# AI gateway Published articles for AI gateway. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## TypeSafe AI's Jev now available on AI Gateway DevFeed: [TypeSafe AI's Jev now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [gateway](), [SDKs](), [API](), [Software]() Tags: [ai-gateway](), [api](), [evaluation](), [gateway](), [model](), [queue](), [retry](), [sdk](), [software](), [support](), [typesafe-ai]() ### AI overview Vercel's AI Gateway now supports TypeSafe AI's Jev, a probabilistic decision model that returns typed Choice, Score, and Boolean answers with probabilities. The changelog describes parallel evaluation, AI SDK 7 integration through an experimental evaluate API, example routing and review workflows, and provider options including Zero Data Retention and No Training. ### Source excerpt Jev from TypeSafe AI is now available on AI Gateway. Jev is a probabilistic decision model for software: state goes in, typed Choice, Score, and Boolean answers come out. Regular language models generate text one token at a time, which the application then parses and validates. Jev evaluates all declared questions in parallel and returns typed answers plus probabilities directly. That removes unnecessary text generation and makes it straightforward to automate clear cases while routing uncertain ones to review. TypeSafe reports Jev was up to 193.6x faster and 444.6x cheaper than LLMs on its workflow evaluations. Example use cases include: Choosing the next tool or subagent in an agent loop Deciding whether to continue, retry, ask the user, or stop Scoring urgency or risk before an action Verifying model outputs and enforcing guardrails. AI SDK 7 exposes Jev through the experimental evaluate API. Choice selects an option, Score grades an ordered rubric, and Boolean estimates the probability of true. Install the current AI SDK (AI SDK 7.0.105 onwards supports the evaluate API): Each evaluation specifies: model: the evaluation model to call, state: the shared string, object, or array to evaluate, and questions: a map of named decisions to make about that state. Call the model with typesafe-ai/jev. This example turns one support case into a queue, priority, and refund-review decision, with uncertain routing sent for manual review: The result preserves question IDs and Choice keys. TypeSafe reports separate Choice and Score confidence in result.providerMetadata.typesafe.confidence. Calibrate probabilities and confidence against labeled examples from your workflow. Jev supports Zero Data Retention and No Training, enabled per request in the example. Evaluation calls also appear in logs and custom reporting, count toward budgets, and accept other Gateway provider options in the same providerOptions.gateway object. Read the documentation on evaluation models on AI Gateway f ## CrowdStrike Falcon Guardian Defines the Next Generation of AI Security DevFeed: [CrowdStrike Falcon Guardian Defines the Next Generation of AI Security]() Original publisher: [Read original article]() Author: Michael Devins Published: 2026-09-12T11:17:51.295154Z Content type: release Language: en Sources: [Blog]() Topics: [AI Bots]() Tags: [agentic](), [agents](), [ai](), [ai-agent](), [ai-agents](), [ai-gateway](), [ai-security](), [architecture](), [autonomous](), [platform](), [securing-ai](), [security](), [telemetry](), [threat-detection]() ### AI overview CrowdStrike announces Falcon Guardian, an AI detection and response solution for discovering, monitoring, investigating, and securing AI agents at runtime. It adds an AI gateway and connects agent activity with endpoint telemetry to support threat response. ### Source excerpt A new flagship AI detection and response solution delivers runtime protection for AI agents, introduces a new AI gateway, and extends expert-led defense. ## Model routing with Google Cloud API Gateway DevFeed: [Model routing with Google Cloud API Gateway]() Original publisher: [Read original article]() Author: Mak Ahmad; Sanjay Pujare Published: 2026-09-12T11:04:33.891311Z Content type: article Language: en Sources: [Google Developers Blog]() Topics: [Amazon API Gateway](), [Model Routing](), [Google](), [Cloud](), [OpenAPI Specification](), [Serverless](), [Claude](), [OpenAI]() Tags: [ai-gateway](), [api-gateway](), [claude](), [cloud](), [google](), [model-routing](), [models](), [openai](), [openapi](), [serverless]() ### AI overview Google Cloud API Gateway adds model routing in Public Preview, providing a serverless, OpenAI-compatible endpoint that dynamically routes requests to Gemini, Claude, or OpenAI OSS-GPT. Developers can configure routing in OpenAPI specifications, centralize model changes, and separate application authentication from backend model credentials. ### Source excerpt Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing open-source proxies. Developers can easily configure these routing rules directly within their OpenAPI 3.x specifications by mapping virtual model names to specific backend targets on a shared host. Once deployed, the Gateway acts as a serverless ingress layer that accepts standard OpenAI-compatible requests, automatically transcodes the payload to the native schema of the target model, and routes the traffic on the fly. ## Where do a compliance dashboard's numbers actually come from? DevFeed: [Where do a compliance dashboard's numbers actually come from?]