# Anthropic Claude Claude is an AI platform by Anthropic with an API, managed agents, and developer tools for building applications. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Prompt Caching Support in Spring AI with Anthropic Claude DevFeed: [Prompt Caching Support in Spring AI with Anthropic Claude]() Original publisher: [Read original article]() Author: Stelios Anastasakis Published: 2026-09-16T07:49:56Z Content type: tutorial Language: en Sources: [Baeldung]() Topics: [Spring AI](), [Anthropic Claude](), [Caching]() Tags: [anthropic](), [anthropic-claude](), [artificial-intelligence](), [artificial-intelligence-anthropic-spring-ai-chatclient](), [caching](), [how-to](), [spring-ai](), [spring-ai-chatclient]() ### AI overview This tutorial explains how prompt caching works in Spring AI with Anthropic Claude. It covers dependencies, model-specific requirements and limitations, configuration options, caching hierarchy, and practical considerations. Prompt caching can reduce latency and input-token costs when prompt prefixes are reused. ### Source excerpt Learn how prompt caching works, the limitations for different Claude models, and how to use it in Spring AI. The post Prompt Caching Support in Spring AI with Anthropic Claude first appeared on Baeldung. ## Claude Fable 5 access restored on AI Gateway DevFeed: [Claude Fable 5 access restored on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-07-01T07:01:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Fable](), [Anthropic Claude](), [API](), [Artificial Intelligence](), [debugging]() Tags: [anthropic-claude](), [api](), [coding](), [debugging](), [docs](), [fable](), [government](), [model](), [models](), [real-time](), [retention](), [safety]() ### AI overview Access to the Claude Fable 5 Mythos-class model has been restored on AI Gateway after the US Government lifted export controls. The release updates its safety classifiers and documents model fallbacks, API usage, and 30-day retention of prompts and completions. ### Source excerpt Access to Claude Fable 5, the Mythos-class model, has now been restored on AI Gateway following the US Government's decision to lift the export controls. Fable 5 is the same model that was available between June 9 and June 12. What has changed is the safety classifiers, which are now updated and more robust. In the near term, some routine tasks such as coding and debugging may trigger safety classifiers. To ensure requests are still serviced when the safety classifiers are triggered, use model fallbacks. AI Gateway will try each model in models in the stated order if Anthropic refuses the request to Fable 5. To call Fable 5, use model name anthropic/claude-fable-5: Model fallbacks work on every API format: for more information on how to configure these, see the docs. Anthropic does not support Zero Data Retention for the model, because some misuse patterns are only visible across cumulative requests, which real-time filters cannot catch on their own. Prompts and completions are retained for 30 days and are not used to train Claude. Read more in the data retention whitepaper. Read more ## From Figma to code in minutes: How I built UI Studio with AI DevFeed: [From Figma to code in minutes: How I built UI Studio with AI]() Original publisher: [Read original article]() Author: Jayant Kumar Published: 2026-06-18T07:01:03Z Content type: tutorial Language: en Sources: [Amex GBT Technology]() Topics: [Figma](), [ui](), [React](), [Anthropic Claude](), [Prompt Engineering](), [repo](), [Terminal]() Tags: [ai](), [anthropic-claude](), [figma](), [frontend-development](), [prompt-engineering](), [react](), [repo](), [software-development](), [terminal](), [ui](), [ui-design]() ### AI overview This tutorial explains how the author built UI Studio, a tool that generates UI code using Egencia's internal UITK React components from a prompt, a Figma URL, or a screenshot. It describes the original feasibility-checking workflow and the tool's progression from a local prototype to a deployable application. ### Source excerpt Whether you're a developer checking feasibility or a designer wanting to see your Figma come to life in real code, UI Studio is built for both. If you've ever worked on a product team, you know the dance, a designer hands over a Figma file, but before anyone writes a single line of production code, a developer has to answer one question: Is this buildable with our component library? At Egencia by Amex GBT, we use UITK (UI Toolkit), our internal component library built on React. It gives developers a set of standardized components to build consistent UIs across our products. As part of Egencia, that question kicks off a process that can take days. We open the doc site, scan the components, write some test code in the React playground or our own repo, and eventually come back to the designer with a verdict. If something isn't feasible, the design goes back for revisions. Then we check again and finally start building. It works. But it's slow. And I couldn't help but wonder whether there was a better way. The idea Earlier this year, I was doing the Anthropic Claude course and somewhere between learning about prompt engineering and working through the hands-on labs, it clicked. What if I could skip the whole feasibility loop and just generate the UI directly using our actual UITK components, from a prompt, a Figma link, or even a screenshot? That was the seed. A few weeks later, UI Studio was live. Figure 1: UI Studio, describe what you want, drop an image, or paste a Figma URLHow it got built It took about three to four weeks to build, and it wasn't linear. It went through three very different versions before becoming what it is today. Phase 1: The hacky local version The first version was built to prove the idea, not to share it. I cloned the UITK doc site repo locally, fetched component data directly from it, and created a proxy that passed all user input to the model via terminal. It worked on my machine. But getting anyone else to use it would have meant cloning re ## Opus 4.8 on AI Gateway DevFeed: [Opus 4.8 on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-05-28T07:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Claude](), [Anthropic Claude](), [Vercel](), [vercel ai sdk](), [API](), [coding](), [Latency](), [model-deployment]() Tags: [agentic](), [ai](), [ai-gateway](), [anthropic](), [anthropic-claude](), [api](), [claude](), [coding](), [cost](), [latency](), [leaderboard](), [performance](), [playground](), [pricing](), [retention](), [sdk](), [uptime](), [vercel]() ### AI overview Claude Opus 4.8 is now available through Vercel AI Gateway and the AI SDK. It is designed for long-horizon agentic execution, complex multi-step coding tasks, and knowledge work. AI Gateway offers unified model access, usage and cost tracking, retries, failover, performance optimization, reporting, Zero Data Retention support, and provider selection based on latency and cost without adding inference fees. ### Source excerpt Claude Opus 4.8 is now available on Vercel AI Gateway. Claude Opus 4.8 is built for long-horizon agentic execution and handles complex, multi-step coding tasks like refactors that previously required human correction mid-task. The model also produces clearer, less hedgy prose for knowledge work like drafting documents, analyzing data, and building presentations. To use Opus 4.8, set model to anthropic/claude-opus-4.8 in the AI SDK. AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-provider uptime. It includes built-in custom reporting, Zero Data Retention support, dynamic provider sorting by latency & cost, and more. AI Gateway reflects provider pricing with no markup and does not charge a platform fee on inference, including on Bring Your Own Key (BYOK) requests. Learn more about AI Gateway, view the AI Gateway model leaderboard or try it in our model playground. Read more ## Snyk announces Anthropic updates: Evo integrates with Claude Enterprise, and Snyk Desk comes to Claude Desktop DevFeed: [Snyk announces Anthropic updates: Evo integrates with Claude Enterprise, and Snyk Desk comes to Claude Desktop]() Original publisher: [Read original article]() Author: Ranko Cupovic Published: 2026-05-21T17:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Anthropic Claude](), [Security](), [Artificial Intelligence](), [Extension](), [MCP](), [API](), [macOS](), [Windows]() Tags: [anthropic-claude](), [api](), [extension](), [integrations](), [macos](), [mcp](), [security](), [windows]() ### AI overview Snyk announces two Anthropic integrations: Evo adds Claude Enterprise inventory, risk, and compliance visibility, while the Snyk Security Desktop Extension brings real-time scanning and vulnerability context to Claude on macOS and Windows. ### Source excerpt Snyk announces two new integrations with Anthropic that cover both sides of AI-assisted development. Evo by Snyk now integrates with Anthropic's Claude Enterprise, and the Snyk Security Desktop Extension is now available in Claude for macOS and Windows. ## Now Available: Anthropic Claude Opus 4.6 on DigitalOcean's Agentic Inference Cloud DevFeed: [Now Available: Anthropic Claude Opus 4.6 on DigitalOcean's Agentic Inference Cloud]() Original publisher: [Read original article]() Author: DigitalOcean Published: 2026-02-06T19:38:29Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [Anthropic Claude](), [Digital Ocean](), [Inference](), [Serverless](), [AI Platform](), [long-context](), [agentic-coding](), [AI search](), [Automation](), [Development]() Tags: [agentic-coding](), [ai](), [ai-platform](), [automation](), [claude](), [development](), [digitalocean](), [inference](), [information-retrieval](), [long-context](), [product-updates](), [serverless](), [software-development]() ### AI overview DigitalOcean announces that Anthropic's Claude Opus 4.6 is available on the Gradient AI Platform through Serverless Inference. The article describes access through the API or DigitalOcean Cloud Console and highlights capabilities including a 1M-token context, adaptive reasoning, agentic coding, data analysis, information retrieval, and office productivity tasks. ### Source excerpt Claude Opus 4.6 is now available on the DigitalOcean Gradient™ AI Platform via Serverless Inference--giving teams access to Anthropic's most capable model on a platform built to run inference reliably at scale. Start using the new model now, via the API or in the DigitalOcean Cloud Console. With massive 1M-token context, adaptive reasoning, and advanced agentic coding, Claude Opus 4.6 enables teams to analyze huge datasets, refactor entire codebases, and generate high-quality outputs in a single pass. It's also optimized for everyday knowledge work, including reports, spreadsheets, and presentations. What Opus 4.6 unlocks Agentic coding & software development: Plan, debug, and iterate across large codebases; perform root cause analysis; handle multilingual coding and cybersecurity tasks. Knowledge work & research: Analyze financial data, run research, and manage multi-step tasks in documents, spreadsheets, and presentations. Agentic automation: Coordinate multiple AI agents for parallel, read-heavy, or long-running tasks; summarize large contexts and make adaptive reasoning decisions. Information retrieval & long-context reasoning: Retrieve hard-to-find details across vast datasets and reason over hundreds of thousands of tokens. Office productivity: Generate structured reports, spreadsheets, and presentation decks; ingest unstructured data and produce polished outputs in one pass. Why Run Opus 4.6 on DigitalOcean Claude Opus 4.6 runs natively inside your existing DigitalOcean environment--alongside your applications, data, networking, and storage--so inference becomes part of your stack, not another system to integrate or operate. There are no separate model contracts, vendor accounts, or billing surfaces to manage. Usage is billed predictably alongside your other DigitalOcean services, with inference managed by default so you can start running Opus 4.6 quickly without provisioning or tuning infrastructure. Safe defaults are built in from the start. Opus 4.6 runs with