OpenAgents Episode 157: Chains of Thought and Action

We define a chain of thought and action (CoTA) as a series of reasoning steps and tool use whereby agentic AI systems show both the intermediate reasoning and the inputs and outputs of actions taken.

We plan a "GitHub issue solver" agent we'll build over the next few videos to show CoTA in action. A possible algorithm:

- Given a GitHub issue, build a repo map from issue (via automated script)

- Identify relevant files (via DeepSeek R1 for reasoning, Mistral Small(?) for structured output)

- Traverse and analyze codebase (file readers, AST parsers)

- Plan changes (DeepSeek R1)

- Generate and test code changes (CI/scripts)

- Create pull request with detailed explanation (GitHub API)

When this agent works well with full transparency, why would you ever use a closed-source alternative?

If you expect your models to show the full CoT, you'd better expect your agents to show the full CoTA!