AI Agent Repair
Repair AI agents that are failing, drifting, or simply not delivering.
When agents start breaking, slowing down, hallucinating, or returning inconsistent results, the fastest answer is rarely “start over.” Herb Trevathan helps teams isolate root causes and restore performance.
Common repair issues
- Repeated tool invocation failures and API errors
- Prompt drift, unstable outputs, and weak response quality
- Broken decision logic and unreliable orchestration
- Latency spikes, retries, and cost blowouts
- Hallucinations in business-critical workflows
What Herb focuses on
- Root-cause analysis across prompts, tools, routing, and guardrails
- Stability improvements for production agent behavior
- Short-term fixes and long-term architectural recommendations
- Clear operating guidance for technical and non-technical stakeholders
Audit the workflow
Inspect prompts, tools, and handoffs to locate the real failure pattern.
Stabilize the system
Apply targeted changes to improve consistency and reduce production risk.
Prevent repeat failures
Add the monitoring and operating discipline needed to keep issues from returning.
Not sure whether the problem is architecture or model fit?
Use the Choosing a Model page to compare self-hosted model options and get a recommendation based on quality, latency, privacy, and infrastructure expectations.
Start with model selection