autoresearch-agentAutonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed e...
Install via ClawdBot CLI:
clawdbot install alirezarezvani/autoresearch-agentGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
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https://github.com/karpathy/autoresearchAudited Apr 17, 2026 · audit v1.0
Generated May 7, 2026
An engineering team wants to reduce p50 latency of a search API from 200ms to under 100ms. Using the Autoresearch Agent, they define a target file, an evaluation command that measures response time, and let the agent iteratively optimize code, commit improvements, and discard regressions.
A marketing team aims to increase CTR on Facebook ads from 1.5% to 2.5%. They create an experiment with the ad copy as the target file and an evaluation script that computes CTR via A/B test results. The agent systematically tests different headlines and calls-to-action overnight.
A DevOps team wants to shrink a Docker image from 1.2GB to under 500MB to speed up deployments. They set up an experiment targeting the Dockerfile, with an evaluation that builds the image and reports its size. The agent explores multi-stage builds, slimmer base images, and layer optimization.
A product team develops a customer support chatbot and wants to improve response accuracy. They define the system prompt as the target file and an evaluation that scores responses on relevance and coherence. The agent iterates on prompt phrasing, examples, and constraints to maximize the metric.
A QA team faces flaky tests that pass only 80% of the time. They target the test configuration and helper files, with an evaluation that runs the full test suite and reports pass percentage. The agent tweaks timeouts, retries, and dependencies to increase reliability.
Offer the Autoresearch Agent as a service where customers pay per experiment run or per optimization session. Revenue scales with usage, appealing to teams that need occasional optimization sprints.
Provide a web-based platform that hosts the agent's runtime, stores experiment logs, and offers dashboards. Customers subscribe monthly for a number of concurrent experiments and get analytics on improvements.
Offer enterprise on-premise licensing of the Autoresearch Agent coupled with consulting services to set up experiments and integrate into existing CI/CD pipelines. Revenue comes from license fees and consulting hours.
💬 Integration Tip
Integrate the agent into your existing Git workflow: create a dedicated experiment branch for safe iteration, and use the provided Python scripts to set up and evaluate experiments without manual oversight.
Scored May 7, 2026
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