# Claude code Published articles for Claude code. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## sem-ai 0.4.0: smaller responses, safer access, and pre-flight checks DevFeed: [sem-ai 0.4.0: smaller responses, safer access, and pre-flight checks]() Original publisher: [Read original article]() Author: Pete Miloravac Published: 2026-09-16T12:01:04Z Content type: release Language: en Sources: [Semaphore Engineering]() Topics: [AI-assisted coding](), [Claude Code](), [Command-line interface](), [Authorization](), [API](), [configuration]() Tags: [ai-coding-agents](), [api](), [audio](), [claude-code](), [command-line](), [configuration](), [permissions](), [pipelines](), [product-news](), [release](), [video]() ### AI overview Semaphore's sem-ai 0.4.0 release adds more compact workflow and pipeline responses, context switching across organizations and credentials, and support for managing pre-flight checks. The update is aimed at reducing context usage and enabling more targeted permissions for AI coding agents. ### Source excerpt AI coding agents work best when they receive the right information without unnecessary noise. They also need clearly defined permissions and reliable safeguards for the changes they make. sem-ai 0.4.0 improves all three areas. The release introduces more compact pipeline responses, flexible context switching, and support for Semaphore pre-flight checks. Watch Nick demonstrate the new [...] The post sem-ai 0.4.0: smaller responses, safer access, and pre-flight checks appeared first on Semaphore. ## DuckDB Skills for Claude Code DevFeed: [DuckDB Skills for Claude Code]() Original publisher: [Read original article]() Author: The DuckDB team Published: 2026-09-16T00:00:00Z Content type: tutorial Language: en Sources: [DuckDB]() Topics: [DuckDB](), [Claude Code](), [Command-line interface](), [data](), [CSV](), [parquet]() Tags: [claude-code](), [cli](), [csv](), [data](), [duckdb](), [parquet](), [using-duckdb]() ### AI overview This post introduces the duckdb-skills plugin for Claude Code. The plugin uses the DuckDB CLI to inspect data files, run SQL queries, convert formats, explore object storage and spatial data, search documentation, and recall earlier sessions. It explains installation, how the skills select appropriate commands, and how Claude uses DuckDB for exact query results. ### Source excerpt The duckdb-skills plugin gives Claude Code a growing number of skills that use the DuckDB CLI to read data files, run queries, convert formats, explore object storage, work with spatial data, search the documentation and recall earlier sessions. ## Build with Claude Code: Enrollment for a Two-Day Cohort Course DevFeed: [Build with Claude Code: Enrollment for a Two-Day Cohort Course]() Original publisher: [Read original article]() Author: ByteByteGo Published: 2026-09-15T19:31:01Z Content type: article Language: en Sources: [ByteByteGo]() Topics: [Claude Code](), [Development](), [Code](), [Git]() Tags: [build](), [claude-code](), [code](), [development](), [git](), [hooks](), [how-to](), [learn](), [mcps](), [parallel]() ### AI overview The article announces the relaunch of Build with Claude Code, a two-day cohort-based course taught by John Kim. It covers Claude Code fundamentals and production workflows, including context engineering, memory, Skills, MCPs, hooks, Git worktrees, subagents, and agent teams. ### Source excerpt We're relaunching Build with Claude Code, a 2-day intensive cohort-based course taught by John Kim, who has trained hundreds of engineers at Meta to use Claude Code in real production workflows. ## 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. ## 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. ## AI's best coding agent fails 60% of the time -- and the data backs it up DevFeed: [AI's best coding agent fails 60% of the time -- and the data backs it up]() Original publisher: [Read original article]() Author: Amanda Caswell Published: 2026-09-14T22:22:27Z Content type: news Language: en Sources: [The New Stack]() Topics: [Benchmark](), [AI-assisted coding](), [Fable](), [Claude Code](), [codex](), [Command-line interface](), [anthropic]() Tags: [ai](), [ai-engineering](), [ai-models](), [benchmark](), [benchmarks](), [claude-code](), [cli](), [codex](), [coding](), [fable](), [performance](), [software-testing]() ### AI overview Real-SWE evaluates coding agents on private company codebases and reports substantially lower success rates than public-repository benchmarks. Claude Fable 5.1, running through Claude Code, led the comparison with a 38.8% score, while the tested systems often failed most attempts. ### Source excerpt Claude Fable 5.1 just won a new coding benchmark despite failing more than six out of 10 times. Its 38.8% The post AI's best coding agent fails 60% of the time -- and the data backs it up appeared first on The New Stack. ## AI SDK harness layer now supports native subscription authentication DevFeed: [AI SDK harness layer now supports native subscription authentication]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-09-14T21:28:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [Authentication](), [OAuth](), [codex](), [Claude Code]() Tags: [ai](), [authentication](), [claude-code](), [codex](), [coding-agents](), [copilot](), [cursor](), [gateway](), [oauth](), [opencode](), [sdk]() ### AI overview The AI SDK harness layer now supports authenticating supported coding-agent harnesses through their native subscriptions. It uses explicit provider credentials when available, otherwise falls back to a host-native subscription without requiring code or configuration changes. ### Source excerpt The AI SDK harness layer now supports authenticating harnesses through their native subscriptions, where the underlying harness supports them. The harness layer runs different coding agents through the same HarnessAgent interface, so you can switch agents without changing your application code. No code changes or new settings are required. The direct authentication mode uses explicit provider environment credentials when they are present, and otherwise a native subscription found on the host. The default auto mode does the same when no AI Gateway credentials are set. The ai-gateway mode never reads native subscriptions. Native subscription credentials stay on the host. Just like with API keys, credentials are resolved at the host boundary. OAuth access tokens are refreshed there as needed. Where the sandbox supports it, the harness receives placeholder credentials and the real token is injected into outbound requests on the host. Native subscriptions work across harness adapters wherever the harness itself supports subscription login. These include Claude Code, Cline, Codex, Cursor, fx, GitHub Copilot, Grok Build, OpenCode, and Pi. Read the harness documentation to learn more. Read more ## Manage end-user OAuth consent for AI agents with Amazon Bedrock AgentCore DevFeed: [Manage end-user OAuth consent for AI agents with Amazon Bedrock AgentCore]() Original publisher: [Read original article]() Author: Swara Gandhi Published: 2026-09-14T20:35:45Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [Amazon Bedrock AgentCore](), [OAuth](), [Amazon Web Services](), [AWS CloudTrail](), [GitHub](), [Slack](), [Model Context Protocol](), [ide]() Tags: [amazon-bedrock](), [amazon-bedrock-agentcore](), [announcements](), [aws](), [aws-cloudtrail](), [claude-code](), [cursor](), [github](), [intermediate-200](), [kiro](), [model-context-protocol](), [oauth](), [slack](), [visual-studio-code]() ### AI overview This tutorial explains how Amazon Bedrock AgentCore Identity's Consent portal manages end-user OAuth consent and session binding for AI agents. It covers configuring GitHub and Slack targets through an AgentCore Gateway, storing user tokens, supporting IDE and MCP clients, and reviewing activity in AWS CloudTrail. ### Source excerpt Amazon Bedrock AgentCore Identity now offers a Consent portal, a managed web experience and session binding endpoint for AgentCore Gateway. This post walks through provisioning a portal, configuring GitHub and Slack 3LO targets, and the end-user consent flow, and shows how to review activity in AWS CloudTrail. ## Inside the LLM Call: GenAI Observability with OpenTelemetry DevFeed: [Inside the LLM Call: GenAI Observability with OpenTelemetry]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-09-14T16:56:42Z