Community

Vercel's CDN can front any application, not just those deployed natively on the platform, and it's simple to set up. This allows you to add firewall protection, DDoS mitigation, and observability to platforms like Discourse or WordPress without migrating them completely. The Vercel Community is an example of this architecture. It is a Discourse application hosted elsewhere, but we proxy it ourselves via Vercel's CDN, which both protects the app and gives us access to useful features in Vercel's website stack: Web Analytics gives us anonymized, cookie-free demographic and referrer data, so we can see where users are coming from and what they're looking for. Firewall gives us DDoS protection and has automatically prevented several attacks in the last year. Bot Management lets us block malicious scrapers while allowing trusted crawlers to index the forum and allow community posts to show up in ChatGPT searches. Some parts of the community platform, like Vercel Community live sessions, run directly on Vercel with Next.js. We use Vercel Microfrontends to mount a Next.js app on the same domain as the Discourse app, for three reasons: To create new pages that would be impractical to implement as CMS plugins. To overwrite existing Discourse pages that we can't fully customize. To keep users authenticated through Sign in with Vercel When the new pages are ready to launch, we add the path to our microfrontends configuration and users are rerouted seamlessly on the next deploy. Vercel as a CDN To set up Vercel as a CDN proxy like this, you need two domains: Inner host: The origin server where the site is actually hosted. This might look like your-site.discourse.com Outer host: The Vercel project domain that users interact with, such as community.vercel.com Ensure that all links on the site and its canonical URLs use the outer domain. Once those are in place, create a new project on Vercel that deploys to the outer host. You can then use vercel.ts (formerly vercel.json) to rewrite traffic to the inner domain. Running multiple apps on a single domain with microfrontends To extend the community forum beyond the limits of Discourse, we configured with the outer host domain using a vertical microfrontend approach. Vercel's microfrontends allow you to mount different Vercel projects to different route paths. We added a microfrontends.json file that directs traffic for specific routes to separate Vercel projects. Additional pages can be added incrementally, route by route. We also added the .well-known/workflow route to use Workflow Development Kit for event creation and video processing. While you could accomplish some of this by using negative matching in the proxy regex to avoid proxying certain routes, splitting the projects provides better isolation. This approach allows for independent environment variables and organization permissions, locking down the project that talks to the third-party host. A modern CDN without a massive migration At this point, you have Vercel's CDN standing between your users and your origin server. All traffic flows through Vercel's global network, giving you enterprise-grade security without touching your existing application. You get even more flexibility when you combine this with microfrontends. You now have a path to modernize your application incrementally. Instead of a "big bang" refactor, you can create a Next.js application and turn on specific routes one by one, while your core application continues to run on Discourse, WordPress, or whatever platform it is built on. This architecture unlocks a pragmatic path forward: secure your existing investment with Vercel's CDN today, then layer modern features on top tomorrow, all without the risk of a full platform migration. Learn more by reading the Vercel microfrontends documentation or see it in action at community.vercel.com/live.

Jacob ParisDX Engineer

At Vercel, our developer community is at the heart of everything we do. It's how we stay closest to the people using what we build. As our community grew, automation helped us scale. But questions still got lost, routing took time, and context switching pulled us away from the work that actually required our expertise. And automation could never help with the things that mattered most, the moments where you really connect with someone and help them. You can't use AI to replicate the feeling of talking to a person who really cares. So we built agents to take over the routing, triage, and follow-ups that don't need a human. We call this the Community Guardian. Let's talk about what it does, how we built it, and how anyone, including non-engineers, can ship agents too. The Community Guardian operations layer When a new post comes in, the Guardian analyzes it, checks for duplicates, and assigns it to the team member with the right specialty and bandwidth. Each person handles up to 10 questions before new ones go to someone else, keeping the workload balanced across time zones. Nothing gets overlooked. If a question goes unanswered for 48 hours, the Guardian reassigns it. It sends reminders when we're waiting for more information and detects when conversations are resolved. Under the hood, the Guardian uses Claude through AI Gateway and runs on Vercel Workflows, which lets it check in every 10 minutes and sleep between cycles without consuming resources. That handles the operations side, but our team still needed better context to respond well. The intelligence layer: c0, the research assistant While the Guardian manages logistics, c0 is the agent that goes deep on research. It lives in Slack, where our team already works. When a team member needs context on a thread, c0 searches our knowledge base, documentation, GitHub issues, and past discussions to put together a context package. The context package helps our team respond faster and more accurately instead of relying on their own memory. Beyond individual threads, c0 helps us close the loop with our product teams. It tracks community sentiment and recurring technical hurdles, so rather than someone spending hours auditing a week's worth of posts, we can ask c0 for the "top product feedback" and bring real data to our product conversations. Reclaiming human focus In its first 23 days, the system helped 281 unique users: Metric Outcome Initial context gathering 4,716 first responses triaging issues and gathering logs before a team member arrives Thread revival 1 in 8 "ghosted" threads brought back to life, resulting in 23 confirmed solutions Operational scale Over 1,400 agent runs in a recent two-week period, from stale-checks to auto-solving Duplicate detection 4 duplicate threads detected via vector similarity, with 3 auto-closed at 95%+ confidence Every substantial answer still comes from our team. Agents handle everything else around those answers. Without the repetitive parts of triage and tracking, our team can spend time on complex pair-debugging and relationship building, creating content for the broader community, or just having fun with the developers they care about. Build your own You don't have to be a developer to build something like this. You just need an idea. I'm not an engineer. I manage community and talk to developers. Sure, I understand the problems we're solving, but I'm not writing production code every day. My idea started at a talk in Zurich where I showed how we were automating community workflows. But that was traditional automation, scripts and rules and if-this-then-that logic. It worked, but it was brittle. Every edge case needed a new rule. I wanted something smarter, so I started experimenting with my coding agent to add a thinking layer, the step between "new post arrives" and "take action." Instead of "if post contains 'billing' then route to billing team," it became "read this post, understand what the person actually needs, then decide." The thinking layer is like another DX engineer looking at each post who can read between the lines when a user says "it's not working," connect dots to a GitHub issue from three months ago, understand when someone's frustrated vs. just confused, and know when to escalate vs. when to gather more context. Building this way meant I could describe what I wanted in plain English, get working code back, test it against real community threads, and iterate. I wanted to use different models for different tasks, give our agent access to read our docs and community, and allow it to suspend, resume, and recover if something failed. Instead of building all of that from scratch, I described what I needed to my coding agent and landed on AI Gateway, AI SDK, and Vercel Workflows, which already handle those complexities. The prompts that built it The first prompt was the core idea: "Build me an agent that helps me with the community, day-to-day operations like assigning posts and formatting. I don't know which model will work best yet but make it easy to switch without needing new API keys. Use the AI SDK for the agent." From there, the prompts got more specific as I understood more about what I was building. "And triggers every 10 minutes, I want to check for the latest threads." I'd started with cron jobs, but switched to Vercel Workflows for this. The durable execution meant the agent could suspend between checks and resume exactly where it left off. "Make sure we're rotating assignments every 4 hours." Every prompt unlocked the next question. I wasn't following a tutorial or docs. I was having a conversation, and the system grew from that conversation. You don't need to know the right terminology or how to code. You just need to know your problem well enough to describe it and be willing to iterate when something doesn't work the way you expected. The thinking layer turns automation from "follow these exact rules" into "understand the situation and make a judgment call." Build with heart Community is about people, and we want our people to have the time and energy to show up fully, building with and for the developers in our community. If you want to build something similar, we built c0 with the Chat SDK, a unified TypeScript SDK for building agents across Slack, Teams, Discord, and more. The Guardian uses Vercel Workflows for durable execution. Come share what you build in the community. We're always happy to talk through what we've learned.

