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Summaries are not the original full articles. ## How API Design Is Evolving for AI Agents, Security, Reliability, and Compliance DevFeed: [How API Design Is Evolving for AI Agents, Security, Reliability, and Compliance]() Original publisher: [Read original article]() Author: J Simpson Published: 2026-09-17T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [API](), [Architecture & Design](), [Artificial Intelligence](), [reliability](), [Security]() Tags: [agents](), [ai-agents](), [api](), [api-architecture](), [api-as-a-product](), [api-design](), [api-discovery](), [api-security](), [architecture](), [authorization](), [blog](), [mcp](), [microservices](), [rate-limiting](), [reliability](), [security]() ### AI overview This article examines six ways API design is evolving as APIs serve AI agents and other machine consumers, with implications for security, reliability, and regulatory compliance. ### Source excerpt For over two decades, API design and architecture remained remarkably consistent. Perhaps it's the outsized influence of Roy Fielding's RESTful dissertation, but API designers have stuck to the principles of stateless architecture, resource-based endpoints, and HTTP commands to an impressive degree. That's all starting to change, now that we've radically recontextualized the way we use ... ## \[Aug 2026\] AI Community -- Activity Highlights and Achievements DevFeed: [\[Aug 2026\] AI Community -- Activity Highlights and Achievements]() Original publisher: [Read original article]() Author: Nari Yoon Published: 2026-09-17T05:12:15Z Content type: article Language: en Sources: [Google Developer Experts - Medium]() Topics: [Google AI](), [Google](), [google-antigravity](), [Artificial Intelligence](), [MCP Server](), [computer-use](), [Fine-tuning]() Tags: [2026](), [agentic-ai](), [ai](), [ai-coding-agents](), [ai-studio](), [antigravity](), [api](), [automation](), [community](), [computer-use](), [gemini](), [google](), [google-ai](), [google-cloud](), [mcp](), [mcp-server](), [multi-agent](), [ocr](), [paper](), [pitfalls]() ### AI overview A monthly roundup of Google AI community activities and achievements, covering Antigravity prototyping and engineering, AI coding agents, MCP-based remote control, computer-use agent orchestration, earthquake research, and TPU fine-tuning and migration guidance. ### Source excerpt We love sharing the accomplishments of the Google AI communities over the month. We appreciate all the hard work and dedication of our community members. Without further ado, here are the key highlights by products! Agentic DevelopmentAntigravityPrototype App: OCR and Text Extraction by the author Prototyping and Bringing Ideas to Application Using Google AI Studio and Antigravity 2.0 by AI GDE Joan Santoso (Indonesia) shares a rapid prototyping workflow building an AI-powered Form Extractor using the Gemini API, featuring a lightweight OCR and text extraction workflow. Antigravity Engineering Series by GDE Amulya Bhatia (Germany) focuses on key features of Antigravity 2.0 across 10 articles covering topics such as multi-agent orchestration, safety architecture, and workflow automation, accompanied by source code examples. (image soruce) Remote Control for Google Antigravity: Drive Your AI Coding Agent From Telegram 🛰 by GDE Nicola Guglielmi (Italy) introduces an open-source MCP server that turns Telegram into a remote control surface for AI coding agents. Before the Quake: How Antigravity CLI's AI Agents & IoT Data Predict Earthquakes by GDE Kanshi Tanaike (Japan) introduces the paper establishing Unified LAIC-AGW Theory by integrating ultra-dense IoT weather data with seismic moment tensors. It demonstrates a pre-seismic early warning capability by capturing enthalpy anomalies and acoustic-gravity waves. ADKAI GDE Henry Ruiz (US) and AI GDE Margaret Maynard-Reid (US) AI GDE Henry Ruiz (US) and AI GDE Margaret Maynard-Reid (US) introduced UISurf: An Operator-Centric Multi-Agent Platform for Observable and Cross-Environment UI Automation at the Agentic AI Summit 2026. They highlighted how the model-agnostic framework leverages the Google Cloud and Gemini ecosystems, such as GEAP and ADK, to orchestrate and evaluate computer-use agents across web, desktop, and mobile environments. Frameworks and ResearchTPU Introduction to SFT on TPU with Tunix -- 10 pitfalls until 2 ## Rider and ReSharper 2026.2.2 Are Out! DevFeed: [Rider and ReSharper 2026.2.2 Are Out!]