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Cap AI Gateway spend before coding agents run away with the bill

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#vercel #ai-gateway+7

AI-generated · Automatically published by LinkLoot. Vercel AI Gateway now supports team, project, and API-key budgets with alerts and request blocking when a cap is reached. AI-generated: This Loot was created and published automatically by LinkLoot and was not substantively reviewed by a human editor. Vercel AI Gateway now has scoped spend budgets, which makes it worth a look for teams running agents through one shared model gateway. What it is Vercel added budgets that can cap AI Gateway spend at the team, project, or API-key level. A request can be checked against multiple budgets, and the gateway rejects it when any applicable limit is exhausted. Who it helps This is useful for product teams, agencies, and internal platform owners who let several agents, apps, or experiments share the same model gateway. It gives finance and engineering a clearer stop-loss than watching one API key after the fact. How to evaluate it Start by mapping current gateway traffic to projects and keys, then create low-risk alert-only thresholds before using hard caps on production workloads. The changelog shows CLI commands for setting team and project budgets, listing configured limits, and removing them. Limits and risks Budgets can block requests once a limit is reached, so production agents need fallbacks, user-visible errors, or a runbook for raising limits. Vercel also notes that BYOK spend is not counted against budgets by default, which matters if teams mix provider keys with gateway-managed spend. Sources Vercel AI Gateway budgets changelog

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Use Vercel's AI Gateway leaderboard export for model adoption research

#ai #data+5

Vercel opened the data behind its AI Gateway leaderboards, giving builders a downloadable and queryable source for model, lab, app, and provider adoption trends. Vercel's AI Gateway leaderboard export is useful when you need a quick market signal before choosing models, writing AI coverage, or comparing provider adoption. What it is Vercel publishes aggregated AI Gateway leaderboard data under a CC BY 4.0 license. The leaderboards rank models, labs, apps, and inference providers across metrics such as requests, token volume, spend, and generated image or video counts. Who it helps It is practical for AI builders, analysts, editors, and product teams who want a repeatable source for model adoption trends instead of relying only on social buzz or benchmark tables. How to evaluate it Start with the leaderboard UI, then use the leaderboard-export endpoint for CSV or programmatic checks. Compare model share over time, filter by modality when needed, and treat the data as Vercel AI Gateway usage rather than the whole AI market. Limits and risks The dataset only reflects traffic visible through Vercel's gateway and opted-in leaderboard surfaces. It can show adoption momentum, but it cannot prove global usage, model quality, or total revenue across providers. Sources Vercel changelog AI Gateway leaderboard export endpoint

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Make Vercel CLI 55 project linking safe for CI agents

#vercel #cli+3

Vercel CLI 55 changes how vercel link, deploy, pull, dev, and git connect resolve teams and projects. CI and agent workflows should pass --team/--scope or set VERCELORGID and VERCELPROJECTID before upgrading, because --yes no longer selects a team automatically. Use this as an upgrade checkpoint before moving CI, coding agents, or deployment scripts to Vercel CLI 55. The linking flow now resolves the team first and searches projects inside that team, which makes project discovery faster but removes an old implicit behavior: --yes confirms prompts, but it does not choose a team. For promptless runs, set VERCELORGID and VERCELPROJECTID, or pass --team/--scope explicitly. If a command has multiple possible teams and no explicit signal, non-interactive runs can fail with actionrequired: missingscope before creating or touching a link. That is useful for safety, but only if your automation expects it.

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Run Thinking Machines Inkling through Vercel AI Gateway

#ai models #vercel+3

Use Vercel's AI Gateway model page to test Inkling as thinkingmachines/inkling without adding another provider integration. Inkling is Thinking Machines' open-weights multimodal MoE model, with text, image and audio inputs, controllable thinking effort, and long-context support. Treat it as an evaluation target for multimodal agent workflows, not as an automatic replacement for stronger closed frontier models. Vercel has added Thinking Machines' Inkling to AI Gateway under thinkingmachines/inkling, so teams already using AI Gateway can test it through the same playground, routing, budget, retry and usage-tracking layer they use for other models. Inkling is an open-weights multimodal MoE model from Thinking Machines with text, image and audio inputs, controllable thinking effort and long-context support. Use it for practical evaluation of multimodal agent workflows, document/audio reasoning and fine-tuning paths; compare latency, cost and output quality before moving production traffic.

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Plan Next.js upgrades before the July 20 security patch window

#Next.js #security+3

Next.js is moving to scheduled security releases. The first planned patch window targets July 20, 2026, with fixes for Next.js 16.2 and 15.5 covering 4 high and 5 medium severity issues. Use this as an upgrade-planning checkpoint, not as a CVE detail source until the final advisory lands. Use this official Next.js announcement to schedule upgrade work before the July 20, 2026 security release window. The post says the first scheduled release will include patch releases for Next.js 16.2 and 15.5, covering 4 high and 5 medium severity issues. Treat it as planning material until the final advisory publishes CVEs and affected ranges.

