# cursor AI coding agent for building software, with desktop and command-line interfaces. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Manage Cursor costs with Datadog Cloud Cost Management DevFeed: [Manage Cursor costs with Datadog Cloud Cost Management]() Original publisher: [Read original article]() Author: Dom Nguyen; Doug Gunter Published: 2026-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [cloud cost management](), [cursor](), [finops](), [ai-coding]() Tags: [ai](), [ai-coding](), [analysis](), [cloud-cost-management](), [configuration](), [datadog](), [features](), [filter](), [finops](), [monitor](), [monitors](), [product](), [software]() ### AI overview This tutorial explains how Datadog Cloud Cost Management helps teams analyze Cursor spending by user, model, usage mode, and billing group. It covers identifying cost drivers, detecting unexpected changes, correlating spend with usage, and using monitors, budgets, and dashboards to manage AI coding costs alongside cloud and SaaS spending. ### Source excerpt Analyze Cursor spend by user and model, catch unexpected cost changes, and manage AI coding costs alongside your cloud and SaaS spend. ## Your AI coding spend bought 25% more output. Duplication rose 81%. DevFeed: [Your AI coding spend bought 25% more output. Duplication rose 81%.]() Original publisher: [Read original article]() Author: Steve Fenton Published: 2026-09-14T14:39:14Z Content type: article Language: en Sources: [The New Stack]() Topics: [ai-coding](), [Claude Code](), [cursor](), [datasets]() Tags: [agentic](), [ai](), [ai-coding](), [ai-impact](), [ai-operations](), [ai-strategy](), [ai-tools](), [claude-code](), [coding](), [contributed](), [contributed-octopus-deploy](), [cursor](), [dataset](), [software-development]() ### AI overview The article examines the return on investment from AI coding tools. It reports that heavy users gained 25% over their previous velocity, while code duplication rose 81%, and argues that output measures such as lines of code, pull requests, and feature counts do not reliably represent business value. ### Source excerpt Since they arrived on the scene, a great swathe of the software industry has pinned its hopes on AI tools, The post Your AI coding spend bought 25% more output. Duplication rose 81%. appeared first on The New Stack. ## Test Complex Interactions Earlier with AI Prototyping DevFeed: [Test Complex Interactions Earlier with AI Prototyping]() Original publisher: [Read original article]() Author: Megan Chan Published: 2026-09-11T17:00:00Z Content type: article Language: en Sources: [NN/g latest articles and announcements]() Topics: [Artificial Intelligence](), [User interface design](), [cursor]() Tags: [ai](), [article](), [case-studies](), [conversational-ai](), [cursor](), [design](), [prototyping]() ### AI overview AI prototyping tools enable teams to create high-fidelity, interactive prototypes of complex interfaces and test them with users earlier in the design process. The article discusses how Ramp used Cursor to prototype an AI chat-based expense-policy editor and uncover usability issues and edge cases. ### Source excerpt AI tools make it feasible to build fully interactive prototypes of complex interfaces so you can test them with users earlier in the design process. ## Your tools work. Will the agent use them right? DevFeed: [Your tools work. Will the agent use them right?]() Original publisher: [Read original article]() Author: Gil Levin Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Webflow Blog]() Topics: [Model Context Protocol (MCP)](), [Artificial Intelligence](), [Claude Code](), [cursor]() Tags: [ai-agents](), [chatgpt](), [claude-code](), [cursor](), [engineering](), [mcp](), [tools]() ### AI overview Webflow's MCP eval harness tests whether autonomous agents use its tools correctly to complete plain-English, multi-step tasks. It runs Claude Code or OpenAI's Codex CLI against disposable Webflow sites, combines deterministic checks with LLM and visual judging, and sends traces and scores to Datadog. ### Source excerpt A passing MCP tool test tells you the JSON is valid. It doesn't tell you an agent will pick the right tool, in order, and get the task right. ## Bring Claude and Cursor Coding Agents Into Your Port Catalog DevFeed: [Bring Claude and Cursor Coding Agents Into Your Port Catalog]() Original publisher: [Read original article]() Author: Sagi Keren Published: 2026-09-07T13:53:22Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [cursor](), [coding](), [Claude](), [AI-assisted coding](), [Orchestration](), [Automation]() Tags: [agents](), [ai](), [automation](), [claude](), [cloud](), [coding-agents](), [cursor](), [governance](), [workflows]() ### AI overview The article explains how Port integrates Claude and Cursor coding agents into a centralized catalog. It focuses on governance, ownership, auditing, workflow