() Original publisher: [Read original article]() Author: Alexander Kurakin Published: 2026-09-16T14:12:44Z Content type: release Language: en Sources: [The JetBrains Blog]() Topics: [rider](), [resharper](), [AI-assisted coding](), [test-coverage]() Tags: [2026](), [ai-agent-hooks](), [ai-agents](), [code-coverage](), [coverage](), [hooks](), [jetbrains](), [macos](), [mcp](), [net](), [net-tools](), [releases](), [resharper](), [rider](), [update]() ### AI overview JetBrains releases Rider, ReSharper, and .NET tools 2026.2.2, adding an AI Agent Setup widget in Rider, more targeted hook feedback for coding agents, TUnit coverage support, and fixes including a macOS freezing issue. ### Source excerpt We've released version 2026.2.2 of ReSharper, Rider, and .NET tools. You can install this update from inside the tools themselves, through the Toolbox App, or on our website. Here's what's new in this update. Rider 2026.2.2 AI Agent Setup widget We've recently added a wide range of features to help you work with coding agents [...] ## ADLX 2.0: Extending graphics control to AI agents and agentic apps DevFeed: [ADLX 2.0: Extending graphics control to AI agents and agentic apps]() Original publisher: [Read original article]() Author: Pete Vagiakos; Alexander Blake-Davies Published: 2026-09-16T10:00:00Z Content type: article Language: en Sources: [AMD GPUOpen]() Topics: [GPU](), [Artificial Intelligence](), [Hardware](), [SDK](), [Model Context Protocol]() Tags: [agents](), [ai](), [amd-device-library-extra](), [amd-device-library-extra-adlx](), [announcement](), [developers](), [gpu](), [hardware](), [mcp](), [ml](), [product-blogs](), [product-release](), [tools]() ### AI overview AMD ADLX 2.0 adds an AI extension framework and MCP servers that connect AI applications with AMD graphics technologies, enabling developers to build apps that monitor, manage, and optimize AMD graphics hardware. ### Source excerpt AMD ADLX 2.0 adds AI extensions and MCP servers to help developers build intelligent apps that can monitor, manage, and optimize AMD graphics hardware. ## MCP Apps: Your UI, Their Chat DevFeed: [MCP Apps: Your UI, Their Chat]() Original publisher: [Read original article]() Author: James Strong Published: 2026-09-16T07:00:00Z Content type: article Language: en Sources: [Scott Logic]() Topics: [Model Context Protocol (MCP)](), [ui](), [ChatGPT](), [App]() Tags: [ai](), [app](), [artificial-intelligence](), [chatgpt](), [mcp](), [ui]() ### AI overview The article examines MCP Apps, an extension of the Model Context Protocol, alongside the protocol's 2026-07-28 changes. It explains how MCP Apps let servers return isolated, interactive, stateful UIs that clients such as ChatGPT can embed in agent responses, with examples including dashboards, data tables, and forms. ### Source excerpt A lot of focus has been put on the statelessness introduced as part of the new MCP specification, but the formalisation of extensions, including MCP Apps, is also worth attention. Using FastMCP and Prefab, I put together an MCP app and show it running in ChatGPT. ## Shared Selective Persistent Memory for Agentic LLM Systems DevFeed: [Shared Selective Persistent Memory for Agentic LLM Systems]() Original publisher: [Read original article]() Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Apple Machine Learning Research]() Topics: [Large Language Model](), [agent observability](), [Framework](), [Code](), [configuration](), [Access Control](), [Git](), [Model Context Protocol (MCP)](), [CSV](), [SQL](), [Grafana]() Tags: [access-control](), [agentic](), [agents](), [code](), [configuration](), [csv](), [dashboards](), [git](), [llm](), [mcp](), [memory](), [platform](), [replication](), [sql]() ### AI overview This research introduces shared selective persistent memory for agentic LLM systems. The architecture retains reusable task specifications, data schemas, tool configurations, and output constraints while discarding