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Run Playwright tests faster on Vercel with Endform

#endform #vercel+3

Endform runs existing Playwright suites on isolated cloud runners and plugs the result into Vercel preview and production deployments. Endform is a managed Playwright test runner for Vercel teams that want deployment checks without building their own browser-runner fleet. It is useful when a suite is slow because tests run serially, collide on shared state, or need trace history across preview deployments. Vercel's Marketplace changelog says Endform can run each test on its own isolated machine, link pass/fail checks to Vercel deployments, keep full Playwright traces, and charge by test runtime. Endform's docs add the important setup caveat: tests run remotely, so the target app must be reachable by the remote runners or proxied through Endform's local-network option. Best fit Vercel apps with Playwright suites that slow down preview deploys. Teams that want deployment checks tied to traces and historical runs. SaaS products where flaky E2E tests delay releases. Projects that already use @playwright/test and want less CI plumbing. Check before using Confirm pricing and runtime limits for your test volume. Make sure each test is independent enough to run in parallel. Check how preview deployment protection, secrets, and test accounts are handled. Validate that remote runners can reach the app or configure the proxy path. Keep destructive tests away from production data.

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Give Vercel agents their own inbox with AgentMail

#agentmail #vercel+3

AgentMail adds API-managed email inboxes, webhooks, custom domains, and live message streams to Vercel-hosted AI agents. AgentMail is an email-infrastructure tool for Vercel apps that need real inboxes for agents, assistants, and workflow automation. It is useful when an agent must receive attachments, handle email-based verification, route support messages, or keep a human reviewer in the loop without sharing one generic mailbox. The Vercel Marketplace page lists AgentMail as a native integration for provisioning inboxes, managing custom domains, and sending or receiving email programmatically. The product page adds the practical developer angle: the TypeScript SDK works in Next.js API routes, App Router route handlers, serverless functions, and Edge functions. Best fit AI support agents that need a dedicated inbound address. Browser or workflow agents that must handle email-based login checks. Document-processing flows that receive attachments and reply automatically. Multi-tenant SaaS products that need one inbox per user, tenant, or agent. Check before building Confirm pricing, limits, and Vercel Marketplace billing for your account. Use separate inboxes and domains for tenants or high-risk workflows. Validate webhook signatures and keep retries idempotent. Treat inbound email and attachments as untrusted input before handing them to an agent. Add human review for workflows that can send external replies or trigger account changes.

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Build X bots with Vercel Chat SDK

#vercel #chat-sdk+3

Use Vercel Chat SDK's new X adapter to handle public mentions and direct messages from one bot codebase. Vercel added an X adapter to Chat SDK on July 14, 2026. It lets teams build bots that reply to public mentions and direct messages through X API v2 and the X Activity API while keeping the same Chat SDK pattern used for Slack, Discord, GitHub, Teams, Telegram, and WhatsApp. Best fit: teams already building multi-channel support, community, or workflow bots with Chat SDK. Check before use: The adapter handles CRC verification, webhook signature checks, and OAuth token refresh for long-running bots. X supports likes as the only reaction in this adapter. Responses post once after completion because X has no native streaming. X automation rules still apply to automated messages, so review policy and rate limits before production use.

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Repair Vercel build settings from the CLI before redeploying

#vercel #cli+3

Use Vercel CLI project update to fix framework presets, build commands, output directories, and auto-detection without opening the dashboard. Vercel now lets teams update project framework and build settings from the terminal with vercel project update. It is most useful when an agent or CI helper has diagnosed a failed deployment and needs to correct the framework preset, build command, install command, development command, or output directory before redeploying. Try it when a project was imported with the wrong preset, a monorepo output path changed, or a dashboard-only fix would slow down an automated recovery flow. Use --format=json when another script needs to inspect what changed, and use --auto-detect when you want Vercel to resume automatic detection for a setting. What to check first: Update the Vercel CLI to v54.21.1 or later. Confirm the linked project or pass the project name explicitly. Review changed settings before redeploying production. Do not pipe secrets into build settings; keep secret values in environment variables. Example use cases: Fix a Vite-to-Next.js preset mismatch. Reset a stale output directory to auto-detection. Let an agent repair build settings using JSON output for verification.

