Stop wasting time on manual trial-and-error loops. If you are tired of tweaking prompts and running tests manually, there is a better way to achieve compounding gains through automation.
The Science of Autonomous Iteration
Based on the principles popularized by Andrej Karpathy, Autoresearch operates on a simple equation: Constraint + Mechanical Metric + Autonomous Iteration = Compounding Gains. You don’t need AGI to see massive improvements in your workflows; you simply need a goal, a metric, and a loop that never quits.
By using the Autoresearch repository, you can automate the process of improving ML models, codebases, or even marketing content by following a strict scientific method. This approach moves you away from manual tinkering and toward a system where progress is logged, verified, and stacked.
How the Autoresearch Loop Operates
The core engine follows a relentless cycle to ensure every change is measured and verified. Instead of moving beyond simple prompting, this tool treats development as a series of experiments. Before the loop begins, the agent performs a setup phase to establish context, define goals, and run an initial baseline.
Architecture Rebuild: v2.1.0 Efficiency
The latest update to the project represents a massive leap in efficiency. The monolithic SKILL.md file, which previously consumed nearly 100K tokens per invocation, has been replaced with a thin routing architecture that uses small, self-contained command files.
| Metric | Monolithic (v2.0) | Modular (v2.1.0) |
|---|---|---|
| Token Usage | ~100K tokens per invocation | ~5-8K tokens per invocation |
| Structure | Single SKILL.md file | Thin routing + 12 command files |
| Efficiency | High overhead | 95% token reduction |
Safety and Defense-in-Depth Guardrails
When letting an agent modify your files, safety is paramount. Autoresearch implements several hooks to act as guardrails, ensuring the agent doesn’t accidentally leak secrets or destroy your environment.
| Hook | Function |
|---|---|
| scout-block | Blocks node_modules and .git from context bloat |
| privacy-block | Prevents reading of .env or SSH keys |
| dangerous-cmd-block | Blocks destructive commands like rm -rf |
Quick Start Guide
You can get up and running quickly by cloning the project from GitHub and using the guided installer for OpenCode.
git clone https://github.com/uditgoenka/autoresearch.git cd autoresearch ./scripts/install.sh --opencode --global
Ready to automate your development? Start building autonomous loops today and let the agent do the heavy lifting while you sleep.
