888 articles on AI & ML.
AI coding tools like agents can be valuable allies in everyday development work. They help handle time-consuming grunt work, guide you through large legacy codebases, and offer low-risk ways to implement features in previously unfamiliar programming languages. Here are practical, easy-to-apply techniques to help you use these tools to improve your workflow.
AI agents need secure, isolated environments that spin up instantly. Vercel Sandbox is now generally available with filesystem snapshots, container support, and production reliability.
Moltworker is a middleware Worker and adapted scripts that allows running Moltbot (formerly Clawdbot) on Cloudflare's Sandbox SDK and our Developer Platform APIs. So you can self-host an AI personal assistant — without any new hardware.
Learn how GitHub built an accessible, multi-terminal-safe ASCII animation for the Copilot CLI using custom tooling, ANSI color roles, and advanced terminal engineering.
With the Figma MCP app in Claude, powered by Anthropic, designers, developers, and product managers can now create AI-generated FigJam diagrams.
Explore the GitHub Copilot CLI and try interacting with Copilot directly from your terminal.
Now in technical preview, the GitHub Copilot SDK can plan, invoke tools, edit files, and run commands as a programmable layer you can use in any application.
Developing effective agentic AI requires a new research playbook. When systems plan, decide, and act on our behalf, UX moves beyond usability testing into the realm of trust, consent, and accountability. Victor Yocco outlines the research methods needed to design agentic AI systems responsibly.
Run tests, fix code, and get support—right in your workflow. Stay focused and let Copilot handle the busywork.
Learn how we are using the newly released GitHub Security Lab Taskflow Agent to triage categories of vulnerabilities in GitHub Actions and JavaScript projects.
Cloudflare acquires Human Native, an AI data marketplace specialising in transforming content into searchable and useful data, to accelerate work building new economic models for the Internet.
Copilot’s cross-agent memory system lets agents learn and improve across your development workflow, starting with coding agent, CLI, and code review.
Announcing GitHub Security Lab Taskflow Agent, an open source and collaborative framework for security research with AI.
We’ve improved personalized video recommendations on Facebook Reels by moving beyond metrics such as likes and watch time and directly leveraging user feedback. Our new User True Interest Survey (UTIS) model, now helps surface more niche, high-quality content and boosts engagement, retention, and satisfaction. We’re doubling down on personalization, tackling challenges like sparse user data […] Re
We've encapsulated 10+ years of React and Next.js optimization knowledge into react-best-practices, a structured repository optimized for AI agents and LLMs.
AI is designed to help you do what you love most, not replace your expertise. Discover how developer feedback and real-world experience are shaping AI coding tools that keep you in control.
Learn how custom instructions, reusable prompts, and custom agents help GitHub Copilot deliver more accurate results.
Under the hood of UCP: the open protocol powering agentic commerce, enabling AI agents to discover, negotiate, and transact with any merchant.
AI is settling the “typed vs. untyped” debate by turning type systems into the safety net for code you didn’t write yourself.
[Penpot](https://penpot.app/?utm_source=SmashingMagazine&utm_medium=Article&utm_campaign=MCPserver) is experimenting with MCP (Model Context Protocol) servers, which could lead to designers and developers being able to perform tasks in Penpot using AI that’s able to understand and interact with Penpot design files. Daniel Schwarz explains how [Penpot MCP](https://github.com/penpot/penpot-mcp) serv
v0’s composite AI pipeline boosts reliability by fixing errors in real time. Learn how dynamic system prompts, LLM Suspense, and autofixers work together to deliver stable, working web app generations at scale.
Design and cooking share a truth: Preparation determines the outcome. Structured prompts turn AI from guesswork into a reliable design partner.
Explore the GitHub Blog’s top posts covering the biggest software development topics of the year.
An easy-to-remember acronym, WRAP will help you write effective issues, refine your instructions, and get the most out of Copilot coding agent.
Turn scattered user research into AI-powered personas that give anyone consolidated multi-perspective feedback from a single question.
Introducing agents, tool execution approval, DevTools, full MCP support, reranking, image editing, and more.
The feature store is a critical part of how we rank and retrieve the right context across your work.
