AI systems don't fail like software.
They fail like organisms.
They degrade at different context lengths, get confused without signaling it, and suffer from harness limitations that are hard to diagnose. As stacks shift across models, integrations, and edge cases, reliability becomes increasingly difficult to maintain.
We believe the next era of AI-native software requires an adaptation layer — infrastructure that makes diagnosis and self-improvement an expected part of the system's lifecycle.
Introspection is a forward-deployed AI agent that lives inside your system. It reasons over your code, telemetry, and user feedback to continuously improve reliability across the stack.
Introspection is an applied AI team building the product we wished we had while scaling out agents at xAI, Superhuman, and Predibase. Based in San Francisco.
If this sounds exciting, we'd love to hear from you.