Content type: tutorial Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [agent observability](), [telemetry](), [AI Agent](), [Large Language Model]() Tags: [agent](), [ai-agent](), [claude-code](), [codex](), [observability](), [opentelemetry](), [token](), [tool](), [visibility]() ### AI overview This tutorial explains how OpenTelemetry Semantic Conventions for Generative AI record LLM calls, tool invocations, token counts, and related events. It demonstrates exporting telemetry from an LLM-powered application, viewing it with Aspire Dashboard, and considering sensitive-data implications of optional content capture. ### Source excerpt Your AI agent just took 45 seconds to answer a simple question. Was it the model? A slow tool call? A retry loop? Every time an application calls an LLM, a chain of model calls, tool invocations, and token exchanges happens behind the scenes -- and without observability, you are guessing. The OpenTelemetry Semantic Conventions for Generative AI give you that visibility. They standardize how GenAI operations are recorded -- the model being called, input and output token counts, and when opted in, the full content of prompts, completions, tool calls, and tool results. ## 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. ## How I Used a Pinterest Board to Get Better Visual Results From Claude Design DevFeed: [How I Used a Pinterest Board to Get Better Visual Results From Claude Design]() Original publisher: [Read original article]() Author: Sydney Cole Published: 2026-09-13T12:00:33Z Content type: tutorial Language: en Sources: [Atomic Object]() Topics: [Claude](), [Artificial Intelligence](), [Claude Code](), [Code](), [Website]() Tags: [ai](), [ai-design-tools](), [ai-for-designers](), [claude](), [claude-code](), [code](), [design](), [how-to](), [html](), [images](), [iteration](), [pinterest](), [portfolio](), [prompt](), [website]() ### AI overview An account of using a Pinterest mood board as a visual reference for Claude Design when creating a creative portfolio website. The author reports that the image references produced less generic layouts and helped clarify the intended aesthetic; Claude Code then generated a basic HTML site based on the design. ### Source excerpt I've been building out a portfolio site for my creative work. While I have hesitations about mixing AI with my art, I decided to use this website as an opportunity to try out Claude Design. Like most people who've tried generating a design with AI, I ran into the same issue over and over. I'd [...] The post How I Used a Pinterest Board to Get Better Visual Results From Claude Design appeared first on Atomic Spin. ## Boris Cherny on guardrails for Claude-written production code DevFeed: [Boris Cherny on guardrails for Claude-written production code]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-11T17:47:11Z Content type: opinion Language: en Sources: [Simon Willison's Weblog]() Topics: [Claude](), [anthropic](), [AI-assisted coding](), [Security]() Tags: [agentic-engineering](), [agentic-engineering-63](), [ai](), [ai-2-236](), [ai-assisted-programming](), [ai-assisted-programming-407](), [anthropic](), [anthropic-336](), [boris-cherny](), [boris-cherny-4](), [claude](), [claude-310](), [claude-code](), [claude-code-127](), [coding-agents](), [coding-agents-248](), [generative-ai](), [generative-ai-1-982](), [llms](), [llms-1-948](), [security]() ### AI overview Boris Cherny says production code written by Claude should meet a higher standard than human-written code. He describes Anthropic's guardrails, including lint rules, tests, Claude-driven end-to-end tests, daily Claude-powered fuzzing, automated code and security reviews, and automated refactoring. ### Source excerpt Production code written by Claude should have a higher bar than if it was written by a human. At Anthropic, we have many guardrails in place to make sure this is happening: lots of lint rules, lots of tests, Claude-driven end to end tests, Claude-powered fuzzers running daily, automated code reviews and security reviews, automated code refactoring, and so on. Without these, you can end up with a mess that is hard to maintain down the line. -- Boris Cherny Tags: claude, ai, claude-code, llms, coding-agents, ai-assisted-programming, generative-ai, agentic-engineering, boris-cherny, anthropic ## Learn Claude Code, evals, AI systems, and more: ByteByteGo Live is here DevFeed: [Learn Claude Code, evals, AI systems, and more: ByteByteGo Live is here]() Original publisher: [Read original article]() Author: ByteByteGo Published: 2026-09-11T15:32:16Z Content type: release Language: en Sources: [ByteByteGo]() Topics: [Artificial Intelligence](), [Claude Code](), [AI Development](), [AI Engineering]() Tags: [ai](), [ai-development](), [ai-engineering](), [ai-evals](), [claude-code](), [development]() ### AI overview ByteByteGo announces ByteByteGo Live, a membership offering live courses on Claude Code, production AI systems, AI engineering, AI evaluations, cost optimization, and related topics. The announcement cites higher completion rates for live cohorts and says the membership covers courses offered over the next 12 months. ### Source excerpt Most online courses never get finished (~4% completion). Live cohorts get ~40%, roughly 10x higher. Live courses are the only courses people actually finish. So we're launching ByteByteGo Live. ## What Is an Agent Harness? The Architecture Behind Claude Code, DeepSeek Harness, and Hermes Agent DevFeed: [What Is an Agent Harness? The Architecture Behind Claude Code, DeepSeek Harness, and Hermes Agent]() Original publisher: [Read original article]() Author: Rudrendu Paul Published: 2026-09-11T15:07:18Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [AI Bots](), [AI-assisted coding]() Tags: [agent](), [ai-agents](), [architecture](), [artificial-intelligence](), [claude-code](), [deepseek](), [developer-tools](), [llm](), [machine-learning](), [mcp](), [memory](), [python](), [sandbox](), [software-engineering](), [tools]() ### AI overview An explainer and hands-on guide to agent harnesses: the runtime infrastructure around an LLM that manages model calls, tool execution, memory, and filesystem sandboxing. It compares popular harnesses and introduces a small Python implementation. ### Source excerpt On August 13, 2026, DeepSeek published a GitHub repository called deepseek-harness. Within two days, it had passed 95,386 stars and 8,826 forks (a vanity metric on its own, but a spike this fast signa ## GitHub Copilot is now available in the AI SDK harness layer DevFeed: [GitHub Copilot is now available in the AI SDK harness layer]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-09-10T17:39:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [GitHub Copilot](), [vercel ai sdk](), [AI-assisted coding](), [cursor]() Tags: [agent](), [ai](), [claude](), [claude-code](), [code](), [codex](), [coding](), [copilot](), [cursor](), [github](), [github-copilot]() ### AI overview The AI SDK harness layer adds official GitHub Copilot support through an adapter, allowing applications to run Copilot and other coding agents through the same HarnessAgent interface. ### Source excerpt The AI SDK harness layer now supports GitHub Copilot through the official @ai-sdk/harness-github-copilot 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 githubCopilot to HarnessAgent: Under the hood, the adapter uses @ai-sdk/harness-acp to connect GitHub Copilot to HarnessAgent through the Agent Client Protocol (ACP). Supported harnesses now include, in addition to GitHub Copilot, Claude Code, Cline, Codex, Cursor, Deep Agents, fx, Grok Build, OpenCode, and Pi, with more coming soon. Read the GitHub Copilot harness documentation to get started. Read more ## Fable 5.1 vs. Fable 5: Results on a real-world budget, not the spec sheet DevFeed: [Fable 5.1 vs. Fable 5: Results on a real-world budget, not the spec sheet]() Original publisher: [Read original article]() Author: Jessica Wachtel Published: 2026-09-10T14:00:00Z Content type: comparison Language: en Sources: [The New Stack]() Topics: [Claude](), [anthropic](), [Command-line interface]() Tags: [ai-engineering](), [ai-models](), [anthropic](), [benchmark](), [claude](), [claude-code](), [large-language-models](), [science]() ### AI overview The article compares Claude Fable 5.1 and Fable 5 on five Terminal-Bench-Science tasks under a $12, 60-turn limit per