integration, and self-service creation through governed templates. ### Source excerpt Port catalogs, creates, and triggers Claude and Cursor coding agents, giving platform teams one governed registry for AI agents. ## The iOS Simulator Inside Cursor, Claude Code, and Codex DevFeed: [The iOS Simulator Inside Cursor, Claude Code, and Codex]() Original publisher: [Read original article]() Author: Antoine van der Lee Published: 2026-09-07T13:07:15Z Content type: opinion Language: en Sources: [SwiftLee]() Topics: [iOS](), [cursor](), [Claude Code](), [codex](), [App](), [Tooling]() Tags: [agent](), [agent-skills](), [ai-development](), [app-development](), [claude-code](), [codex](), [cursor](), [developer-tools](), [ios]() ### AI overview An opinion article examines how the iOS Simulator is becoming integrated into Cursor, Claude Code, and Codex as app development shifts toward orchestrating AI agents. It argues that visual testing, performance review, and critical human validation remain essential, and describes AI Agents for the iOS Simulator as a way to automate navigation and validation within the developer workflow. ### Source excerpt App development is changing, and the iOS Simulator is too, as it starts to appear in Cursor, Claude Code, and Codex in different ways. I've been developing apps since 2009 and the RocketSim developer tool since 2019, and I can tell we're reinventing ourselves like never before. I also started to wonder: what is the ... -> The post The iOS Simulator Inside Cursor, Claude Code, and Codex appeared first on SwiftLee. ## Cursor Cloud Agents can now run in Vercel Sandbox DevFeed: [Cursor Cloud Agents can now run in Vercel Sandbox]() Original publisher: [Read original article]() Author: Allen Zhou Published: 2026-09-03T15:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [cursor](), [Vercel](), [Agent Harness](), [Firecracker]() Tags: [agents](), [apis](), [architecture](), [cursor](), [enterprise](), [firecracker](), [guide](), [sandbox](), [scale](), [vercel](), [virtual-machines](), [workflows]() ### AI overview Cursor Cloud Agents can run in Vercel Sandbox, using isolated Firecracker microVMs as their execution environment. The architecture combines Cursor's agent harness and inference loop with Vercel Functions and Workflows for durable request handling, worker provisioning, monitoring, retries, cleanup, and short-lived user-scoped credentials. ### Source excerpt Cursor Cloud Agents can now run in Vercel Sandbox instead of Cursor's hosted machines. Cursor manages the agent harness and inference loop. Its Self-Hosted Machines APIs let you supply the execution environment where agents clone repositories, edit files, and run commands and tests. Self-Hosted Machines requires a Cursor Enterprise plan. Vercel Sandbox provides that execution environment as an isolated Firecracker microVM for each agent request. Vercel Functions and Vercel Workflows form a durable control plane that claims queued agent requests, provisions workers, monitors sessions, and cleans up automatically. With this architecture, you get: A scale-to-zero worker pool without long-lived virtual machines A dedicated, isolated Sandbox for every agent request Durable retries when a worker or session fails Short-lived, user-scoped credentials inside each Sandbox Follow the step-by-step guide to deploy the reference implementation to your own Vercel account, or learn more in the Vercel Sandbox documentation. Read more ## Build and run Datadog workflows from Bits Chat or AI agents DevFeed: [Build and run Datadog workflows from Bits Chat or AI agents]() Original publisher: [Read original article]() Author: Neha Haresh; Gabriel Margolis; Brianna Wang; David Robert-Ansart Published: 2026-09-03T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Bots](), [cursor](), [incident]() Tags: [ai](), [ai-agents](), [ai-coding](), [bits-ai](), [claude-code](), [codex](), [cursor](), [debug](), [incident-management](), [mcp](), [workflow-automation](), [workflows]() ### AI overview Datadog describes using Bits Chat and AI coding agents to create, run, and debug automated workflows with Datadog and development context. ### Source excerpt Build, debug, and run Datadog workflows from Bits Chat and AI coding agents using the operational and development context where you're working. ## Encore now works with Entire DevFeed: [Encore now works with Entire]() Original publisher: [Read original article]() Author: Ivan Cernja Published: 2026-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Encore Updates]() Topics: [AI-assisted coding](), [codex](), [Claude Code](), [coding](), [Git](), [cursor](), [PostgreSQL]() Tags: [claude-code](), [codex](), [coding](), [coding-agents](), [cursor](), [git](), [object-storage](), [postgresql]() ### AI overview Encore now works with Entire, allowing developers to use Codex, Claude Code, Gemini, and Cursor in Encore projects while