Pauline P. NarvasHead of Community Platforms

On April 16th, 39 teams took the stage to pitch investors at Demo Day. During the prior six weeks, founders worked shoulder-to-shoulder with the Vercel team, our partners, and industry leaders to shape their ideas into the next generation of AI applications. Six weeks with the 2026 cohort Teams from around the world joined the 2026 cohort, building agents, developer tools, consumer apps, and vertical AI for finance, security, healthcare, and robotics. Each week, the cohort joined two sessions: a hands-on technical workshop and a fireside chat with an external speaker. The workshops covered the technical side of building AI products, from agents and models to deployment and scale. The fireside chats brought in industry leaders, Vercel experts, and investors. Speakers included Peter Steinberger (OpenAI/OpenClaw) and the Windsurf team, with topics ranging from the state of AI to pricing, legal, sales, marketing, and fundraising. Builder day Halfway through the program, the cohort came together with the broader Vercel startup ecosystem for Builder Day at Vercel's office. The day combined technical workshops, hands-on office hours with engineers from accelerator partners like AWS and Anthropic, open time to build and connect, and a special fireside chat between Malte Ubl (Vercel CTO) and Stephen Haney (Paper CEO). $8M in infrastructure and credits Beyond the programming, every team got over $200K to build with on Vercel and across the AI stack: Vercel AI stack: AI Gateway, Sandbox, Workflows, Fluid Compute, v0, and more Partners: AWS, Anthropic, OpenAI, Browserbase, ElevenLabs, Auth0, WorkOS, Notion, Modal, Neon, Supabase, and more Demo Day After six weeks of building, the cohort showed their work at Demo Day. Auth0 hosted the event at their offices, and each team had a few minutes to present to a room of VCs, AI leaders, and partners, with a panel of judges from across the AI ecosystem selecting the winners. Winners On Demo Day, judges scored teams on problem validity, technology fit, product quality, and each team's final pitch. Three teams took home $100K+ in credits and prizes, and the first-place team also received an investment from Vercel Ventures. 1st: Rex Rex is building AI for the enterprise finance back office, unifying customer context across systems so agents can run accounts receivable end to end. In addition to credits, Rex received an investment from Vercel Ventures. 2nd: Hacktron AI Hacktron AI is an AI teammate for security. As AI writes more of the code shipping into production, vulnerabilities scale with it. Hacktron integrates into the development lifecycle to find and remediate real, exploitable issues. 3rd: Roots Roots is rebuilding how people buy and sell homes. Buyers save hundreds to thousands of dollars a month, and sellers net thousands more at closing. $100M+ in fundraising, and counting The 40 alumni from the last cohort have raised over $100M in venture funding, and several have been accepted to Y Combinator. Stably, the 2025 winner, is now converting enterprise pilots into contracts and shipping new product lines in hours instead of weeks. Other teams from past cohorts, including Jigsaw Stack, Belli AI, and General Translation, have signed enterprise customers and formed partnerships through the program. Apply to the next cohort If you're an early-stage founder building in AI, you can apply for the next AI Accelerator program. We will open applications later this year. Visit our startup hub to learn more and connect with our startups team.

Alli Pope, Caroline Ciaramitaro, and 1 other