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-11T09:52:40Z Content type: article Language: en Sources: [Tyk API Management]() Topics: [dashboards](), [Amazon API Gateway](), [Script]() Tags: [ai-gateway](), [ai-governance](), [ai-studio](), [api-management](), [api-platform-teams](), [complexity](), [compliance](), [llm-security](), [ppi-redaction](), [tengo](), [tutorial]() ### AI overview The article explains where a compliance dashboard's metrics come from. Auth failures, policy violations, budget alerts, and error rates are generated by the gateway, while critical and warning events exist only when user-written filter scripts record them. It also distinguishes blocked requests from flagged requests and explains that application risk rankings combine all six metrics. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given something I consider a genuine privilege: an entire dashboard, and the question of where its numbers come from. That question is less obvious than it sounds. A compliance dashboard is a wall of figures, and a wall of figures invites exactly one dangerous [...] The post Where do a compliance dashboard's numbers actually come from? appeared first on Tyk API Management. ## How Tailscale built a customer-facing model router on AI Gateway DevFeed: [How Tailscale built a customer-facing model router on AI Gateway]() Original publisher: [Read original article]() Author: Susan Aziz Published: 2026-09-11T04:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [AI Platform](), [networking](), [API keys]() Tags: [ai-gateway](), [ai-models](), [api](), [model-routing](), [sandbox](), [security](), [vercel]() ### AI overview Tailscale describes using Vercel AI Gateway and Sandbox to deliver customer-facing access to hundreds of AI models through tailnet identity. The article explains that provider integration and secure agent execution were complex enough that Tailscale chose managed routing and sandboxing instead of building those layers in-house. ### Source excerpt Tailscale on Vercel Hundreds of AI models shipped to customers in-product Model access granted and revoked by tailnet network identity Went from model routing prototype to paying customers in months Tailscale connects a company's laptops, servers, cloud instances, and personal devices into one private network called a tailnet. Remy Guercio, who leads product for Aperture by Tailscale, describes it simply: "It's basically like a VPC that can span any cloud, on-prem, your house, and your phone." Aperture takes that same idea and applies it to AI. Instead of giving every employee, agent, or tool a separate provider API key, Aperture lets companies control model access through the tailnet itself. Add someone to the network, and they can immediately use approved models. Remove them, and access disappears. Under the hood, Aperture is built on Vercel AI Gateway and Vercel Sandbox. AI Gateway gives Tailscale one API for hundreds of models. Sandbox gives agents a safe place to run. Together, they let Tailscale offer model access and agent execution inside a customer's private network, without their team building every piece of AI infrastructure from scratch. Model routing is harder than it looks Tailscale is an infrastructure company, so building the routing and execution layers in-house was the obvious first option. But once they took a deeper look into the engineering effort required, they chose not to. The provider layer looked deceptively simple from the outside. "You would think all of the endpoints are the same," Remy says. "They are not." David Carney, Co-founder and Chief Strategy Officer, has the receipts, because Tailscale still maintains that plumbing for a few customers who haven't migrated to Aperture yet. "There are a lot of things the big providers don't do that blow my mind that the gateway does, like simply putting the cost in the response," he says. "We initially built those systems for customers ourselves, and the complexity is insane." Agents raised the s ## How Featured's users make 100K media pitches per month on Vercel DevFeed: [How Featured's users make 100K media pitches per month on Vercel]() Original publisher: [Read original article]() Author: Susan Aziz Published: 2026-09-11T04:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [migration](), [vercel ai sdk](), [AI Chat](), [SDKs]() Tags: [ai](), [ai-gateway](), [aws](), [featured](), [infrastructure](), [migration](), [models](), [vercel](), [vercel-ai-sdk](), [workflow]() ### AI overview Featured describes migrating 374 Sanity sites from AWS Elastic Beanstalk to Vercel while using Vercel's AI SDK, AI Gateway, and Workflow SDK to reduce infrastructure work for a three-engineer team. ### Source excerpt Featured on Vercel 3 engineers supporting 3 brands and 100,000+ users on Vercel Migrated 374 Sanity sites from AWS Elastic Beanstalk to Vercel AI SDK and AI Gateway power Featured's chat bot across 17 models Workflow SDK replaced custom long-running job infrastructure Featured is a co-pilot for public relations (PR) that subject matter experts and PR teams use to find media opportunities. Tell Featured's agents what you know, and it surfaces opportunities across journalist requests, podcasts, awards, and GEO, with no PR background required. Founder Brett Farmiloe knows from experience how hard and time consuming getting press is. He spent 10 years running Markitors, a digital marketing agency with 500 small business clients. Every client, from an eyelash extension supplier to an equipment financing company, had real expertise to share, but no way to get it in front of journalists. PR, as Farmiloe puts it, "has always been about who has access to what." He founded Featured to change the question from who has access to who has knowledge. Featured connects one of their users with a journalist or publisher every 6 seconds. Their agents deliver more than 100,000 media pitches per month, and have sent over 100 million Help A Reporter Out (HARO) emails in the past year. Behind it all is an engineering team of just three people. With a team that lean, there's no time to manage servers or piece together custom integrations. Every hour spent on infrastructure is an hour taken away from building features what will help their customers land more media placements. The cost of managing infrastructure by hand Before Vercel, Featured's infrastructure work pulled the team away from product development. Hosting lived on AWS Elastic Beanstalk, AI features depended on custom provider integrations, and long-running, multi-step jobs ran on separate orchestration infrastructure. Each layer worked, but each one added operational overhead for a three-person team supporting multiple brands. ## One name in, whichever vendor you like out DevFeed: [One name in, whichever vendor you like out]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-10T11:21:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [API](), [Large Language Model](), [App](), [Bot]() Tags: [ai-gateway](), [ai-governance](), [ai-strategy](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [developers](), [enterprise](), [llm](), [llm-governance](), [model](), [router](), [tutorial]() ### AI overview A tutorial explains how to use Tyk's Model Router as a single OpenAI-compatible endpoint that routes requests to registered LLM providers. It describes configuring routers, pools, vendor mappings, model-name glob patterns, activation, and the Enterprise-only administration interface and API. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given a router. Not the sort that sits in a cupboard blinking reproachfully at you. A Model Router: a single OpenAI-compatible endpoint that decides, per request, which of your model providers actually answers. Your application asks for a model by name. Which vendor serves [...] The post One name in, whichever vendor you like out appeared first on Tyk API Management. ## Tako Search is free on AI Gateway through September 30 DevFeed: [Tako Search is free on AI Gateway through September 30]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-10T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [SDKs](), [API](), [Web](), [data]() Tags: [ai](), [ai-gateway](), [api](), [configuration](), [documentation](), [free](), [integration](), [playground](), [sdk](), [search](), [tools](), [web]() ### AI overview This changelog announces that Tako Search is free on AI Gateway through September 30. It enables AI models to search curated data and the live web, filter results, and provide current answers with citations and visualizations. Tako Search works with any model on AI Gateway and does not require a separate Tako account or API key. ### Source excerpt Tako Search is free exclusively on AI Gateway through September 30. It lets AI models search Tako's curated data and the live web, filter web results by domain or publication date, and use the results to answer questions with current information, citations, and visualizations. After September 30, searches are billed at standard rates. The same integration works with any model on AI Gateway, so you can switch models without changing your search setup. You also don't need a separate Tako account or API key. To use Tako Search with the AI SDK, add gateway.tools.takoSearch() to