session-specific reasoning traces. Shared workspaces support role-based collaborative reuse, and experiments report higher task completion than no memory or full-history persistence, along with zero-token data refresh and lower token costs. ### Source excerpt Agentic LLM systems that generate code through multi-turn tool use face a fundamental context problem: each session starts from zero, discarding the configuration choices, domain constraints, data schemas, and tool-use patterns that made previous sessions productive. Naively persisting entire conversation histories is both token-inefficient and counterproductive--irrelevant context degrades generation quality. We introduce shared selective persistent memory, a memory architecture for agentic systems that identifies and retains four categories of reusable context--task specifications, data... ## Turso Accident Protection Enables Database Restoration for Up to 5 Days DevFeed: [Turso Accident Protection Enables Database Restoration for Up to 5 Days]() Original publisher: [Read original article]() Author: Pedro Muniz Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Turso Blog]() Topics: [Turso](), [Databases](), [MCP Server]() Tags: [ai-agents](), [database](), [databases](), [feature](), [mcp](), [mcp-server](), [turso]() ### AI overview Turso has released Accident Protection, allowing databases deleted on a paid plan to be restored for up to five days at no additional cost. The feature is available through the UI and Turso MCP server. ### Source excerpt Agents delete things. Now you can undelete them. Restore databases for up to 5 days after deletion, on any paid plan, at no additional cost. ## MCP went stateless: What changed in the 2026-07-28 spec DevFeed: [MCP went stateless: What changed in the 2026-07-28 spec]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Model Context Protocol](), [migration](), [HTTP](), [servers](), [client]() Tags: [api](), [client](), [http](), [load-balancer](), [mcp](), [replacement](), [request](), [routing](), [server](), [servers](), [sessions](), [stateless](), [stream]() ### AI overview The 2026-07-28 MCP specification removes protocol-level sessions, the initialize handshake, and stream resumability, making the protocol behave more like an ordinary HTTP API. Most migrations are mechanical, but lost stream requests can cause reliability regressions or duplicated side effects when retried, so side-effecting tools need application-level idempotency keys. The elicitation change also requires architectural rework. ### Source excerpt Sessions, the initialize handshake, and stream resumability are all gone. Here is what replaced them, and what breaks if you ignore it. ## Highlights from the 2026 State of Knowledge Report DevFeed: [Highlights from the 2026 State of Knowledge Report]() Original publisher: [Read original article]() Author: Lauren Volpi Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Artificial Intelligence](), [HTML](), [Website](), [MCP]() Tags: [2026](), [ai](), [ai-agents](), [ai-trends](), [documentation](), [llms-txt](), [markdown](), [mcp](), [report]() ### AI overview Mintlify's 2026 State of Knowledge Report examines how AI agents are changing documentation readership and access. It reports that agent requests exceeded human page loads on Mintlify-powered sites in August, with many agents using Markdown, llms.txt, agent skills, and MCP tool calls. Controlled tests across 20 documentation sites found that linking Markdown pages to llms.txt improved agent navigation and reduced token consumption. ### Source excerpt AI agents overtook humans as the primary readers across Mintlify-powered sites. In August alone, agents made 257 million web requests compared to 131 million human page loads, which means agent traffic now outnumbers human traffic by nearly 2:1. ## OpenAI's Greg Brockman discusses computer use as an alternative to purpose-built AI agent integrations DevFeed: [OpenAI's Greg Brockman discusses computer use as an alternative to purpose-built AI agent integrations]() Original publisher: [Read original article]() Author: Meredith Shubel Published: 2026-09-15T23:41:22Z Content type: opinion Language: en Sources: [The New Stack]() Topics: [computer-use](), [OpenAI](), [Model Context Protocol](), [Reinforcement learning]() Tags: [ai-agents](), [computer-use](), [developer-tools](), [developers](), [mcp](), [model-context-protocol](), [openai](), [reinforcement-learning]() ### AI overview OpenAI president and co-founder Greg Brockman discusses whether AI agents could use computers through screens, keyboards, and mice instead of relying on purpose-built MCP servers, CLIs, APIs, and other integrations. ### Source excerpt This week on the a16z show, Greg Brockman, president and co-founder of OpenAI, made the point that developers have been The post OpenAI president: "The computer should be there to empower you." So stop retooling software for AI agents appeared first on The New Stack. ## Meta lets Claude and Codex configure WhatsApp Business via MCP DevFeed: [Meta lets Claude and Codex configure WhatsApp Business via MCP]() Original publisher: [Read original article]() Author: Paul Sawers Published: 2026-09-15T22:08:56Z Content type: news Language: en Sources: [The New Stack]() Topics: [Meta](), [Model Context Protocol](), [AI-assisted coding](), [Claude](), [codex](), [API]() Tags: [ai](), [ai-agents](), [ai-coding-agents](), [api](), [claude](), [codex](), [developer-tools](), [mcp](), [mcp-server](), [meta](), [model-context-protocol](), [product](), [updates]() ### AI overview Meta announced a WhatsApp Business Tools MCP server that lets developers connect Claude or Codex to selected businesses they administer. The agents can help configure WhatsApp Business accounts, verify phone numbers, manage templates, and perform related API tasks, with access scoped to the businesses the developer selects. ### Source excerpt Any business worth its salt in 2026 needs to be embracing the right tools to reach its customers, and few The post Meta lets Claude and Codex configure WhatsApp Business via MCP appeared first on The New Stack. ## Cypress Cloud MCP adds test details, filters, and compact responses DevFeed: [Cypress Cloud MCP adds test details, filters, and compact responses]() Original publisher: [Read original article]() Published: 2026-09-15T16:21:48Z Content type: release Language: en Sources: [Cypress Blog]() Topics: [Cypress](), [MCP](), [Test coverage]() Tags: [cypress](), [mcp](), [release](), [responses](), [september-2026]() ### AI overview Cypress Cloud MCP now provides compact responses by default, new per-spec and per-test tools, filters by run, spec, and test status, and duration data across multiple levels. It also adds deeper links for accessibility and UI coverage reports. ### Source excerpt New tools, more data, smaller responses: what's new in Cypress Cloud MCP as of September 2026. ## Build an interview coach app with the GitHub Copilot SDK DevFeed: [Build an interview coach app with the GitHub Copilot SDK]() Original publisher: [Read original article]() Author: Justin Yoo Published: 2026-09-15T16:00:11Z Content type: tutorial Language: en Sources: [Developer Blogs]() Topics: [GitHub Copilot](), [SDK](), [Model Context Protocol](), [.NET](), [Blazor]() Tags: [agent-framework](), [ai](), [blazor](), [github-copilot](), [github-copilot-sdk](), [mcp](), [microsoft-agent-framework](), [microsoft-foundry](), [model-context-protocol](), [net](), [sdk]() ### AI overview This tutorial demonstrates how to build an interview coach application with the GitHub Copilot SDK in .NET. The sample uses a Blazor chat interface, Copilot instructions and callable tools, and Model Context Protocol services for document handling and interview records. It emphasizes giving Copilot application-specific tools rather than access to shell commands or source files. ### Source excerpt An interview coach has to do more than ask questions. It needs to read a resume, follow up on an incomplete answer, and save enough context to give useful feedback at the end. Some of that work is conversation. Some of it requires calling an application service. The GitHub Copilot SDK lets you use the [...] The post Build an interview coach app with the GitHub Copilot SDK appeared first on Microsoft for Developers. ## MCP authorization: governing tool calls beyond OAuth DevFeed: [MCP authorization: governing tool calls beyond