Kinesthetic

Kinesthetic is a platform designed to provide infrastructure and tooling for building specialized AI agents that can learn to improve themselves. It addresses the challenge of managing agent knowledge and behavior at scale, offering a knowledge layer that separates human-authored ground-truth from derived artifacts and allows for auditable, version-controlled specifications. The system is structured around an agent pipeline that incorporates user input, session context, an agent harness, output, and a robust mechanism for annotations and evaluations, all of which are governed by the Kinesthetic Knowledge Layer.

Key features include a Spec IDE, which serves as a collaborative workspace for teams, enabling users to see and modify exactly what instructions are given to models. The platform allows agents to propose changes based on failure reports or new feature requests, with all modifications staged and reviewed through a pull request workflow that requires human approval before deployment. The knowledge engine leverages a variety of data formats and supports the use of the latest research methods as a service. The knowledge base is designed to be scalable, with no token limits or context window hazards, and treats agent knowledge as a versionable, living asset that persists beyond individual model or harness lifecycles.

Kinesthetic emphasizes auditability and transparency, allowing users to trace precisely how AI agents behave in any scenario and to retrieve the artifacts that govern those behaviors in plain language. The platform supports feeding corrections, annotated traces, or feature specifications directly into the system, where a specialized agent transforms them into safe edits. Automated consistency checks, trace replays, and regression simulations are integrated into the review process to flag conflicting rules, coverage gaps, and ambiguities before changes are merged. Every change is tracked with a full history, and nothing is deployed without explicit human sign-off, ensuring both agent and specification quality.

The platform is designed for teams developing specialized AI agents who require scalable, auditable, and collaborative tooling to manage complex agent behaviors and knowledge assets.