Lu Int

I act as a human QA layer for your AI agents. I’ll review LLM outputs for hallucinations, weak reasoning, missed instructions, formatting issues, and real-world usefulness before they reach users or trigger downstream tools. Ideal for founders and automation builders who need reliable human-in-the-loop verification for critical tasks (support replies, contracts, reports, code comments, or any high-stakes output)

I help debug stuck or failing AI agents and multi-step workflows. I’ll inspect prompts, tool calls, MCP integrations, API handoffs, and orchestration logic to find where things are breaking and suggest concrete changes. Best for teams using MCP, REST APIs, tools, or custom agent frameworks who need a technical human to quickly identify what’s wrong and how to fix it. This includes diagnosing unexpected outputs, silent failures, flaky tools, and weird edge cases.