test. It contrasts these constrained runs with Anthropic's published benchmark score and higher-cost leaderboard testing. ### Source excerpt When Anthropic launched Claude Fable 5.1 this month, it centered the announcement around one benchmark result: its Terminal-Bench-Science score. In The post Fable 5.1 vs. Fable 5: Results on a real-world budget, not the spec sheet appeared first on The New Stack. ## From token consumer to token provider: Building your org's AI API DevFeed: [From token consumer to token provider: Building your org's AI API]() Original publisher: [Read original article]() Author: Markell Rawls Published: 2026-09-10T13:01:50Z Content type: tutorial Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Artificial Intelligence](), [API](), [API keys](), [AI Infrastructure](), [Security](), [NVIDIA DGX](), [vllm](), [Claude Code](), [hugging face](), [anthropic](), [OpenAI]() Tags: [ai](), [ai-inference](), [ai-infrastructure](), [api](), [api-keys](), [claude](), [claude-code](), [developer](), [gpu](), [hugging-face](), [openai](), [security](), [vllm]() ### AI overview The article describes how organizations can move from independently purchasing AI-provider access and distributing API keys toward centrally managing AI infrastructure and providing internal AI APIs. It highlights rising token costs, fragmented workloads, limited visibility, and security-audit difficulties. ### Source excerpt One of the biggest problems with AI right now is that it's expensive. If you've been anywhere near an enterprise IT budget in the last 2 years, then you already know that. Most companies that wanted to get AI into their workflows did the same thing: They signed up for a business account with an AI provider, handed out API keys, and started building. It made sense at the time because the models were good, the APIs were simple, and the alternative was standing up your own inference infrastructure, which nobody had bandwidth for. But then the bills started coming in. The post From token consumer to token provider: Building your org's AI API appeared first on Red Hat Developer. ## 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. ## Claude performed best on a new benchmark for 'agents that build agents'. But it passed fewer than a quarter of the tests. DevFeed: [Claude performed best on a new benchmark for 'agents that build agents'. But it passed fewer than a quarter of the tests.]() Original publisher: [Read original article]() Author: Paul Sawers Published: 2026-09-09T20:14:09Z Content type: news Language: en Sources: [The New Stack]() Topics: [Claude](), [coding](), [anthropic](), [Software]() Tags: [agents](), [ai](), [ai-agents](), [ai-engineering](), [ai-models](), [benchmark](), [claude](), [claude-code](), [codex](), [coding](), [large-language-models](), [leaderboard](), [testing]() ### AI overview Hyper-𝜏-bench evaluates whether AI developer agents can build customer-service agents from simulated business materials. Claude Opus 5 in Claude Code led the six tested configurations at 23.9%, while none exceeded 25%. ### Source excerpt AI models now power all manner of agents, from coding assistants that write and debug software to customer service systems The post Claude performed best on a new benchmark for 'agents that build agents'. But it passed fewer than a quarter of the tests. appeared first on The New Stack. ## Spring Tools 5.4.0 released DevFeed: [Spring Tools 5.4.0 released]() Original publisher: [Read original article]() Author: martinlippert Published: 2026-09-09T00:00:00Z Content type: release Language: en Sources: [Spring]() Topics: [releases](), [Claude](), [Model Context Protocol](), [Visual Studio Code]() Tags: [batch](), [boot](), [claude](), [claude-code](), [cloud](), [event-driven](), [java](), [mcp](), [microservices](), [performance](), [reactive](), [release](), [release-notes](), [serverless](), [spring](), [tools](), [updates](), [validation](), [web-applications]() ### AI overview Spring Tools 5.4.0 has been released for several development environments, with new validations and quick fixes, Claude Code and MCP enhancements, and stability and performance improvements. ### Source excerpt On behalf of the team and everyone