Tencent EdgeOne Makers is an edge platform for modern web apps and AI agents. Build with your preferred frameworks and deploy through familiar CLI, Git, and CI/CD workflows. Get built-in agent runtime, sandboxed tools, memory, observability, model gateway support, serverless functions, and storage—without stitching together complex infrastructure. Add AI agents to existing products or launch new AI applications in minutes. Deploy AI agents like web apps.
Hey Product Hunt 👋 Kitty here, product lead for Tencent EdgeOne Makers.
Over the past year, I've watched more and more people—including myself—start building their own AI Agents.Today, building an Agent has never been easier. A solid idea and a few hours gets you a working demo. But the real work starts after the demo ships.
Suddenly, you're hit with a wall of production questions: How do you manage memory? How do you run tools securely in sandboxed environments? How do you trace and debug execution paths? How do you scale when a hundred users hit it at once? And how do you deploy it globally so it's actually fast?
Most builders end up choosing between two painful paths: spend weeks building all of this boilerplate infrastructure from scratch, or lock themselves into a restrictive platform that dictates which framework, language, or model they have to use.
We wanted a third option. That's why we built Tencent EdgeOne Makers.
Tencent EdgeOne Makers is an edge platform for modern web apps and AI Agents. It fits into the workflows developers already know, with familiar CLI, Git, and CI/CD support. You get Agent runtime, sandboxed tools, memory, observability, model gateway support, serverless functions, and storage built in, without having to stitch together complex infrastructure yourself. In other words, you can deploy AI Agents the same way you deploy web apps.
We kept the platform completely open. No vendor lock-in, no framework constraints:
Framework agnostic: Works out of the box with Claude SDK, OpenAI SDK, LangGraph, CrewAI, and more.
Polyglot: Full support for both JavaScript and Python.
Flexibility: Use whatever model or tech stack makes sense for your application.
Whether you’re looking to plug an Agent into an existing SaaS, website, or e-commerce flow, or you're building a brand-new AI application from scratch (like an AI recruiter, sales rep, data analyst, or fitness coach)—Tencent EdgeOne Makers is designed to let you spend your time on your product, not the plumbing.
We're excited to share this with the Product Hunt community today. Give it a spin, ask us any tough questions, and let us know what you think! Feel free to join our Discord to chat with us.
Congrats on shipping this! between the build, the copy, the visuals, and then actually getting eyes on it... it's a grind most people don't see. Been in the trenches myself with a similar kind of launch recently, so I know exactly how much went into this. Wishing you success🚀
This is a compelling approach. I'm curious how you think about balancing flexibility with simplicity. As more capabilities get added, how do you avoid becoming another platform that feels overwhelming to new builders?
As we scale, "does it stay reliable under load" matters more than features. Glad to see that treated as a first-class concern here.
Going from a prototype my team is excited about to something customers can actually use has always been the slow part. This looks like it shortens that a lot.
Deploying agents like web apps is the right mental model. The part I’d pressure-test is the boundary per customer or workspace: which secrets/tools the agent gets, which writes need approval, and what receipt survives after the run.
Do those permissions live with each deployed agent, or with the app/project around it?
@kitty_lee1 Since it supports multi-agent setups like CrewAI, how detailed is the built-in observability when tracing complex, multi-turn agent loops at the edge? Can we monitor specific tool call latencies directly from your platform?
Most "agent platforms" stop at the build step. Seeing one that actually owns the run-and-serve part is what makes this stand out.
Nice launch! The deployment experience looks really clean.
One question: how do you handle long-running agent workflows? For example, if an agent needs to wait for user approval or perform multiple asynchronous steps, is there built-in state management or checkpoint support?
Multi-user isolation out of the box is a big deal for anyone serving real customers, not just demos.
The honest truth is most of us under-budget the "make it production-ready" phase by like 3x. A platform that absorbs that is genuinely valuable.
Running Web and agents from the same project is a clever architectural choice. Less to manage, fewer moving parts.
Coming from stitching together a bunch of cloud services, having this as one coherent thing is refreshing.
Congrats on the launch!
Is "sandbox" referring to the browser's sandbox environment?
This feels like a good fit for teams moving from AI experiments into production. That transition is still more painful than it should be.
