Knowledge Work SDK
A Python SDK for building AI agents that perform knowledge work—research, analysis, writing, and decision-making tasks that require iteration, verification, and structured thinking.
Why Knowledge Work is Different from Code
Code has a tight feedback loop: write code → run tests → fix errors → repeat. The solution space is constrained—there's usually one correct answer, and automated tests tell you if you found it.
Knowledge work is fundamentally different. The solution space is vast and underspecified. A "market analysis" could be a two-paragraph summary or a 50-page deep dive. A "strategy recommendation" could emphasize cost, speed, risk, innovation, or any combination. There's no test suite that returns pass/fail.
Our approach: Since knowledge work lacks natural verification, we synthesize one using rubrics. A rubric defines what "good" looks like before execution begins, enabling:
Self-verification : The agent checks its own work against explicit criteria
: The agent checks its own work against explicit criteria Iterative refinement : Failed verification triggers targeted improvement
: Failed verification triggers targeted improvement Transparent evaluation: Humans can audit the rubric and verification process
This SDK implements a self-verifying agentic loop that brings structure to the inherently open-ended nature of knowledge work. The agent can search the web, read and write files, execute code, generate artifacts, and ask the user for clarification—all coordinated through an orchestrator that verifies its own output.
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