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YYLO
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YYLO provides a structured harness for managing autonomous AI agent work loops, leveraging Git for task truth, isolated worktrees for safe execution, and durable provenance receipts.
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Overview
YYLO is a developer framework and execution system designed to control AI agent work loops by anchoring task dependencies and session provenance directly within Git.
Key Features
Task truth and dependency management tracked directly in Git
Bounded delegation across multiple agent instances and foundation models
Isolated Git worktree execution with recorded session provenance
Validation, review, and merging backed by durable execution receipts
Comparative agent attempt analysis with retained benchmark evidence
Use Cases & Problems Solved
Use Cases
- •Orchestrating multi-agent coding and debugging workflows in isolated worktrees
- •Benchmarking different LLM models and agent prompts against identical tasks
- •Automating safe, verifiable code reviews and merges with complete session history
Who It's For
AI EngineersSoftware DevelopersAutonomous Agent Architects
Fit Analysis
Best For
Engineering teams deploying autonomous agents that need strict sandboxing and auditability. Developers looking for Git-native orchestration to manage multi-model tasks
Not Ideal For
Non-technical teams seeking no-code automation or prompt-chaining UIs. Basic single-turn chatbot interactions without code or repository context
FAQ
Metrics
Discovered9/1/2026
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Saved By0 users