a generateText or streamText request. The model can then call it when it needs current information: Try Tako Search in the AI Gateway playground. See the web search documentation for configuration and search options. Read more ## The same question twice, paid for once: installing an LLM response cache DevFeed: [The same question twice, paid for once: installing an LLM response cache]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-09T09:15:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Large Language Model](), [Cache](), [Caching](), [Tutorial](), [Open Source](), [Go](), [Code]() Tags: [ai-gateway](), [ai-strategy](), [ai-studio](), [api-management](), [api-platform-teams](), [article](), [cache](), [container](), [container-image](), [go](), [llm](), [llm-governance](), [open-source](), [tutorial]() ### AI overview A tutorial showing how to install a community plugin that caches LLM responses in AI Studio. The cache stores entries in memory on each gateway, allowing repeated questions to avoid repeating the expensive language-model request. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment involves no code whatsoever, which I am told is a selling point. Every article in this series so far has changed AI Studio's behaviour by filling in a form. This one changes what AI Studio is. We are going to install a plugin -- a compiled [...] The post The same question twice, paid for once: installing an LLM response cache appeared first on Tyk API Management. ## DeepSeek V4.1 Flash now available on AI Gateway DevFeed: [DeepSeek V4.1 Flash now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-09T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [deepseek](), [Artificial Intelligence](), [API](), [Language models](), [AI-assisted coding](), [Claude Code](), [codex](), [cursor]() Tags: [ai](), [ai-gateway](), [api](), [caching](), [codex](), [context-window](), [cursor](), [deepseek](), [responses](), [tool](), [vercel](), [vision]() ### AI overview DeepSeek V4.1 Flash is now available through Vercel's AI Gateway, offering native image understanding, a 1 million token context window, responses up to 384,000 tokens, reasoning, tool use, and prompt caching. Developers can use it in Claude Code, Codex, Cursor, and other coding agents with the model name deepseek/deepseek-v4.1-flash. ### Source excerpt DeepSeek V4.1 Flash is now available on AI Gateway with native image understanding. V4.1 Flash has vision support and accepts text and images in the same request, so you can ask questions about screenshots, read charts, and extract information from visual content. The model has a 1 million token context window and supports responses up to 384,000 tokens, along with reasoning, tool use, and prompt caching. Its new architecture processes input and generates output with separate components, reducing the active computation needed for each stage. Use deepseek/deepseek-v4.1-flash as the model name: To use it in Claude Code, Codex, Cursor, and more, install the latest Vercel CLI and run setup: Then select deepseek/deepseek-v4.1-flash in the agent. See the coding agents guide for details. Try DeepSeek V4.1 Flash in the model playground. 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, budgets for API keys, routing rules, 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. You can view all language models available on AI Gateway. Read more ## Somebody else's API, safely on your menu DevFeed: [Somebody else's API, safely on your menu]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-08T14:28:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [API](), [shadow AI](), [audit trail](), [Template](), [Tool](), [data]() Tags: [ai](), [ai-gateway](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [article](), [audit-trail](), [community](), [governance](), [llm](), [llm-governance](), [markdown](), [password](), [policy](), [resource](), [shadow-ai](), [tools](), [tutorial]() ### AI overview This tutorial explains how to submit an internal API for governed use by colleagues and organizational language models. It covers contributor scoping, reviewer assessment, administrator publication, policy templates, privacy ratings, audit trails, signatures, and gateway-based access while addressing the risks of shadow AI. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment is one I have been looking forward to rather a lot. Somebody on your engineering team has written an API. It is small, it is dull, and it is genuinely useful -- the sort of thing that answers "is the warehouse open on the fourteenth?" without [...] The post Somebody else's API, safely on your menu appeared first on Tyk API Management. ## Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one DevFeed: [Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-08T11:07:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [Authorization](), [Language models]() Tags: [access-control](), [ai](), [ai-gateway](), [ai-studio](), [api-management](), [api-platform-teams](), [article](), [developer](), [governance](), [llm](), [llm-governance](), [tutorial](), [uncategorized]() ### AI overview This tutorial explains how to govern which users can access language models and other resources in Tyk AI Studio. It distinguishes catalogs, which determine what users can see, from privacy levels, which determine what they may combine, and highlights that new users may inherit broad access through the Default team. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today's assignment is a slightly different sort of thing. Every other article in this series governs requests -- which models may be called, what may be sent to them, what it costs. This one governs people. By the end, one person in this organisation will be able to [...] The post Who can use which model? Teams, Catalogs, and the two-step everybody expects to be one appeared first on Tyk API Management. ## One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice DevFeed: [One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-07T09:27:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [OpenAPI Specification](), [Model Context Protocol (MCP)](), [MCP Server](), [API](), [ASCII](), [HTTP](), [cURL]() Tags: [ai-gateway](), [ai-governance](), [ai-readiness](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [article](), [ascii](), [curl](), [developer](), [http](), [llm-governance](), [llm-observability](), [mcp-server](), [model-context-protocol](), [openapi]() ### AI overview This tutorial shows how to define an HTTP API once in an OpenAPI document and expose it through three surfaces: model-initiated tool calls, a REST endpoint accessed with curl, and an MCP server. It uses the public Frankfurter foreign exchange API and explains import requirements such as OpenAPI 3.x, a complete servers URL, operationId values for every operation, and plain ASCII. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given a genuinely satisfying assignment. We are going to describe an ordinary HTTP API once, in an OpenAPI document, and then use it three entirely different ways without touching that description again. A model will call it on its own initiative inside a chat. [...] The post One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice appeared first on Tyk API Management. ## Comparing token economics across 42 AI models DevFeed: [Comparing token economics across 42 AI models]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2026-09-04T12:00:00Z Content type: comparison Language: en Sources: [Blog -- Neon Docs]() Topics: [AI Chat](), [AI-assisted coding]() Tags: [ai-gateway](), [ai-models](), [benchmark](), [community](), [cost](), [llms]() ### AI overview A comparison of 42 AI models on a synthetic workload of 100 support tickets, evaluating cost, usable responses, and completion time. It highlights differences in token use, accuracy, speed, and total workload cost. ### Source excerpt If headcount is often a company's largest cost, tokens will be a close second soon as agents take on more work. Imagine how much $$ a software company will be able to save just by pre-selecting models that are efficient to run, especially in large companies with many engineers using coding agents. ## GPT 6 Astra now available on Vercel AI Gateway DevFeed: [GPT 6 Astra now available on Vercel AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-04T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [OpenAI](), [Vercel](), [AI-assisted coding](), [codex]() Tags: [agentic](), [ai](), [ai-gateway](), [coding](), [coding-agents](), [gpt](), [model](), [openai](), [playground](), [vercel]() ### AI overview Vercel AI Gateway now offers OpenAI's GPT 6 Astra, a model designed for long-running agentic work. It can navigate software, analyze data, run simulations, and build and test websites while adapting to changing requirements. ### Source excerpt GPT 6 Astra from OpenAI is now available on AI Gateway. GPT 6 Astra is designed for long-running agentic work. It can navigate software, analyze data, run simulations, and build and test websites while adapting to new requirements, filling in routine gaps, and continuing other work when it needs clarification. Use the model ID openai/gpt-6-astra: To use GPT 6 Astra with a coding agent, run vercel ai-gateway coding-agents setup, then select openai/gpt-6-astra. See the setup guides for Codex and Hermes for specific instructions. Try GPT 6 Astra in the model playground. Read more ## Ling 3.0 Flash Sante is now available on AI Gateway for free DevFeed: [Ling 3.0 Flash Sante is now available on AI Gateway for free]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-04T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [context window]() Tags: [agentic](), [ai](), [ai-gateway](), [coding](), [context-window](), [free](), [healthcare](), [model](), [retrieval]() ### AI overview Ling 3.0 Flash Sante, a healthcare-focused model from inclusionAI, is available on AI Gateway for free through October 4. It supports medical reasoning, research, evidence retrieval, multi-step healthcare tasks, function calling, and a 256K-token context window. ### Source excerpt Ling 3.0 Flash Sante from inclusionAI is now available on AI Gateway, and free through October 4. Ling 3.0 Flash Sante is the healthcare-focused version of Ling 3.0 Flash. It's built for medical reasoning, research, evidence retrieval, and multi-step healthcare tasks. It has a 256K-token context window, supports function calling, and retains the base model's general reasoning, coding, and agentic capabilities. Choose a model ID based on what should happen after the free period: inclusionai/ling-3.0-flash-sante continues serving requests at standard rates after October 4. inclusionai/ling-3.0-flash-sante-free stops serving requests after October 4. Free requests remain visible in your usage and traces but show a cost of $0. Use the model: Try Ling 3.0 Flash Sante in the model playground, or see the free model page. Read more ## Your redaction filter works. Are you quite sure? DevFeed: [Your redaction filter works. Are you quite sure?]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-03T09:03:23Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Tutorial](), [pii](), [Artificial Intelligence](), [Script](), [Regular expression](), [payload](), [API]() Tags: [ai-gateway](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [data-privacy](), [how-to](), [llm-governance](), [payload](), [pii](), [pii-redaction](), [tengo](), [tutorial]() ### AI overview This tutorial explains how to create and test a Tyk request filter that redacts personal data before a request reaches an AI model. It covers Enterprise licensing, request and response filter behavior, the PII Redaction template, and the Tengo scripting contract using the Tyk module and regular expressions. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given something genuinely useful to explain: how to stop personal data reaching a model in the first place. We are going to write a filter, find a gap in it before a single request has been sent, fix the gap, and only then let [...] The post Your redaction filter works. Are you quite sure? appeared first on Tyk API Management. ## One environment variable, and Claude Code is suddenly accountable DevFeed: [One environment variable, and Claude Code is suddenly accountable]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-02T10:38:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [Claude Code](), [anthropic](), [API](), [configuration](), [Tutorial]() Tags: [ai-gateway](), [ai-studio](), [anthropic](), [api](), [api-management](), [api-platform-teams](), [article](), [claude-code](), [configuration](), [llm-governance](), [llm-observability](), [secrets](), [tutorial]() ### AI overview This tutorial explains how to route Claude Code through Tyk AI Studio's Anthropic-compatible endpoint using one environment variable. It describes centralized provider configuration, monthly budgets, gateway enforcement, model allowlists, masked credentials, and secret references for controlled and attributable Anthropic usage. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been handed something slightly unusual: an article in which the thing being governed is very probably the thing you are using right now. Claude Code. Somebody on your team is running it. Possibly everybody is. It is excellent, it is fast, and from where your [...] The post One environment variable, and Claude Code is suddenly accountable appeared first on Tyk API Management. ## Nobody Should Be Sharing Your OpenAI Key DevFeed: [Nobody Should Be Sharing Your OpenAI Key]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-02T08:35:50Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [OpenAI](), [Large Language Model](), [Tutorial](), [API]() Tags: [ai](), [ai-gateway](), [ai-studio](), [anthropic](), [api](), [api-management](), [api-platform-teams](), [developer](), [gpt](), [large-language-model](), [llm](), [llm-governance](), [models](), [openai](), [secrets](), [tutorial]() ### AI overview This tutorial explains how an organization can register OpenAI as a provider in Tyk, expose it through a portal and gateway, keep the provider key hidden from developers, optionally reference the key through Secrets, and restrict permitted models with a regular-expression pattern such as gpt-5.*. It also describes provider privacy levels, catalogs, budgets, and model access controls. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and I have been given the considerable privilege of explaining how a large language model gets from "we have an account with OpenAI" to "a developer is shipping with it, inside a budget, and has never seen the key". It is a shorter journey than you might expect. It [...] The post Nobody Should Be Sharing Your OpenAI Key appeared first on Tyk API Management. ## Muse Spark 1.3 now available on AI Gateway DevFeed: [Muse Spark 1.3 now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [AI Chat]() Tags: [agents](), [ai](), [ai-gateway](), [claude](), [claude-code](), [codex](), [coding](), [cursor](), [meta](), [models](), [pdf](), [playground](), [release](), [spark](), [vercel]() ### AI overview Muse Spark 1.3 from Meta is now available on AI Gateway in standard and contributor pricing tiers. The model adds a 1M-token context window and accepts text, image, and PDF input; the contributor tier uses the same model but allows Meta to use submitted inputs and outputs for model improvement in exchange for lower pricing. ### Source excerpt Muse Spark 1.3 from Meta is now available on AI Gateway, in both the standard and contributor pricing tiers. This model improves on prior Muse Spark models at agent work and coding, with a 1M token context window and text, image, and PDF input. On coding it takes fewer turns and writes less filler than the previous release. To use Muse Spark 1.3, set model to meta/muse-spark-1.3: Contributor tier Muse Spark 1.3 Contributor is a pricing tier on the same model rather than a separate one, with the same weights, capabilities, and context window. The difference is that Meta uses the inputs and outputs sent to this tier to train and improve its models, and pricing is lower in exchange. Model Input Output Cached input meta/muse-spark-1.3 $1.25 $4.25 $0.15 meta/muse-spark-1.3-contributor $0.10 $0.20 $0.002 Rates are per million tokens and unchanged from Muse Spark 1.2 on both tiers. To use it in a coding agent, see the coding agents guide, then run vercel ai-gateway coding-agents setup to connect Claude Code, Codex, Cursor, and more, then select meta/muse-spark-1.3 in the agent. Try Muse Spark 1.3 in the model playground. You can view all language models available on AI Gateway. Read more ## GLM-5.3 is 50% off through DigitalOcean on AI Gateway DevFeed: [GLM-5.3 is 50% off through DigitalOcean on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Digital Ocean](), [Language models](), [long-context](), [AI-assisted coding](), [Claude Code](), [codex](), [cursor]() Tags: [ai-gateway](), [claude-code](), [codex](), [coding-agents](), [context-window](), [cursor](), [digitalocean](), [language-models](), [model](), [tokens](), [vercel]() ### AI overview Vercel announces a 50% discount on GLM-5.3 through DigitalOcean on AI Gateway until September 8. The article explains the temporary promo model name, standard provider routing, model limits, spend tracking, and setup for coding agents. ### Source excerpt GLM-5.3 is 50% off on AI Gateway through Tuesday, September 8, in partnership with DigitalOcean. How to use the model during the offer period Using the promo name (zai/glm-5.3-promo-50) gets the discounted rate. It routes only to DigitalOcean, with no fallback to another provider, and it stops serving when the offer ends. Using the standard name (i.e., zai/glm-5.3) with provider options to sort DigitalOcean as the preferred provider keeps working after September 8 and routes across every provider that serves the model, at their usual rates. Because the promo name goes away when the offer ends, treat it as something you switch on for the window rather than hardcode. To keep the standard name in your code instead, pin the provider with order: ['digitalocean'] under providerOptions.gateway, which prefers DigitalOcean and falls back to the others if it cannot serve the request. GLM-5.3 takes text input, with a 1M token context window and a maximum output of 128K tokens. Discounted requests appear in your spend dashboard and carry a trace like any other request. Try GLM-5.3 in the model playground. To use it in a coding agent, see the coding agents guide, then run vercel ai-gateway coding-agents setup to connect agents like Claude Code, Codex, OpenCode, Cursor, Pi, and more and select zai/glm-5.3-promo-50 inside the agent. You can view all language models available on AI Gateway. Read more ## Gemini 3.8 Flash now available on AI Gateway DevFeed: [Gemini 3.8 Flash now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [Language models](), [Google](), [context window](), [AI-assisted coding]() Tags: [ai](), [ai-gateway](), [coding-agents](), [context-window](), [flash](), [google](), [inference](), [language-models]() ### AI overview Vercel announces that Gemini 3.8 Flash from Google is available on AI Gateway, with a 1M-token context window, multimodal input, tool calling, web search, and a 65,536-token maximum output. The model is discounted by 50% through December 31 and is positioned as an improvement for software engineering, agent work, and multi-step