AI competition intensified in 2025 as ChatGPT gained strong challengers. Instagram climbed, X declined, and platforms like Shopee, Temu, and Kwai reshaped global Internet usage. Our 2025 DNS data shows how Internet patterns evolved.
Figma designer–turned–product manager Nikolas Klein worked on building prototyping tools for seven years. Then AI changed the game.
We envision the future of AI-enabled tooling to look like near-effortless engineering for sustainability. We call it Continuous Efficiency.
Our Agentic Commerce Suite gets your business agent-ready. It enables you to sell on AI agents by making your products discoverable, simplifying your checkout, and allowing you to accept agentic payments via a single integration.
We’re introducing new ways to track your AI credit usage in Figma, and soon you’ll have more ways to buy additional AI credits.
AI can help you build faster than ever, but it can also produce bugs, issues, and problems. Use these strategies to keep your speed without losing control of your code.
Discover how advanced AI users are redefining software development—shifting from code producers to strategic orchestrators—through delegation, verification, and a new era of AI-fluent engineering.
Lead your organization’s AI strategy before someone else defines it for you. A practical framework for UX professionals to shape AI implementation.
Tangle saves months of compute time, makes every experiment automatically reproducible, and allows teammates to share computation without coordination.
Explainable AI isn’t just a challenge for data scientists. It’s also a design challenge and a core pillar of trustworthy, effective AI products. Victor Yocco offers practical guidance and design patterns for building explainability into real products.
Follow this step-by-step guide to learn how to debug your issues using GitHub Copilot Spaces and Copilot coding agent.
Use partner-built Copilot agents to debug, secure, and automate engineering workflows across your terminal, editor, and github.com.
Run multiple Copilot agents from one place. Learn prompt techniques, how to spot drift early, and how to review agent work efficiently.
FLUX.2 [dev] by Black Forest Labs is now on Workers AI! This advanced open-weight image model offers superior photorealism, multi-reference inputs, and granular control with JSON prompting.
Discover how Python changed developer culture—and see why it keeps evolving.
Learn more about the agentic security principles that we use to build secure AI products—and how you can apply them to your own agents.
GitHub Copilot’s next edit suggestions just got faster, smarter, and more precise thanks to new data pipelines, reinforcement learning, and continuous model updates built for in-editor workflows.
We spoke with product leaders and practitioners about the shifts they’re seeing in how design systems are built, used, and maintained.
We’re using embedding-guided tool routing, adaptive clustering, and a streamlined 13-tool core to deliver faster experience in VS Code.
Learn how to write effective agents.md files for GitHub Copilot with practical tips, real examples, and templates from analyzing 2,500+ repositories.
We’ve released Ax 1.0, an open-source platform that uses machine learning to automatically guide complex, resource-intensive experimentation. Ax is used at scale across Meta to improve AI models, tune production infrastructure, and accelerate advances in ML and even hardware design. Our accompanying paper, “Ax: A Platform for Adaptive Experimentation” explains Ax’s architecture, methodology, and h
The Gemini 3 Pro Preview model, released today, is now available through AI Gateway and in production on v0.app.
Bringing Replicate’s tools into Cloudflare will continue to make our Workers Platform the best place on the Internet to build and deploy any AI or agentic workflow.
Building effective, agentic AI isn’t just about adding more; it’s about helping the model focus on what matters most.
Discover practical tips, examples, and best practices for writing effective instructions files. Whether you’re new or experienced, you’ll find something to level up your code reviews.
An interview with the leader of GitHub Next, Idan Gazit, on TypeScript, Python, and what comes next.
A breakdown of how Copilot coding agent has contributed to a better, more powerful GitHub.
We recently released a series of improvements to expand multiprocessor support, give you more control over your billing and invoicing models, and better tailor your pricing for AI products. Here’s everything that’s new.
We’re sharing details about Meta’s Generative Ads Recommendation Model (GEM), a new foundation model that delivers increased ad performance and advertiser ROI by enhancing other ads recommendation models’ ability to serve relevant ads. GEM’s novel architecture allows it to scale with an increasing number of parameters while consistently generating more precise predictions efficiently. GEM propagat
AI platform, ServiceNow, and Figma announced a strategic collaboration to turn design vision into enterprise transformation.