recording agent sessions in Git and linking them to commits. The article demonstrates building and testing an image service with local PostgreSQL and object storage, including integration tests and a live upload/download verification. ### Source excerpt Keep the agent session behind every Encore change, directly in Git. ## Our decision on Cursor following its acquisition by SpaceX DevFeed: [Our decision on Cursor following its acquisition by SpaceX]() Original publisher: [Read original article]() Published: 2026-08-28T06:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [cursor]() Tags: [acquisition](), [ai](), [company](), [compliance](), [cursor](), [developers](), [models](), [openai](), [safety](), [spacex](), [support]() ### AI overview OpenAI says it plans to wind down its contract to provide models through Cursor after Cursor's acquisition by SpaceX, citing concerns about compliance with its terms of service. The proposed shutoff date is November 12, 2026, and OpenAI says it will support affected developers during the transition. ### Source excerpt Our decision to wind down our contract providing OpenAI models to Cursor following its acquisition by SpaceX. ## Cursor is now available in the AI SDK harness layer DevFeed: [Cursor is now available in the AI SDK harness layer]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-08-27T14:47:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [cursor]() Tags: [agent](), [agents](), [ai](), [code](), [codex](), [coding](), [cursor]() ### AI overview The AI SDK harness layer adds official Cursor support through an adapter. Applications can run Cursor and other coding agents through the shared HarnessAgent interface without changing application code. ### Source excerpt The AI SDK harness layer now supports Cursor through the official @ai-sdk/harness-cursor adapter. The harness layer lets your application run different coding agents through the same HarnessAgent interface, so you can switch agents without changing your application code. Pass cursor to HarnessAgent: Under the hood, the adapter uses @ai-sdk/harness-acp to connect Cursor to HarnessAgent through the Agent Client Protocol (ACP). Supported harnesses now include, in addition to Cursor, Claude Code, Cline, Codex, Deep Agents, Grok Build, OpenCode, and Pi, with more coming soon. Read the Cursor harness documentation to get started. Read more ## How Srini Raghavan helped $3.4B SaaS Giant Freshworks Embrace the AI PDLC DevFeed: [How Srini Raghavan helped $3.4B SaaS Giant Freshworks Embrace the AI PDLC]() Original publisher: [Read original article]() Author: Aakash Gupta Published: 2026-08-24T23:16:09Z Content type: article Language: en Sources: [Product Growth]() Topics: [Software as a service](), [AI Agent](), [cursor](), [Design system](), [context](), [repo]() Tags: [ai](), [ai-agent](), [context](), [cursor](), [design-system](), [repo](), [saas]() ### AI overview The article summarizes how Freshworks moved from a six-month release process to a two-week cycle under Chief Product Officer Srini Raghavan. It describes an AI product development lifecycle built on structured data, a parsable design system, documented coding standards, a single source repository, contextual knowledge hubs, reusable AI builder artifacts, governed AI agents, and an evaluation phase. ### Source excerpt + Why he uses Grok models, and the future of the "Product Builder" role ## 🎙 How I AI: Grok Bot + Grok 4.6--what's great (and what's still hype) & Lessons from spending $20,000 on Devin in one month DevFeed: [🎙 How I AI: Grok Bot + Grok 4.6--what's great (and what's still hype) & Lessons from spending $20,000 on Devin in one month]() Original publisher: [Read original article]() Author: Lenny Rachitsky Published: 2026-08-24T15:02:23Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [Artificial Intelligence](), [Bot](), [cursor](), [OpenClaw](), [Claude](), [Frontier Model](), [GitHub](), [email](), [Slack]() Tags: [agent](), [ai](), [claude](), [cursor](), [frontier-model](), [github](), [openclaw](), [podcast]() ### AI overview This solo podcast episode evaluates Grok Bot, Cursor Origin, and Grok 4.6. It finds Grok Bot's multi-account connectors particularly useful, describes its simplicity as both a strength and a limitation, considers Cursor Origin promising but not yet a strong replacement for GitHub, and reports that Grok 4.6 performed competitively in the presenter's blind evaluations. The episode also favors Claude Sonnet 5 for concise, responsive agent conversations. ### Source excerpt Your weekly listens from How I AI, part of the Lenny's Podcast Network ## Remote Control for Google Antigravity: Drive Your AI Coding Agent From Telegram DevFeed: [Remote Control for Google Antigravity: Drive Your AI Coding Agent From Telegram ]() Original publisher: [Read original article]() Author: Nicola Guglielmi Published: 2026-08-21T12:12:57Z Content