OAuth]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-15T15:04:00Z Content type: tutorial Language: en Sources: [WorkOS Blog]() Topics: [Model Context Protocol](), [Authorization](), [MCP OAuth](), [MCP Server](), [OAuth]() Tags: [authorization](), [mcp](), [mcp-server](), [oauth](), [permissions](), [policy](), [scope](), [scopes]() ### AI overview This guide explains why OAuth scopes alone cannot govern the content and destination of MCP tool calls. It presents server- or gateway-side policy enforcement before execution, including request-content inspection, approval handling, and testing for data leakage. ### Source excerpt Secure MCP tool calls beyond OAuth scopes. Learn where to enforce tool permissions, check request content, and test for data leakage with Airlock. ## Laravel MCP 1.0 Is Released DevFeed: [Laravel MCP 1.0 Is Released]() Original publisher: [Read original article]() Author: Eric L. Barnes Published: 2026-09-15T14:27:51Z Content type: release Language: en Sources: [Laravel]() Topics: [Laravel](), [Model Context Protocol (MCP)](), [OAuth](), [pkce](), [Caching](), [servers]() Tags: [caching](), [context-window](), [laravel](), [mcp](), [news](), [oauth](), [pkce](), [servers]() ### AI overview Laravel MCP 1.0 is the first stable release of Laravel's package for building Model Context Protocol servers. It adds protocol revision 2026-07-28 support, searchable tool catalogs, cache hints, stateless request handling, OAuth changes requiring PKCE, and Client ID Metadata Documents. ### Source excerpt Laravel MCP 1.0 ships protocol revision 2026-07-28, stateless servers, searchable tool catalogs, cache hints, and reworked OAuth with required PKCE. The post Laravel MCP 1.0 Is Released appeared first on Laravel News. Join the Laravel Newsletter to get Laravel articles like this directly in your inbox. ## Announcing Meta Business Messaging MCP: Set up and manage WhatsApp Business from your AI agent DevFeed: [Announcing Meta Business Messaging MCP: Set up and manage WhatsApp Business from your AI agent]() Original publisher: [Read original article]() Published: 2026-09-15T14:00:49Z Content type: release Language: en Sources: [Facebook Developers]() Topics: [Model Context Protocol](), [MCP Server](), [AI Agent](), [Messaging](), [Meta](), [API]() Tags: [agent](), [ai-agent](), [api](), [mcp](), [mcp-server](), [messaging](), [meta](), [testing](), [whatsapp](), [workflow]() ### AI overview Meta announces Business Messaging MCP, an MCP server that connects AI coding agents to the WhatsApp Business Platform. It supports account and phone-number setup, message templates, webhooks, and test messages within the developer workflow. ### Source excerpt Business Messaging MCP connects your AI coding agent to the WhatsApp Business Platform, so you can create accounts, add numbers, build templates, and send test messages without leaving your workflow. ## Red Hat Developer Hub: Preventing compliance violations with AI coding agents DevFeed: [Red Hat Developer Hub: Preventing compliance violations with AI coding agents]() Original publisher: [Read original article]() Author: Evan Shortiss, Ben Wilcock Published: 2026-09-15T13:17:13Z Content type: tutorial Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [internal developer portal](), [AI-assisted coding](), [Backstage](), [Claude Code](), [Command-line interface](), [Model Context Protocol](), [Security]() Tags: [ai-coding-agents](), [ai-inference](), [backstage](), [catalog](), [claude-code](), [cli](), [developer](), [developer-productivity](), [developer-tools](), [mcp](), [platform-engineering](), [security]() ### AI overview This tutorial demonstrates how an AI coding agent connected to Red Hat Developer Hub can query a Backstage software catalog, TechDocs, and software templates before making architectural decisions. Using a simulated insurance-company catalog, the demo shows how this context can help avoid PCI-DSS compliance violations, resolve governance conflicts, and create a traceable decision record. ### Source excerpt AI coding agents can generate entire services, reason about architectures, and scaffold applications in minutes. But ask one to build a service for your organization and you'll quickly notice the gap: it doesn't know