What Is Hyperagent? How to Use Airtable's AI Agent (5 Builds)
Hyperagent is the AI agent from Airtable's team that gets its own computer, browser, and tools. Here's what it is and how I used 5 prompts to build real work.
I gave Hyperagent five prompts. It published a real landing page, turned my website analytics into a live dashboard, designed six thumbnails from a face reference, built a watchdog that tracks ten competitor channels every week, and researched a batch of Y Combinator startups against my investment thesis.
Not five drafts. Five finished things, most with a public URL I can open right now.
I've built AI agents before. OpenClaw on my own server, Hermes on a cheap VPS. Fun to show off, and I never trusted the output enough to hand them real work. This one felt different, and the reason is boring on paper but changes everything in practice: each agent gets its own computer.
Here's what Hyperagent actually is, how to prompt it so the first result is usable, and the five things I built.
What Is Hyperagent?#
Hyperagent is a product built by the team behind Airtable. It's a separate product from Airtable itself, so don't picture a spreadsheet. Picture giving an AI agent a full computer of its own.
That agent gets a cloud machine with a browser, a file system, code execution, integrations to your tools, and the ability to publish. So a single conversation doesn't end with the agent describing what it would do. It ends with a webpage that's live, a dashboard you can share, or a folder of images you can download.
The second half is what makes it stick. Once a workflow works, you save it as a named agent with its own identity, tools, memory, and a rubric for what "good" looks like. Then you give it a trigger. It can run from a thread, a schedule, an email, Slack, Telegram, a webhook, or an API call. A weekly research brief runs every Monday on its own. A landing-page builder waits until you hand it a finished brief. The one-off build becomes a coworker that shows up on its own.
This post comes from a video Hyperagent sponsored. They gave me credits to build with, and everything below is a real thing I made during that build, not a feature list read off their site.
How to Use Hyperagent (the prompt structure that actually works)#
The demos you see online use one-line prompts. "Build me a landing page." That's also why those demos look generic and invent facts. A one-liner gives the agent no source of truth and no definition of done, so it fills the gaps by guessing.
The fix is to write the prompt like a short operating brief. The prompts I used all share seven parts:
- Role and outcome. Tell it what expert to act as and what finished result you need.
- Source of truth. Name the files, integrations, and sources it may use, and what it may not invent.
- Deliverables. Spell out every artifact, format, size, and link you expect back.
- Decision rules. Define the math, the ranking logic, the thresholds, and what missing data means.
- Design constraints. Give a concrete visual direction and list the generated-looking patterns you don't want.
- Quality gate. Make it verify links, math, layouts, and image identity before it publishes.
- Trigger and stop conditions. Say when the saved agent should run, when to stay quiet, and what still needs your approval.
That structure is the whole game. It's longer than a demo prompt on purpose, because it hands the agent room to make design and build decisions without leaving room for it to make things up.
The 5 Things I Built#
A published landing page. I pointed it at my product, Sevenposts, which turns one photo into a week of on-brand social posts. I handed it the logo, real product screenshots, a before and after pair, and a full seven-post output, then told it the price and the destination URL. It designed and published a responsive page, kept my images untouched, wrote the copy, and returned the live link plus three alternate headlines to test. If you want to see the product it built the page for, Sevenposts is free to try.
A live traffic dashboard. I gave it a cleaned analytics workbook from my site and asked for a decision tool, not a pretty report. It reconciled the numbers, built the charts, kept two data sources from being blended into one misleading total, flagged where measurement was incomplete, and ended with the three highest-value actions. Then it published the dashboard at a URL.
Six YouTube thumbnails. I uploaded a small library of face references and asked for three creative directions with two variations each. It generated six finished 1280x720 thumbnails with the hook text baked into a single image pass, ran identity and text and crop checks, and ranked the top three while keeping all six.
A weekly competitor watchdog. This one is metadata only by design, so it never watches a video or pulls a transcript, which keeps the cost low. It tracks ten channels in my niche, finds what they published last week, spots the outliers, and proposes three differentiated video ideas with evidence. Saved as an agent, it runs every Monday morning and only pings me when something actually moved.
A YC investment analyzer. As an angel investor, this is the one I keep using. It researched a curated shortlist of Y Combinator companies against my thesis, ranked them, deepened the top ten, and produced a research hub, a 2x2 map with real logos, an investment-committee deck, and one-page tear sheets. It never invented traction or valuations, and it labeled every claim as evidence or interpretation.
Five prompts, five real outputs, each one savable as an agent that keeps running.
The Honest Take#
It's not free of tradeoffs. Research-heavy builds burn credits, so review the plan and cost estimate before you approve a big run. The heavier the task, the more it costs, which is the right tradeoff when the output is a finished deck but worth watching on routine jobs.
The bigger rule is about trust. Give it real files, but never paste analytics logins, API keys, or private deal terms into a screen recording. And keep an approval step on anything that leaves your control, like sending an email or posting publicly. Skipping that review is one of the AI automation mistakes that bites people first.
Who it's for: solopreneurs and creators who are tired of watching agent demos and want the agent to actually ship. If you've run agents that felt like a toy, the own-computer setup is the difference. I said the same thing after running Hermes as an always-on agent on a cheap VPS, and this takes that idea further because publishing and memory are built in. If you're still assembling your stack, my roundup of the best AI tools for solopreneurs is a good place to start.
Get Everything From the Video#
- Get $500 in Hyperagent credits (first 500 signups): hyperagent.com/moe
- Free guide with every prompt and the framework from this video: The Hyperagent Playbook
- Try Sevenposts free, the product it built the landing page for: moelueker.com/sevenposts
The unlock was never that AI can think. It already could. The unlock is that it can now do the work on its own machine and keep doing it after you close the tab.
Watch the full walkthrough on YouTube: https://youtu.be/ajn5NzzLCAw
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