Why I separated live discovery from the AI chat box

Description and use

Separating live discovery from the chat interface improves data freshness and error visibility, enabling users to choose the appropriate layer for each task.

Problem

General AI chat boxes mix routine drafting with live discovery tasks, leading to stale or incorrect information about current topics and open‑source projects.

Outcome

Separating live discovery from the chat box improves data freshness, reduces misidentification of projects, and makes failure modes visible, enabling more reliable research workflows.

Workflow

• 1. Use the workspace for everyday drafting and knowledge work.
• 2. Access Global Topic Radar to find current research-worthy topics with up‑to‑date evidence and sources.
• 3. Access Open‑Source AI Radar to compare active AI projects, view rankings, licenses, and repository links.
• 4. Run Topic Intelligence Skill to transform a Radar item into a structured content brief with research questions and verification flags.
• 5. Run AI Open Source Intelligence Skill to resolve project identity, examine licenses, build comparison matrices, and plan stacks under constraints.
• 6. Review the Skill outputs, verify must_verify items, and proceed with content creation.
• 7. Keep the final judgment and publishing decisions in the workspace.

Evidence

Both questions depend on live evidence. They also have different failure modes from ordinary drafting.

Source

The Radars are intentionally usable without signing in. A visitor can inspect the current data before deciding whether the workflow is useful.

Source