reasoning. ### Source excerpt Gemini 3.8 Flash from Google is now available on AI Gateway. The model is 50% off through December 31st. It has a 1M token context window, accepts text, image, PDF, and video input, returns text, and supports tool calling and web search. Maximum output is 65,536 tokens. Gemini 3.8 Flash improves on prior Flash models at software engineering, agent work, and multi-step reasoning, at the same speed and cost as the previous release. Thinking is on by default. To use Gemini 3.8 Flash, set model to google/gemini-3.8-flash: To use it in a coding agent, see the coding agents guide, then run vercel ai-gateway coding-agents setup to connect agents like Claude Code, OpenCode, Cursor, Pi, and more and select google/gemini-3.8-flash inside the agent. Try Gemini 3.8 Flash in the model playground. 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. You can view all language models available on AI Gateway. Read more ## Qwen 3.8 Max 0902 now available on AI Gateway DevFeed: [Qwen 3.8 Max 0902 now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-01T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [qwen](), [Language models](), [AI-assisted coding]() Tags: [ai-gateway](), [coding-agents](), [models](), [qwen](), [release](), [vision]() ### AI overview Qwen 3.8 Max 0902, a new Alibaba snapshot, is now available through AI Gateway. The release focuses on coding for larger projects, unsupervised long-horizon tasks, agent runs, and improved vision handling for charts and dense documents. It can be selected directly, pinned by its dated model ID, or reached through a rewrite routing rule. It is also supported in several coding-agent integrations and the model playground. ### Source excerpt Qwen 3.8 Max 0902 from Alibaba is now available on AI Gateway. This is a new snapshot of Qwen 3.8 Max, with the gains concentrated in coding on larger projects, long-horizon work that runs without supervision, and agent runs. Vision handling is more accurate on charts and dense documents. To use Qwen 3.8 Max 0902, set model to alibaba/qwen3.8-max-0902: The dated ID pins this snapshot, so a later release will not change what your requests run against. To move existing traffic onto it without a code change, add a rewrite routing rule. The gateway substitutes the destination transparently, so an application that still asks for alibaba/qwen3.8-max runs on the new snapshot: To use it in a coding agent, see the coding agents guide, then run vercel ai-gateway coding-agents setup to connect agents like Claude Code, Codex, OpenCode, Cursor, Pi, and more and select alibaba/qwen3.8-max-0902. Try Qwen3.8-Max-0902 in the model playground. You can view all language models available on AI Gateway. Read more ## Claude Fable 5.1 now available on AI Gateway DevFeed: [Claude Fable 5.1 now available on AI Gateway]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-01T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Language models](), [AI-assisted coding](), [AI, ML & Data Engineering](), [Vulnerabilities](), [cursor]() Tags: [agentic](), [agentic-coding](), [ai-gateway](), [anthropic](), [api](), [claude](), [language-models](), [safety](), [vulnerabilities]() ### AI overview Claude Fable 5.1 is available on AI Gateway, with model fallback support for safety-classifier refusals and compatibility across its API formats. ### Source excerpt Claude Fable 5.1 from Anthropic is now available on AI Gateway. Fable 5.1 improvements compared to previous Claude models are concentrated in long, multi-stage work like agentic coding, knowledge work, and research that takes several rounds of searching and following up. Anthropic ships Fable 5.1 with cybersecurity and biology safety classifiers enabled. Finding vulnerabilities in source code is allowed, but some routine coding and debugging may still be refused. To ensure requests are still serviced when the safety classifiers are triggered, use model fallbacks. Add a models array to providerOptions.gateway listing the models to try. AI Gateway sends the request to Fable 5.1 first, and if Anthropic refuses it, works down the array in order and returns the response from the first model that succeeds: This request falls back to Opus 5, then Sonnet 5, if a safety classifier is triggered. The same models option works on every AI Gateway API format, including Chat Completions, Messages, and OpenAI Responses. Try Fable 5.1 in the model playground. To use it in a coding agent, see the coding agents guide, then run vercel ai-gateway coding-agents setup to connect agents like Claude Code, Codex, OpenCode, Cursor, Pi, and more and select anthropic/claude-fable-5.1 inside the agent. Anthropic does not support Zero Data Retention for Fable 5.1. Prompts and completions are retained for 30 days and are not used to train Claude. You can view all language models available on AI Gateway. Read more [Next page]()