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Generate editable Seedream 5.0 Pro images through Vercel AI Gateway

#vercel #ai-gateway+3

Vercel AI Gateway now exposes ByteDance Seedream 5.0 Pro as bytedance/seedream-5.0-pro, giving teams a routed API path for production image generation and editing workflows. Vercel added ByteDance Seedream 5.0 Pro to AI Gateway on July 11, 2026. Use it when you want one API layer for image generation, usage tracking, budgets, routing rules, retries, and BYOK behavior instead of wiring a separate image provider directly into every app. The practical draw is not just another model listing. ByteDance positions Seedream 5.0 Pro for production image work: layer-separated outputs, precise local edits, coordinate and hex color control, multilingual text rendering, infographics, product visuals, and marketing assets. Through Vercel's AI SDK, the model id is bytedance/seedream-5.0-pro. Why bookmark it Vercel gives app teams a standard gateway route for Seedream 5.0 Pro instead of a one-off provider integration. Seedream 5.0 Pro is aimed at editable commercial assets, not only flat prompt-to-image output. ByteDance says the model supports layer separation, targeted editing, 14-language text generation, and design-oriented controls. Vercel says AI Gateway can track usage and cost, apply budgets, configure routing rules, support Zero Data Retention, and use provider pricing with no platform markup. Quick checks before shipping Confirm your Vercel project can access AI Gateway and the model playground. Test text rendering, brand colors, localization, and image edits with real campaign assets. Compare Vercel Gateway pricing and retention settings with direct ByteDance/Lumina access. Check whether your workflow needs layered export features that may only exist in specific ByteDance/Lumina surfaces. Keep generated commercial assets in human review until rights, brand, and regional requirements are clear.

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Cut LLM routing waste with Vercel AI Gateway provider sorting

#vercel #ai gateway+3

Vercel AI Gateway can now rank providers by cost, time to first token, or throughput before fallback, so agent apps can optimize routing without hard-coding provider order. Vercel added provider sorting to AI Gateway. Set providerOptions.gateway.sort to cost, ttft, or tps and the gateway ranks available providers behind a model by the selected metric before it falls back to the next provider. Use it when a model has multiple providers and your workflow has a clear priority: lowest listed input cost for batch jobs, lower time to first token for interactive chat, or higher tokens per second for long outputs. The routing metadata can show which providers were considered, attempted, deprioritized, or selected. This is useful, but it is not a magic optimizer. Provider sorting works best after you define the workload, check data-retention constraints such as ZDR, and verify model/provider behavior with your own prompts and token mix.

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Use Vercel Connect to stop storing bot tokens in Chat SDK projects

#Vercel #Chat SDK+4

Vercel's Chat SDK now supports Vercel Connect, letting bot builders use connector-backed Slack, GitHub, and Linear credentials instead of storing long-lived tokens and signing secrets in their own app. Use Vercel Connect to stop storing bot tokens in Chat SDK projects Vercel Connect support in Chat SDK is worth bookmarking if you build bots that talk to Slack, GitHub, or Linear. The practical win is credential handling: @vercel/connect/chat returns adapter helpers that use connector UIDs, fresh short-lived tokens, and OIDC-verified inbound triggers instead of app-managed token storage. Best fit Use case Why it helps Caveat --- --- --- Slack bots on Vercel connectSlackAdapter() can feed credentials into the Slack adapter. Vercel Connect is still beta. GitHub or Linear workflow bots Connector-backed auth reduces manual token rotation work. Check connector availability for your account. Inbound bot events Vercel documents trigger forwarding with OIDC validation. Review event scope and permissions before production use. What to check first Confirm your project can use Vercel Connect and the needed connector. Review the @vercel/connect/chat adapter helper docs. Keep least-privilege scopes on Slack, GitHub, and Linear connectors. Test inbound trigger verification before trusting production events. Read the beta terms, because connector behavior can change before GA. Practical LinkLoot angle This is not broad platform news, but it is a useful security and maintenance shortcut for bot projects. If your Chat SDK bot currently stores tokens or webhook signing secrets, test Vercel Connect in a staging deployment and compare the operational surface: fewer secrets, shorter-lived outbound credentials, and a standard verification path for inbound events. Source check Vercel's July 8, 2026 changelog confirms Chat SDK support for Vercel Connect and the @vercel/connect/chat subpath. The Chat SDK documentation explains setup, connector UIDs, adapter helpers, outbound token handling, and inbound webhook verification.

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Blog

#vercel

More from this topic

Cap AI Gateway spend before coding agents run away with the bill

Use Vercel's AI Gateway leaderboard export for model adoption research

Make Vercel CLI 55 project linking safe for CI agents

Run Thinking Machines Inkling through Vercel AI Gateway

Plan Next.js upgrades before the July 20 security patch window

Run Playwright tests faster on Vercel with Endform

Give Vercel agents their own inbox with AgentMail

Build X bots with Vercel Chat SDK

Repair Vercel build settings from the CLI before redeploying

Generate editable Seedream 5.0 Pro images through Vercel AI Gateway

Cut LLM routing waste with Vercel AI Gateway provider sorting

Use Vercel Connect to stop storing bot tokens in Chat SDK projects

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