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I’ve been thinking about a gap in the way we discuss graphs in AI. Most of the conversation starts after the graph already exists. We talk about graph neural networks, GraphRAG, graph agents, and graph foundation models.
DigitalOcean Managed Agents secure autonomous workloads by ensuring agents never hold live credentials directly, utilizing ephemeral execution-time brokering via Action Gateway and strict runtime boundaries.
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.
DigitalOcean Managed Agents unifies compute, inference, and data into one platform for AI agents, billed for actual work, not idle time.
The following article originally appeared on Elevate and is being reposted here with the author’s permission. A software factory is a repeatable loop around software work. If you’re building a software factory, code good enough to ship still needs human taste and ownership.
What is a developer to do when they need something more tangible than a chat box? Enter canvases. The post When chat is the wrong UI appeared first on The GitHub Blog.
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 appeared first on The GitHub Blog.
How we rebuilt the diff surface in the GitHub Copilot app to open a million-line pull request with hundreds of inline review comments. The post Rendering huge pull requests in the GitHub Copilot app appeared first on The GitHub Blog.
The following article originally appeared on Arize’s blog and is being reposted here with the author’s permission. This week the AI community was in uproar about Jev from TypeSafe, not just a new model but a new kind of model: one that classifies, scores, and routes but can’t write a sentence.
Ask most engineers what MCP is and you’ll get the same answer: a way to plug tools into an LLM. Fair enough, as far as it goes. But that description treats MCP like plumbing, and after months building MCP-based integrations for large enterprise platforms, I don’t think plumbing is the right…
The following article originally appeared on Venkatesh Rao’s Substack, Contraptions, and is being republished here with the author’s permission. The sole athletic achievement of my life came in 1993: winning the IIT Bombay freshman 50m freestyle race with a time of 41s.
The early rapid expansion of AI capabilities that focused on frontier models was largely ushered into the world by a few powerful, US-based AI labs. Open-weight models released from labs in China, early on from DeepSeek, and later from Moonshot, Z.ai, and others, have in part disrupted that…
This is the third post in a four-part series about post-training. If you missed them, read part 1 and part 2. The final post, on implementing your own pipeline, will be coming October 7.
When considering the history of AI, Richard Sutton observed that brute force and compute scale has always trumped human expertise, and when you look for it, you can see this “bitter lesson” play out throughout tech history.
The following article originally appeared on Addy Osmani’s blog and is being republished here with the author’s permission. A software factory harnesses loops at scale. You can run the loop with humans in it (light factory), trading judgment and concentration against speed and breakage.
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 Blog.
The way we talk about data is changing faster than the way we build it. Every quarter a vendor ships a new approach, coins a new term for it, or quietly adopts a term someone else has been using and redefines it to fit the shape of their product. None of this is malicious. Every […]
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 Rust, using Copilot appeared first on The GitHub Blog.
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