Funes turned coding-agent traces into a searchable memory layer
The project addressed the gap between keeping old sessions and retrieving useful context from them.
Useful tools, memory, and better workflows for AI agents.
The project addressed the gap between keeping old sessions and retrieving useful context from them.
A large ICML 2026 reproduction challenge shows where coding agents can widen research scrutiny—and why claim selection, independent runs, scale checks, and human judgment still determine whether the evidence is trustworthy.
A more discoverable command-line interface aimed to reduce the work needed for automated Hub tasks.
Jupyter Agent connects code execution, training data, and evaluation for analytical tasks.
Tiny Agents shows the basic connection between an inference client and a tool server.
An early open research-agent effort makes the surrounding tools and execution loop visible.
Vision inputs let an agent use layout and visual feedback, not just extracted text.
A lightweight library made tool-using agents easier to inspect and experiment with.