Episode 5: How to Grow Safer AI
- Jerry Overton
- 6 hours ago
- 1 min read
Overview
In our final episode, we lay out a step-by-step path for building agent systems that are not just functional—but safe, auditable, and ready for deployment. This isn’t a research project. It’s a development plan.
We walk through the Inhibitor Application Sprint—a build process that guides teams from early design through launch. If you’re a CTO under pressure to adopt AI responsibly, this is your blueprint.
Key Takeaways
Phase-Based Integration: The Application Sprint includes five phases: define inhibitions, build reflective loops, activate the Inhibitor, stress test the agent, and launch with oversight.
Code + Ops: Developers can start with working code samples (examples/) and performance benchmarks (benchmarks/) to model safe behaviors and measure latency impacts.
Lifecycle Safety: Safety isn’t tacked on at the end. It’s embedded throughout the development cycle—so your system launches with ethical reasoning, not just clever outputs.
Operational Outcomes: The goal is not just to build something that works—but to build something you can trust, deploy, and scale under legal, reputational, and technical pressure.
Note: All voices in this podcast are AI-generated. No human actors were used.
🔗 Explore the Tech: Inhibitor Lab on GitHub