type: tutorial Language: en Sources: [Google Developer Experts - Medium]() Topics: [google-antigravity](), [MCP Server](), [cursor](), [Claude Code](), [Terminal](), [Code]() Tags: [agent](), [ai](), [ai-agent](), [ai-coding](), [antigravity](), [coding](), [google-antigravity](), [mcp](), [mcp-server](), [telegram-bot](), [terminal](), [vibe-coding]() ### AI overview This tutorial introduces Telegravity, a single-binary MCP server that connects Telegram with AI coding agents such as Google Antigravity, Claude Code, and Cursor. It describes remote instructions, live status, conversation history, workspace selection, and an active mode for reacting to Telegram messages. ### Source excerpt Your agent runs for 20 minutes. You walk away from the laptop. What if your phone became your mission control? We are living a strange new moment in the software industry. We kick off an AI coding agent: Antigravity, Claude Code, Cursor, give it a task, and then... we sit there. Watching a terminal. Babysitting a process that might run for two minutes or for two hours. That always felt wrong to me. The whole promise of an autonomous agent is that it works while you live your life. But the moment you stand up to grab a coffee, you go blind: you can't see what it's doing, you can't nudge it, you can't say "wait, not that file" until you're back at the keyboard. So I built the missing piece I needed. I call the project Telegravity, the uplink between Telegram and my AI coding agent. In this article I want to show how it turns Antigravity into something you can drive remotely, from the same chat app you already check fifty times a day. Let's launch. 🚀 https://github.com/nicolaguglielmi/Telegravity The idea explained in one sentence Telegravity is a single-binary MCP server that exposes a tiny set of tools to your agent, pull instructions, post live status, stream conversation history, while the Telegram side gives you a polished dashboard, a conversation hub, and an Active Mode that wakes the agent the instant you type. That's it. One process. No cloud service in the middle, no extra account, no telemetry. Your bot token never leaves your machine. End to end, the whole conversation stays private. The magic is that it speaks the Model Context Protocol (MCP), so it doesn't care which agent you use. Antigravity is a first-class citizen, but the exact same setup works for Claude Code, Cursor, Cline, or anything else that speaks MCP. What you actually get Before the setup, here's the payoff, so you know what we're building toward: A live dashboard with an agent heartbeat: 💭 Thinking - ⚡ Executing - ✅ Done an unread inbox counter, the current workspace, and a chat-mode badge. A ## Cursor Origin vs GitHub: What changes for developers DevFeed: [Cursor Origin vs GitHub: What changes for developers]() Original publisher: [Read original article]() Author: Aditya Oberai Published: 2026-08-18T00:00:00Z Content type: comparison Language: en Sources: [Appwrite Blog]() Topics: [cursor](), [GitHub](), [pull-requests](), [AI-assisted coding](), [hosting](), [Development]() Tags: [ai-assisted-coding](), [coding](), [comparisons](), [cursor](), [cursor-origin](), [development](), [github](), [hosting](), [pull-requests](), [workflow]() ### AI overview This comparison explains how Cursor Origin, an early-beta code hosting platform built into Cursor, differs from GitHub and what it changes for developers. Origin combines repositories, pull requests, code browsing, GitHub sync, and agent workflows in one editor, but initially targets paid Cursor accounts and is not positioned as an immediate replacement for GitHub. ### Source excerpt Cursor Origin vs GitHub: how Cursor's new code hosting handles repos, pull requests, and GitHub sync, and what actually changes in your daily workflow. ## Cursor Origin review: An engineer's perspective DevFeed: [Cursor Origin review: An engineer's perspective]() Original publisher: [Read original article]() Author: Matej Bačo Published: 2026-08-18T00:00:00Z Content type: opinion Language: en Sources: [Appwrite Blog]() Topics: [cursor origin](), [cursor](), [Git](), [GitHub](), [pull-requests](), [Command-line interface]() Tags: [ai](), [cli](), [cursor](), [cursor-origin](), [git](), [github](), [pull-request](), [review](), [switching]() ### AI overview A review of Cursor Origin, Cursor's Git hosting service, examines its repository, code browsing, search, pull request, and GitHub mirroring features. It finds that core repository and pull request workflows work, while account switching, repository creation flows, and repository management remain rough in the early beta. ### Source excerpt A detailed review of Cursor Origin, covering Git hosting, GitHub sync, cloud agents, current limitations, and whether it's worth switching. ## Stop burning tokens on code review DevFeed: [Stop burning tokens on code