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The rise of async AI programming
The workflow that's changing how software gets built.
An AI agent takes a detailed problem description, writes code (primarily Typescript, Rust, and Python), adds tests, and commits the changes to a branch. Unit and integration tests that validate core functionality Type checking that catches interface mismatches Performance benchmarks that ensure code meets speed requirements Linting and formatting that enforce style guidelines Our agent, Loop, lets you describe the evaluation problem you're trying to solve and spends time in the background analyzing experiment results, identifying patterns in failed test cases, and suggesting improvements to prompts, datasets, and scorers.
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