Simple beats complex: A three-step approach outperforms autonomous coding agents.
Agentless proposes a simpler, more effective approach to automated software development by removing complex autonomous agents and using a straightforward three-phase process.
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https://arxiv.org/abs/2407.01489
🤖 Original Problem:
→ Current LLM-based software development relies heavily on complex autonomous agents that use multiple tools and make decisions independently
→ These agents often struggle with tool usage, decision planning, and self-reflection, leading to inefficient and costly solutions
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🔧 Solution in this Paper:
→ Agentless introduces a three-phase process: localization, repair, and patch validation
→ The localization phase uses hierarchical steps to identify edit locations, starting from files down to specific code segments
→ The repair phase generates multiple patch candidates using a simple diff format
→ The validation phase uses both regression tests and generated reproduction tests to verify fixes
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💡 Key Insights:
→ Complex autonomous agents may not be necessary for effective automated software development
→ A simple, structured approach can achieve superior results while maintaining cost efficiency
→ Test generation and validation are crucial for effective patch selection
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📊 Results:
→ Achieved 32% success rate (96 correct fixes) on SWE-bench Lite benchmark
→ Maintained low cost ($0.70 per fix) compared to agent-based approaches
→ Already adopted by OpenAI as their go-to approach for GPT-4o and o1 models
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