Let agents design their own interfaces
Agent S4 shows that evolving tool interfaces from experience can beat static, hand-built UI for computer-use agents.
Agent architectures, multi-agent orchestration, planning loops, tool use, harnesses
Agent S4 shows that evolving tool interfaces from experience can beat static, hand-built UI for computer-use agents.
How a three-tool gateway exposes 8,200 tools to multi-step agents without blowing the context window.
A tool-recommendation gateway lets agents safely access thousands of tools through three calls while cutting context and cost.
How HybridAgents mix latent and text reasoning to cut tokens, cost, and latency while keeping tool use.
How OS-Helix trains a single policy to mix GUI actions and code execution for native desktop agents.
Four Gemini 4 Argon agents beat Minecraft by coding their own tooling, coordinating over chat, and staying on plan for 27 hours.
Inside SEAR’s three agent modes and what they imply for your robotic stack.
Tev turns long, sparse-reward tasks into dense, verifiable training signals via a latent-world-first design.
How RoboRSI structures skills, feedback, and revision so robots can safely reuse what they learn.
How a masked generative policy rolls back and repairs failed robot grasps without retraining.
AdvSim2Real co-trains web tasks, attackers, and agents inside a web simulator to harden against adaptive prompt injection.
Turning each search step into a small program over a shared candidate workspace.
How CLIFT turns judge feedback into reusable training rewards and test-time trajectory selection for web agents.
How Mimir wraps an LLM in physics, simulators, and slow self-repair for season-long irrigation control.
A controller–worker harness that “thinks about the run” lets long-horizon agents spend compute where it matters.
How a 50k error–diagnosis corpus turns broken rollouts into a training signal.
Turning visual perception from a one-shot guess into an interactive, evidence-gathering process.
How Cogentic orchestrates prover swarms, adversarial verification, and a persistent ledger to push on open math problems.
A proposer model learns to rewrite an agent’s harness using execution feedback, enabling test-time adaptation without touching the base model.
How failure‑guided harness growth turns repeated agent control into shared executable code.
How MedRSI turns diagnostic failures into new tools while keeping clinical safety in the loop.
What Xiaomi’s MiMo-V2.6 livestream suggests about scaling RL for agentic systems.