A self-evolving agent harness is the layer of prompts, memory, skills, tools, and control logic that lets an AI agent improve its own behavior over time. Proteus is an open-source, MIT-licensed research-preview framework that lets you plug in any agent harness, evolve it across episodes, and measure exactly what changed. Instead of chasing a single benchmark score, Proteus asks what a self-evolving harness actually does and whether an initial condition leaves a permanent mark. ...

A codex project documentation skill is a portable, SKILL.md-based capability that lets an AI coding agent plan work as traceable YAML contracts and record every execution step, so the reasoning behind a project survives as an auditable archive instead of vanishing into a chat log. Project Orrery implements exactly this: it turns high-level goals into executable, engineered workflows whose state lives in a .agent-work/ directory with plans/, reports/, and completed/ subdirectories. Because the skill is built on the open agent skills standard, the same skill works in Codex CLI, Claude Code, Cursor, and Gemini CLI. ...

An AI agent mocap animation pipeline can turn any locked-camera video into a clean, rigged Mixamo animation end-to-end — no motion-capture suits, no commercial subscription, and no manual keyframing. The open-source mixamo-llm-mocap project (204 stars, 44 forks) runs a 10-stage pipeline that recovers a 3D body mesh from video, converts the motion into a JSON action spec, retargets it onto any Mixamo character, and applies it in Blender — all driven by an AI agent that reads numbers instead of eyeballing frames. ...

HarnessEval-W is an agentified evaluation benchmark that brings the “harness” paradigm from the LLM ecosystem to world-model benchmarking. Instead of computing a fixed rubric over generated rollouts, it interprets each evaluation case, decomposes the question into measurable sub-questions, and spawns specialized sub-agents with tailored context and diagnostic tools. A parent agent then validates the gathered evidence and aggregates it into a final verdict, producing a transparent evidence tree with a complete reasoning chain for every single rollout. ...

A multi-agent dev workspace lets you run several AI coding workers in parallel on your own machine, and DevSpace Ultra is the open-source tool that makes it possible using nothing more than your existing ChatGPT subscription. It layers an elastic “Chat Swarm” control plane on top of the DevSpace local MCP workspace, so one ChatGPT account can power a pool of independent ChatGPT Classic worker conversations that scale up and down with your workload. This guide explains what DevSpace Ultra is, how the worker pool works, how to set it up, and the honest platform and cost trade-offs you need to know before adopting it. ...

GPU performance is the single biggest lever in modern AI infrastructure, and the fastest way to master it is to stop reading theory and start building. This guide gives you a hands-on playground path: set up profiling tooling, measure before you optimize, build the canonical matrix multiplication kernel, and learn how micro-optimizations compound into real training and inference cost savings. By the end, you will know exactly how to profile a GPU, where your time actually goes, and when to hand-write a kernel versus trust a vendor library. ...

The All-AI-Jailbreaks repository is a curated, actively maintained archive of 19 prompt-injection and jailbreak experiment files spanning at least nine major model families, including DeepSeek, Gemini, GLM, Grok, Kimi, Qwen, Sonnet, ChatGPT, and Antigravity. It is best understood not as a “how to jailbreak” list but as a structured red-teaming corpus that maps directly onto the OWASP Top 10 for LLM Applications, where prompt injection ranks as LLM01:2025 — the number-one vulnerability in the industry. This review explains what the archive contains, how its five research themes align with the OWASP taxonomy, and how it fits the broader 2026 AI-security ecosystem of automated red-teaming frameworks and defensive proxies. ...

DeepSeek V4 Flash Vision Exp is an experimental multimodal model that accepts images alongside text, outputs text only, and pairs a 1M-token context window with an Intelligence Index score of 51 — ranked #3 out of 172 comparable models. At cache-hit input prices near $0.0028 per million tokens, it is shaping up as the cheapest capable vision path for high-frequency agent loops. Here is everything developers need to know before building with it. ...

Anthropic is quietly A/B testing reduced default effort levels in Claude Code, and the change does not make the coding agent dumber — it makes it less proactive. Effort controls how much autonomous work Claude performs per turn (reading files, running tests, double-checking its own output) before responding or asking for context. When the default drops, you get faster, cheaper turns that skip deep investigation, which is fine for scoped tasks but can silently degrade complex multi-file refactors. ...

A self-hostable Codex is an open-source coding-agent platform you run on your own infrastructure instead of depending on a single vendor’s cloud. Proliferate is exactly that: an AGPL-3.0 AI IDE from a Y Combinator S25 founder that runs Claude Code, Codex, OpenCode, Cursor, and Grok in parallel inside one workspace, gives each task an isolated git worktree, and lets you self-host the entire control plane with Docker, AWS, Kubernetes, or even air-gapped operation. It is the open-source answer to the “Codex everything app” thesis. ...