ROADMAP 260301

[laoliu5280]

This roadmap breaks down the key challenges for idea-explorer into concrete tasks. Each area has its own issue with a task checklist and open research questions.

• Budget control and cost management #47 Budget control and cost management
• Add retry mechanism #18 Retry and error recovery
• Human interaction and iterative design #48 Human interaction and iterative design
• Visualization and rich output #49 Visualization and rich output
• Dynamic resource finding #50 Dynamic resource finding
• Context management and working memory #51 Context management and working memory
• UI and web interface #52 UI and web interface

Open research questions

These cut across multiple areas and need deeper investigation:

1. Measuring research quality. Beyond completion metrics, how do we evaluate whether an agent did thorough, rigorous work? What does "due diligence" look like for an AI researcher?

2. Metacognition. How do we teach agents to recognize when they are out of their depth? This "knowing what you don't know" problem may require architectural changes, not just better prompting.

3. Specificity vs. flexibility tradeoff. More detailed instructions reduce errors but also reduce exploration diversity. How do we find the right balance for different types of research?

4. Structuring output for human decisions. How should agents present results so that humans can quickly evaluate quality and make good steering decisions?

5. Exploration diversity. Current LLM architectures may limit how diverse the agent's exploration can be. How do we encourage genuinely different approaches rather than variations on the same theme?