your rules. It doesn't know which messaging broker your compliance team mandates, which services already exist in adjacent domains, or which project template is the golden path for your team. The post Red Hat Developer Hub: Preventing compliance violations with AI coding agents appeared first on Red Hat Developer. ## Using the Komodo MCP Server to Manage Docker Infrastructure with AI Assistants DevFeed: [Using the Komodo MCP Server to Manage Docker Infrastructure with AI Assistants]() Original publisher: [Read original article]() Author: Brandon Lee Published: 2026-09-15T12:38:26Z Content type: tutorial Language: en Sources: [Virtualization Howto]() Topics: [Homelab](), [Model Context Protocol (MCP)](), [Docker](), [Docker Compose](), [GitOps](), [Artificial Intelligence]() Tags: [ai](), [automation](), [containers](), [docker](), [gitops](), [home-lab](), [home-server](), [infrastructure](), [mcp]() ### AI overview This tutorial introduces the Komodo MCP Server, which connects AI assistants such as Claude and GitHub Copilot to Komodo for managing Docker environments. It describes natural-language control of containers, stacks, deployments, servers, builds, repositories, and related infrastructure through the Model Context Protocol. ### Source excerpt There are so many cool projects now that we have access to in the the realm of home lab, especially when it comes to automation and AI Ops for our... The post I Gave AI Control of My Docker Home Lab With Komodo MCP appeared first on Virtualization Howto. ## Super Stack: Laravel Starter Kit With Filament and NativePHP DevFeed: [Super Stack: Laravel Starter Kit With Filament and NativePHP]() Original publisher: [Read original article]() Author: Yannick Lyn Fatt Published: 2026-09-15T02:50:55Z Content type: news Language: en Sources: [Laravel]() Topics: [Laravel](), [MCP](), [MCP Server](), [Model Context Protocol (MCP)](), [Open Source](), [PHP](), [Android](), [iOS]() Tags: [api](), [authentication](), [filament](), [github](), [laravel](), [laravel-packages](), [mcp](), [mcp-server](), [mobile](), [nativephp](), [open-source](), [starter-kits]() ### AI overview NativePHP released Super Stack, an open-source Laravel starter kit that combines a web app, Filament admin panel, native mobile app, Sanctum API tokens, and a Laravel MCP server in one repository. The MCP server is intended for local exploration and requires authentication before production deployment. ### Source excerpt Super Stack is an open-source Laravel starter kit from NativePHP with a Filament admin, a native mobile app, Sanctum, and a Laravel MCP server in one repo. The post Super Stack: Laravel Starter Kit With Filament and NativePHP appeared first on Laravel News. Join the Laravel Newsletter to get Laravel articles like this directly in your inbox. ## Rails Hyperdrive: supercharged agentic development for Rails DevFeed: [Rails Hyperdrive: supercharged agentic development for Rails]() Original publisher: [Read original article]() Author: Travis Turner (richardturner@evilmartians.com) Published: 2026-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Evil Martians]() Topics: [Ruby on Rails](), [AI-assisted coding](), [Model Context Protocol]() Tags: [agent-experience](), [ai](), [ai-coding-agents](), [claude-code](), [mcp](), [open-source](), [rails](), [ruby-on-rails](), [ruby-on-rails-consulting]() ### AI overview This tutorial introduces Rails Hyperdrive, a development-only Rails engine that gives AI coding agents live answers from a booted Rails application and lets gems provide agent guidance through Gemfile-gated knowledge. It covers installation, MCP server setup, skills, sub-agents, slash commands, upgrades, and integration for gem authors. ### Source excerpt Introducing Rails Hyperdrive: a development-only Rails engine that gives AI coding agents live answers from your booted app and lets any gem in your bundle ship guidance gated to your Gemfile. Convention over configuration, applied to agent knowledge. ## 🎙 How I AI: How two SpaceXAI designers use Grok Bot to do their jobs DevFeed: [🎙 How I AI: How two SpaceXAI designers use Grok Bot to do their jobs]() Original publisher: [Read original article]() Author: Lenny Rachitsky Published: 