review]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-08-15T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [Code review](), [Claude Code](), [Code](), [GitHub Actions](), [Architecture & Design](), [cursor]() Tags: [agents](), [claude-code](), [code](), [code-review](), [cursor](), [engineering](), [github-actions](), [security]() ### AI overview The author argues that custom linters can provide fast, inexpensive guardrails and feedback loops for both human and agent-written code. They describe mixed experiences with Cursor's BugBot and Claude code review skills, especially the high noise and review burden produced when those skills run in GitHub Actions. ### Source excerpt I've been experimenting with different approaches to build a system where humans and agents can ship fast safely. Think I've found something that works - custom linters. ## What We Learned by Reproducing 2,200 papers from ICML DevFeed: [What We Learned by Reproducing 2,200 papers from ICML]() Original publisher: [Read original article]() Author: Abubakar Abid Published: 2026-08-13T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [AI research agents](), [AI-assisted coding](), [Human-AI evaluation](), [Claude Code](), [codex](), [cursor](), [Open Source]() Tags: [2026](), [agents](), [ai-agents](), [ai-research](), [claude-code](), [codex](), [community](), [cursor](), [open-source](), [research](), [science]() ### AI overview The article reports lessons from the ICML 2026 Open Reproductions challenge, in which the community used coding agents to reproduce research papers at scale. It discusses how agents can read papers, write code, run experiments, and report findings, while examining the continuing role of human oversight in AI research reproducibility. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Introducing the Port plugin for coding agents DevFeed: [Introducing the Port plugin for coding agents]() Original publisher: [Read original article]() Author: Matan Grady Published: 2026-08-11T17:29:31Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [AI-assisted coding](), [MCP](), [MCP Server](), [Claude Code](), [cursor](), [codex](), [pull-requests](), [Kubernetes]() Tags: [agents](), [automation](), [claude-code](), [codex](), [coding-agents](), [copilot](), [cursor](), [deployment](), [kubernetes](), [mcp](), [mcp-server](), [pull-requests]() ### AI overview Port introduces a plugin for coding agents that packages Port Skills and connects an up-to-date Port MCP server. The plugin gives Claude Code, Cursor, Codex, Copilot, and other coding agents guidance for using Port, reducing repeated tool experimentation and context usage while applying Port's best practices. Examples include building Kubernetes pod self-healing workflows, extending blueprints with deployment-frequency data, and creating ticket-resolution flows that turn Jira tickets into pull requests. ### Source excerpt Give your coding agent the context to work with Port: install the official Port plugin. ## Advancing AI fluency at Capital One DevFeed: [Advancing AI fluency at Capital One]() Original publisher: [Read original article]() Author: Capital One Tech Published: 2026-08-11T15:12:03Z Content type: opinion Language: en Sources: [Capital One Tech]() Topics: [Artificial Intelligence](), [AI Development](), [Development](), [cursor](), [Learning](), [Cloud]() Tags: [ai](), [ai-coding](), [ai-machine-learning](), [aifluency](), [cloud](), [developers](), [development](), [learning](), [software-development]() ### AI overview Capital One describes making AI fluency an enterprise-wide capability, including an AI learning hub for more than 60,000 associates and training for foundational literacy, advanced workflows, and specialized tools. The article also discusses AI coding tools and their role in helping engineers focus on architecture, complex systems thinking, and creative problem-solving. ### Source excerpt Capital One is raising the bar on AI fluency by making it a fundamental part of how we operate. At Capital One, we sought early on to operate like a bank that a technology company would build--modernizing our data ecosystem, going all in on the cloud and building an in-house engineering workforce. That deep investment has set us up to thrive with AI at enterprise scale today. As we continue to build at the forefront of technology and AI, sustaining an edge requires more than just deploying off-the-shelf models. Because at Capital One, we don't just use AI--we build AI. Delivering proprietary AI solutions across the enterprise requires investing deeply in the people who architect, customize and build with them. That's why our enterprise-wide emphasis on AI fluency isn't an ad-hoc training program. It is a fundamental part of how we operate, innovate and push the boundaries of what's possible for our business and our more than 100 million customers. AI skill building at enterprise scale Building on nearly a