Search: “agents”

We are committed to empowering every developer by building an open, secure, and AI-powered platform that defines the future of software development. The post GitHub recognized as a Leader in the Gartn

Learn to find and exploit real-world agentic AI vulnerabilities through five progressive challenges in this free, open source game that over 10,000 developers have already used to sharpen their securi

In this blog post, I explain how to use the new fuzzing taskflow based on the GitHub Security Lab Taskflow Agent AI framework. The post AI-powered fuzzing with the GitHub Security Lab Taskflow Agent a

See how four GitHub agent apps can help you scope, secure, roll out, and ship a feature across the SDLC–all without leaving GitHub. The post How to bring your software delivery workflow into GitHub wi

Chat is great for intent, but agent work gets lost in the scroll. Here is how I use canvases with my agentic workflows—and why your workflow also deserves a canvas. The post How canvases make agentic

Agentic workflows that run on every pull request can quietly accumulate large API bills. Here's how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them

Learn about the experimental general-purpose accessibility agent that GitHub is piloting. The post Building a general-purpose accessibility agent—and what we learned in the process appeared first on T

A practical guide to reviewing agent-generated pull requests: what to look for, where issues hide, and how to catch technical debt before it ships. The post Agent pull requests are everywhere. Here’s

How to build the “Trust Layer” for Github Copilot Coding Agents without brittle scripts or black-box judgements by using dominatory analysis. The post Validating agentic behavior when “correct” isn’t

Explore how the GitHub Copilot agentic harness delivers strong results across multiple benchmarks and leading token efficiency, while maintaining flexibility to choose among more than 20 models. The p

A rewrite this size wasn't affordable before agents. Here's what porting the Copilot agent runtime to 800,000 lines of production Rust actually took. The post Migrating the GitHub Copilot runtime to R

Explore how the Aspire team turns merged product changes into SME-reviewed docs pull requests, closing the gap between release and documentation. The post Automating cross-repo documentation with GitH

We’re launching ReviewBench, a benchmark for code review agents built on representative GitHub pull requests, multi-source ground truth, calibrated evaluation, and production-aligned metrics. The post

Describe the interface you need in plain English, then let the agent build a live surface you can both use and update—so you spend less time adapting to tools and more time getting work done. The post

We dive into these questions and other AI hot takes on the latest episode of the GitHub Podcast. The post Should you read the code, is RAG dead, and did Skills kill MCP? appeared first on The GitHub B

Checking agent-generated code usually means hopping between tabs. Learn how to view diffs, run terminal commands, and preview web apps side by side in the GitHub Copilot app. The post GitHub Copilot a

NVIDIA Nemotron 3.5 Lightning NVIDIA Nemotron 3.5 Lightning is an open 30B mixture-of-experts (MoE) model with 3B active parameters built for that execution layer of always-on agents. It is designed f

What's Changed launch: keep Claude Code channels available by @hoyyeva in #17210 cmd: remove dead agent prompt wrappers by @ParthSareen in #17227 agent: reorder working directory instruction by @Parth

What's Changed New interactive agent experience: running ollama now launches an agent to help you code and delegate work ❯ ollama Ollama 0.32.0 ▸ Chat, Code, & Work (glm-5.2:cloud) Chat with models, c

How migrating Copilot code review to shared Unix-style code exploration tools reduced review cost by reshaping agent workflows around pull request evidence. The post Better tools made Copilot code rev

Mariko Wakabayashi is a Principal Applied Scientist at Microsoft who leads the development of agentic AI workflows for cybersecurity operations. She specializes in evaluating LLM‑powered systems and a

Muse Glimmer Muse Glimmer is now available on all platforms. Muse Glimmer can power coding agent applications such as Claude Code, Codex, Pi and more, as well as long-running personal assistants such

Muse Glimmer Note: Muse Glimmer is currently available via initial support via Ollama's MLX engine on Apple Silicon. Additional support and optimizations for Apple Silicon, NVIDIA, AMD, and other plat

ui: CWD for agent (#26518) server : extend file_glob_search for UI pickers ui : add per-conversation working directory with picker ui : add path navigation and search scope to cwd picker Treat path-li

New to the GitHub Copilot app? Learn how to start projects, work with AI agents, explore canvases, and streamline your development workflow. The post GitHub Copilot app for Beginners: Getting started

Ollama v0.20.6-rc0 is a pre-release update to the Ollama local model runner, published on April 10, 2026. Key changes include adding a Hermes agent integration guide to the docs, fixing missing par...

Learn three ways to get noticed and grow your career as AI reshapes how developers build software. The post AI is rewriting the developer career ladder. Here’s how to stand out. appeared first on The

Overview llama.cpp 0.4.0 adds initial Qwen3.8-Flash-Next and Nemotron-3-Puzzle support, on-demand tensor reading, per-slot server context limits, video input options, and a ggml update to 0.23.0 with

Qwen 3.8 - 27B model support This release adds the support of Qwen 3.8 27B. For Apple Silicon devices, Ollama has in particular optimized for maximum performance and output quality suitable for repeat

What's Changed x/create: quantize lm_head at 8-bit in the requested family by @jessegross in #17357 test: harden flaky updater and transfer unit tests by @dhiltgen in #17378 server: fix ps data race o

What's Changed Improved Gemma 4 tool calling and multi-turn reasoning, including more reliable tool-response continuations Fixed a recurrent MLX model cache leak that could increase memory use across

The secondary button gets its own look back and the chat add button its own light surface. Pressable elements get a pointer cursor again, the font rendering smooths on the app shell, the root layout r

cli: exit on stdin EOF and drop the console wide Ctrl+C broadcast (#29722) cli: exit on stdin EOF and drop the console wide Ctrl+C broadcast On Windows the simple input reader sends CTRL_C_EVENT to ev

chat : add dedicated Ling 3.0 (Bailing V3) parser (#28682) chat: add dedicated Ling 3.0 (Bailing V3) parser Ling 3.0 Flash templates pre-open the think block in the generation prompt, so the model nev

vulkan: add dedicated iq4_xs mat-vec shader (#28426) vulkan: add dedicated iq4_xs mat-vec shader Dedicated mul_mat_vec_iq4_xs for the dmmv path, replacing the generic fallback. ~+6-17% token generatio

Enterprise Java developers have a new superpower—drive GitHub Copilot from idiomatic Java code with annotations, virtual threads, and more. The post Using the GitHub Copilot SDK for Java appeared firs

Ollama v0.31.2-rc1 is a pre-release version released on July 6, 2026. This release includes CI improvements to avoid unbounded parallelism, fixes for CUDA toolkit lookup, updates to cloud documentatio

v0.30.12 is a release candidate (rc0) that fixes a gemma4:12b floating point exception crash on x86, CUDA, Linux, and Windows systems. It includes improvements to ollama launch for Hermes Desktop, all

v0.21.1-rc1 is a release candidate for Ollama, an open-source tool for running machine learning models locally. The release candidate phase indicates testing and bug-fixing before the stable v0.21.1 r

Ollama v0.20.6-rc1 is a pre-release candidate for the v0.20.6 update to Ollama, the open-source framework for running large language models locally. Based on the associated v0.20.6 pre-release notes,

Karpathy’s pattern: LLMs compile raw sources into a persistent interlinked markdown wiki—entity/concept pages, index, log—rather than re-deriving answers from RAG on every query.