2026-09-14T15:03:48Z Content type: article Language: en Sources: [Lenny's Newsletter]() Topics: [Artificial Intelligence](), [Bot](), [Figma](), [Model Context Protocol (MCP)](), [Google]() Tags: [agents](), [ai](), [ai-agents](), [designers](), [figma](), [google](), [mcp](), [podcast]() ### AI overview This podcast episode features SpaceXAI designers John Bai and Peng Zheng describing how they use Grok Bot and AI agents in their design work. Peng demonstrates a self-updating personal site whose workflow handles location lookup, custom 3D artwork, and publishing. John describes using voice memos, Figma, and an MCP connection to create design assets and prototypes. ### Source excerpt Your weekly listens from How I AI, part of the Lenny's Podcast Network ## How Grok Bot designers use AI agents to build personal sites and product prototypes | John Bai & Peng Zheng DevFeed: [How Grok Bot designers use AI agents to build personal sites and product prototypes | John Bai & Peng Zheng]() Original publisher: [Read original article]() Author: Claire Vo Published: 2026-09-14T12:04:39Z Content type: article Language: en Sources: [Lenny's Newsletter]() Topics: [Artificial Intelligence](), [Figma](), [coding](), [Website]() Tags: [agents](), [ai](), [ai-agents](), [design](), [figma](), [mcp](), [prototype]() ### AI overview A 42-minute podcast episode featuring Grok Bot designers John Bai and Peng Zheng, who discuss using AI agents to update personal websites, automate design work in Figma, and turn ideas into working prototypes. ### Source excerpt Watch now (42 mins) | 🎙 Two designers at SpaceXAI show me how they use Grok Bot to run Figma from the gym, update a portfolio with one photo, and turn shower thoughts into working prototypes ## Symfony AI Spotlight: Mate, an Agent's Way into Your Runtime DevFeed: [Symfony AI Spotlight: Mate, an Agent's Way into Your Runtime]() Original publisher: [Read original article]() Author: Wachter Johannes Published: 2026-09-14T07:47:00Z Content type: article Language: en Sources: [Symfony Blog]() Topics: [Symfony](), [Artificial Intelligence](), [Command-line interface](), [MCP]() Tags: [agent](), [ai](), [cli](), [mcp](), [symfony]() ### AI overview Mate gives coding agents direct access to runtime information from Symfony applications, including profiler records, logs, and the dependency-injection container. In Symfony AI 0.13, it is a CLI with a discovery layer rather than a separately running MCP server, and it reads artifacts already written to disk instead of reconstructing behavior from source code. ### Source excerpt An agent working on a Symfony project can read every line of your source code and still not know what actually happened on the last request: which query was slow, or what the profiler already recorded five minutes ago, before anyone thought to ask. Source... ## Meta Open-Sources Astryx, Its Agent-Ready React Design System DevFeed: [Meta Open-Sources Astryx, Its Agent-Ready React Design System]() Original publisher: [Read original article]() Author: Bruno Couriol Published: 2026-09-13T23:39:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Meta](), [React](), [Open Source](), [CSS](), [Tooling](), [Accessibility](), [Model Context Protocol](), [User interface design](), [Web Development](), [Svelte](), [Flutter]() Tags: [accessibility](), [css](), [development](), [flutter](), [javascript](), [mcp](), [meta](), [meta-astryx-design-system](), [news](), [open-source](), [react](), [svelte](), [tokens](), [tooling](), [typescript](), [ui](), [web-development]() ### AI overview Meta has beta-released Astryx, an open-source React design system developed internally over eight years. It offers more than 150 accessible components, customizable CSS design tokens, precompiled StyleX-based styling, component code ejection, CLI tooling, and an MCP endpoint for developer and AI workflows. ### Source excerpt Meta recently announced the beta release of Astryx, an open-source React design system developed internally over eight years. Astryx builds on React 19 and StyleX to provide over 150 accessible UI components, customizable CSS design tokens, and dedicated CLI and MCP tooling -- for both engineers and AI agents. By Bruno Couriol [Next page]()