Engineers” I know have stopped trying to achieve 100% success rates. It is a fool’s errand. Even human engineers break production.
Instead, they optimize for Mean Time to Recovery (MTTR).
If an agent breaks something, how long does it take to know? And how long does it take to fix?
If the answer is “I have to git revert and wait for CI,” you are already dead. Agentic loops are too fast for human-speed recovery.
The Debugger for 2026
To debug an autonomous agent, you don’t need a step-through debugger. You need a Time Machine.
You need to see exactly what the agent saw at the moment of execution.
- The Context: What was the file state?
- The Action: What did it try to execute?
- The Result: What was the
stderr?
This is why we built the PrevHQ Sandbox.
It is not just a staging environment. It is a forensic record of every agent action. When an agent fails, we don’t just show you the error log. We give you a live URL of the environment as it existed when the error occurred.
You can click “Connect,” open a terminal, and poke around the corpse of the failed task.
Stop Trusting. Start verifying.
The “Agentic Reliability” mindset is simple: Containment over Correction.
Don’t ask “Will this agent make a mistake?” Ask “When this agent makes a mistake, will it take down the company?”
If you are building autonomous agents without a sandbox, you aren’t building software. You’re building a bomb.
FAQ
Q: How is debugging an agent different from debugging normal code? A: With normal code, you look for the logic error in the code. With agents, the error might be in the decision. You need to debug the state that led to that decision.
Q: Can’t I just use Docker containers locally? A: You can, but “locally” doesn’t scale to 1,000 concurrent agents. You need an ephemeral infrastructure that spins up and tears down in seconds, not minutes.
Q: What is the best metric for agent reliability? A: MTTR (Mean Time to Recovery). Accuracy is a vanity metric. Recovery speed is a survival metric.
Q: Does PrevHQ support custom runtimes? A: Yes. If it runs in Docker, it runs in PrevHQ. We support Node, Python, Go, Rust, and anything else you can containerize.