What verification patterns are you using for agents that call tools or automate browsers?

If your agent writes code, calls tools, or does browser actions, you know what the problems can be: hallucinations, yes. I have been testing a few things: add a verification loop so the agent has to produce checkable outputs and pass a separate validator before any real action is allowed. Here's the core idea: Separate actor and verifier. The verifier is just deterministic code with no LLM and no creativity. Its job is to determine whether this output is valid based on clear rules. Force structured outputs. Anything that triggers tools or side effects should come out as JSON with checkable fields and IDs, not free-form text. That makes validation and retries much easier. Evidence and caps. Store one evidence artifact per side effect, for example, a log entry, an ID, or a snapshot. Cap tool calls, cost, and runtime in the runner so a misbehaving agent cannot go wild. In practice, this prevents agents from confidently saying "done" when nothing actually changed and makes debugging less painful. I also wrote up a 30-minute implementation guide with concrete patterns and examples. Wanted to check how you people are handling this: Do you already run some kind of verification layer for your agents? What is the riskiest agent you are running right now, for example, browser automation, RAG pipelines, codegen, or something else?