Build a Basic AI Agent from Scratch: Long Task Planning

6 days ago

The agent previously built with tools for file operations, bash commands, and web content now struggles with long-term tasks due to its conversational LLM nature, requiring enhancements for sustained autonomous work.
To enable long task planning, two new tools were introduced: a Scratchpad for in-memory thought storage and a To-do List for task decomposition and tracking, both implemented in Python to enforce structured planning and progress monitoring.
The system prompt was updated to instruct the agent on using these tools for planning, including steps like goal restatement, option evaluation, failure anticipation, and verification before task completion, ensuring robust handling of complex tasks.
Testing demonstrated the agent's ability to migrate a static site from Eleventy to Hugo by planning steps, executing actions, and verifying success, highlighting its improved capacity for long, multi-step tasks with error recovery and replanning capabilities.

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