who has contributed, I am pleased to announce the 5.4.0 release of the Spring Tools for Visual Studio Code, Cursor, Eclipse, Theia - and Claude Code. Hightlights New Validations & Quick Fixes: Added validations and quick fixes to convert to @ApplicationModuleListener, @SpringJUnitConfig, @RestController, and specific @Scope annotations Claude Code / MCP Enhancements: Enabled the Claude Code plugin to render a project's logical structure Stability & Performance: Significant speedups around various quick fixes and repository-based version validation + improved reliability while indexing source code Updates to the Spring Tools for Eclipse distribution updated to the latest Eclipse 2026-09 release (new and noteworthy) Detailed changes can be found in the release notes: https://github.com/spring-projects/spring-tools/releases/tag/5.4.0.RELEASE Downloads To download the distribution for Eclipse and find links to the marketplace entries for Visual Studio Code, Cursor, and Theia, please go visit: Spring Tools: https://spring.io/tools/ Next up is the 5.5.0 release, currently scheduled for mid December 2026. ## How to secure AI coding agents with permissions, approval gates, hooks, and sandboxing DevFeed: [How to secure AI coding agents with permissions, approval gates, hooks, and sandboxing]() Original publisher: [Read original article]() Author: Jeff Morhous Published: 2026-09-08T10:07:38Z Content type: tutorial Language: en Sources: [The AI-Augmented Engineer]() Topics: [Claude Code](), [agentic-coding](), [Artificial Intelligence](), [AI-assisted coding](), [coding]() Tags: [agents](), [ai](), [ai-coding-agents](), [claude-code](), [coding-agents](), [how-to](), [least-privilege](), [permissions](), [sandboxing](), [security]() ### AI overview The article explains why coding-agent instructions such as CLAUDE.md are behavioral guidance rather than enforceable security boundaries. It discusses least privilege, Claude Code permissions, approval gates, hooks, and sandboxing as technical controls for limiting agent actions. ### Source excerpt Learn how to use the principle of least privilege, Claude Code permissions, approval gates, hooks, and sandboxing to keep your agentic coding secure ## How Anthropic Uses AI in Software Engineering DevFeed: [How Anthropic Uses AI in Software Engineering]() Original publisher: [Read original article]() Author: Ryan Peterman Published: 2026-09-07T13:17:19Z Content type: opinion Language: en Sources: [The Developing Dev]() Topics: [anthropic](), [Claude Code](), [Claude](), [Software Engineering](), [Artificial Intelligence]() Tags: [ai](), [anthropic](), [claude-code](), [software-engineering](), [talk]() ### AI overview A conversation with Anthropic Claude Code engineer Thariq Shihipar about how the company uses AI models in software engineering, including onboarding, code maintenance, preventing AI-written breakages, and autonomous work. ### Source excerpt When I talk with my friends who work at Anthropic it always surprises me how far ahead they are in adopting AI within their processes and workflows. ## 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. ## Build an AI Agent (From Scratch) DevFeed: [Build an AI Agent (From Scratch)]() Original publisher: [Read original article]() Author: Nicolas Fränkel Published: 2026-09-06T00:00:00Z Content type: opinion Language: en Sources: [Nicolas Fränkel]() Topics: [AI Agent](), [Large Language Model](), [Model Context Protocol (MCP)](), [Retrieval Augmented Generation (RAG)](), [Multi Agent Systems]() Tags: [ai](), [ai-agent](), [ai-agents](), [book](), [claude-code](), [coding-assistant](), [genealogy](), [llm](), [llms](), [mcp](), [multi-agent-systems](), [rag](), [review]() ### AI overview A review of Build an AI Agent (From Scratch) by Jungjun Hur and Younghee Song describes the book's coverage of LLM agents, tool use, ReAct agents, RAG, memory, planning, code execution, multi-agent systems, and agent evaluation. The reviewer considers it a fundamental introduction, while wishing the evaluation chapter were more developed. ### Source excerpt Facts 10 chapters$29.29 (at the time of this writing)315 pages Chapters Building your first LLM agentWhat is an AI agent? [Next page]()