Episode 4: AI You Can Trust
- Jerry Overton
- 6 hours ago
- 1 min read
Overview
Different use cases demand different kinds of trust. In this episode, we break down how the Inhibitor operates under real-world pressure—balancing performance with precision. Whether you’re building fast-moving agents or audit-focused systems, safety isn’t one-size-fits-all. The Inhibitor was built to flex.
We cover its two operating modes, show how it integrates into agent pipelines, and walk through hands-on tools you can use today to put real-time oversight into production.
Key Takeaways
Two Modes, One Engine:
Insight Mode delivers detailed reasoning and full explainability—ideal for audits, debugging, and compliance.
Performance Mode is built for speed—lightweight, fast, and perfect for real-time moderation or inline safety checks.
Integration Tools:The open-source notebooks include examples like the Adaptive Feedback Agent (real-time critique and adjustment) and the Real-Time Moderation Agent (low-latency decision flags).
Developer Resources:Everything needed to integrate is in the docs/ folder—including API references, system architecture, and configuration guides.
Design Philosophy:Safety isn’t an extra layer. It’s a mode of operation. The Inhibitor adapts to how your system thinks—and scales with how fast it moves.
Note: All voices in this podcast are AI-generated. No human actors were used.
🔗 Next: Episode 5 – How to Grow Safer AI
🔗 Explore the Tech: Inhibitor Lab on GitHub