decade of insights from internal learning platforms and initiatives like Tech College--which offers hundreds of courses and offerings on topics like AI, machine learning, data, cloud engineering and beyond--this year we launched a dynamic, enterprise-wide AI learning hub to over 60,000 Capital One associates. More than a static content library, the platform meets associates where they are, whether that means building foundational AI literacy, mastering advanced workflows or getting training for specialized tools purpose-fit for their domains. We believe AI fluency shouldn't be treated as a side-of-desk exercise or an isolated science project; it must be a shared capability across the entire company. This is especially true for our engineers and developers. AI coding tools have redefined what high-performance software development looks like. By leveraging advanced AI capabilities to help streamline "run-the-engine" tasks, our engineers are more free to focus on complex ## Why every engineering org needs an agentic registry DevFeed: [Why every engineering org needs an agentic registry]() Original publisher: [Read original article]() Author: Matar Peles Published: 2026-08-10T11:43:10Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Agent Skill](), [MCP](), [cursor](), [Azure](), [bedrock](), [site-reliability-engineering]() Tags: [agent-skill](), [agentic](), [agents](), [azure](), [bedrock](), [coding](), [governance](), [mcp](), [slack](), [workflows]() ### AI overview The article argues that engineering organizations need an agentic registry to manage the rapid growth of agents and skills. It describes registries for SKILL.md files, deployed agents, and approved MCP servers, with capabilities for discovery, standardization, governance, and workflow composition. ### Source excerpt Why every engineering org needs an agentic registry ## AI Native Software Development: 5 Radical Team Decisions Now DevFeed: [AI Native Software Development: 5 Radical Team Decisions Now]() Original publisher: [Read original article]() Author: Zohar Einy Published: 2026-08-10T11:33:22Z Content type: opinion Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Artificial Intelligence](), [AI Development](), [ai-coding](), [Claude Code](), [cursor](), [GitHub Copilot](), [Terminal](), [Command-line interface](), [Prompt Engineering](), [sdlc](), [FIRST]() Tags: [ai](), [ai-coding](), [claude-code](), [coinbase](), [copilot](), [cursor](), [prompt-engineering](), [software-development](), [terminal](), [workflow]() ### AI overview The article argues that AI-native software development requires redesigning an organization around AI-assisted coding rather than merely purchasing tools. It introduces five team decisions, including no-IDE weeks, AI-focused hiring, platform engineering, and an agentic software development lifecycle; the supplied text details the no-IDE experiment and begins the discussion of measuring AI usage through leaderboards and velocity. ### Source excerpt The 5 team decisions that make you AI native software development: no-IDE weeks, AI hiring, platform engineers, agentic SDLC. ## Track Cursor and Copilot Adoption with a Live Port Dashboard DevFeed: [Track Cursor and Copilot Adoption with a Live Port Dashboard]() Original publisher: [Read original article]() Author: John Crowley Published: 2026-08-10T11:31:18Z Content type: tutorial Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [cursor](), [GitHub Copilot](), [Pull Request](), [GitHub](), [Automation](), [Artificial Intelligence]() Tags: [ai](), [automation](), [copilot](), [cursor](), [developer-portal](), [github](), [pull-request]() ### AI overview A Port walkthrough shows how to build a live dashboard for Cursor and GitHub Copilot adoption, costs, usage, and delivery impact. ### Source excerpt See who actually uses Cursor and Copilot, what it costs, and how it changes delivery, with a live adoption dashboard in Port. ## Cursor Usage Data Now Flows into Port's Context Lake Platform DevFeed: [Cursor Usage Data Now Flows into Port's Context Lake Platform]() Original publisher: [Read original article]() Author: Tomasz Skora Published: 2026-08-10T11:31:03Z Content type: release Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [cursor](), [data](), [dashboards](), [ai-coding](), [systems]() Tags: [ai](), [ai-coding](), [cost](), [cursor](), [dashboards](), [data](), [governance](), [integration](), [workflow](), [workflows]() ### AI overview Port can now sync Cursor usage data into its Context Lake, connecting AI coding activity with teams, services, ownership, delivery, reliability, quality, and operational data. The integration supports adoption analysis, license and spend governance, dashboards, scorecards, and workflows. ### Source excerpt Cursor usage data now syncs into Port's Context Lake, joining the teams, ownership, and delivery data you already track in Port. [Next page]()