🚀 Huge congrats on the PH launch, Kitty @kitty_lee1 & team! "Deploy AI agents like web apps" – that tagline alone made me click. As someone who spent way too long stitching together LangGraph + memory + sandboxed tools, I feel personally attacked by your "third option" pitch 😂
What I genuinely love:
Framework-agnostic + polyglot – no vendor lock-in, no forcing me into a specific stack. Huge win.
Built-in observability & model gateway – these are production must-haves, and you just ship them out of the box. Respect.
One actionable suggestion: since you support CLI/Git workflows, how about adding a "Deploy from GitHub template" one-click flow (like Vercel does)? Let newcomers fork a pre-built agent template and have it live in 30 seconds – that would be an absolute conversion magnet.
And a quick question for you: what's the default timeout and resource limit for sandboxed tools? Is it configurable per agent? Didn't spot it in the docs – would love to know.
Definitely spinning this up tonight. Congrats again! 🔥
For teams migrating an existing LangGraph setup that's already deployed elsewhere, how much of the agent code needs to change vs just the deployment config?
This sounds very important like Cloudflare. I wish it was clearer whether the AI agents can use EdgeOne through a CLI! Congrats on the launch :>
About Tencent EdgeOne Makers on Product Hunt
“Ship AI agents like web apps, in minutes.”
Tencent EdgeOne Makers launched on Product Hunt on June 24th, 2026 and earned 562 upvotes and 168 comments, earning #1 Product of the Day. Tencent EdgeOne Makers is an edge platform for modern web apps and AI agents. Build with your preferred frameworks and deploy through familiar CLI, Git, and CI/CD workflows. Get built-in agent runtime, sandboxed tools, memory, observability, model gateway support, serverless functions, and storage—without stitching together complex infrastructure. Add AI agents to existing products or launch new AI applications in minutes. Deploy AI agents like web apps.
Tencent EdgeOne Makers was featured in Website Builder (9.6k followers), Artificial Intelligence (473.7k followers) and Development (6k followers) on Product Hunt. Together, these topics include over 113.3k products, making this a competitive space to launch in.
Who hunted Tencent EdgeOne Makers?
Tencent EdgeOne Makers was hunted by Zac Zuo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Tencent EdgeOne Makers stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Zac Zuo
Hey Product Hunt 👋 Kitty here, product lead for Tencent EdgeOne Makers.
Over the past year, I've watched more and more people—including myself—start building their own AI Agents.Today, building an Agent has never been easier. A solid idea and a few hours gets you a working demo. But the real work starts after the demo ships.
Suddenly, you're hit with a wall of production questions: How do you manage memory? How do you run tools securely in sandboxed environments? How do you trace and debug execution paths? How do you scale when a hundred users hit it at once? And how do you deploy it globally so it's actually fast?
Most builders end up choosing between two painful paths: spend weeks building all of this boilerplate infrastructure from scratch, or lock themselves into a restrictive platform that dictates which framework, language, or model they have to use.
We wanted a third option. That's why we built Tencent EdgeOne Makers.
Tencent EdgeOne Makers is an edge platform for modern web apps and AI Agents. It fits into the workflows developers already know, with familiar CLI, Git, and CI/CD support. You get Agent runtime, sandboxed tools, memory, observability, model gateway support, serverless functions, and storage built in, without having to stitch together complex infrastructure yourself. In other words, you can deploy AI Agents the same way you deploy web apps.
We kept the platform completely open. No vendor lock-in, no framework constraints:
Framework agnostic: Works out of the box with Claude SDK, OpenAI SDK, LangGraph, CrewAI, and more.
Polyglot: Full support for both JavaScript and Python.
Flexibility: Use whatever model or tech stack makes sense for your application.
Whether you’re looking to plug an Agent into an existing SaaS, website, or e-commerce flow, or you're building a brand-new AI application from scratch (like an AI recruiter, sales rep, data analyst, or fitness coach)—Tencent EdgeOne Makers is designed to let you spend your time on your product, not the plumbing.
We're excited to share this with the Product Hunt community today. Give it a spin, ask us any tough questions, and let us know what you think! Feel free to join our Discord to chat with us.
Thanks so much for the support!