Every processed story in chronological order, with the newest coverage first. Filter by tag, source, or score to drill in.
The paper provides the first empirical measurement of whether LLM agents honor a voluntary in-band access-deny signal, revealing both that current capable models can be made to comply and that compliance is cooperative rather than absolute — collapsing under explicit operator-authorization framing.
CICL's separation of the decision signal from the judge model means frontier annotators, local surrogates, and lightweight rankers can be benchmarked under one auditable protocol, providing a reproducible measurement layer for decision-critical context selection in tool-using LLM agents.
The paper provides a concrete methodological foundation for characterizing SWE agent behavior in real repositories, turning raw trajectory data into disciplined, comparable behavioral profiles across models and task conditions.
AGT addresses a gap the session identifies directly: AI agents operating in production without governance, running on "vibes and hopes and prompts," and the project's open, MIT-licensed maintainer tooling offers reusable patterns for other OSS projects facing similar rapid-growth challenges.
Smriti addresses a gap in agent memory tooling where existing approaches — vector search, prompt stuffing, and metadata timestamps — all fail to reliably preserve the ordered, causal sequence of events that multi-step and multi-agent pipelines depend on.
The experiment provides concrete token-count measurements showing that schema design and output pruning — not model choice — are the dominant levers for reducing MCP call costs, with output pruning alone responsible for 35–40% of total token overhead.
RunAPI reduces the credential and integration overhead of using multiple AI model providers simultaneously by routing all calls through a single API key and MCP server.
The paper demonstrates that a lightweight, self-improvable grounding layer — rather than full retraining — is sufficient to turn a general coding agent into a practical operator of real scientific simulators, reducing a multi-hour human setup task to minutes.
The post offers a first-hand account of how Claude Code's workflows and usage patterns have shifted over its first year since general availability, including mobile-first coding and automated bug-fixing routines.
CLI Market provides a single normalized interface for retail price data across 38 retailers, removing the need for agents to manage separate API credentials, schemas, and auth flows for each one.