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The first GPT-4V-powered frontend engineer agent. Just upload a picture of a design, and the agent autonomously codes it up, looks at a render for mistakes, improves the code accordingly, repeat. Utterly insane.

1,370,425 次观看 • 2 年前 •via X (Twitter)

10 条评论

Matt Shumer 的头像
Matt Shumer2 年前

Built this after seeing the results of the text -> design agent I built yesterday. We’ll have a whole new frontend stack soon!

Robert Scoble 的头像
Robert Scoble2 年前

@artificialguybr This is so intriguing. So much is about to change. Thanks for showing it to us!

Matt Shumer 的头像
Matt Shumer2 年前

@artificialguybr Absolutely… insane times we’re living in.

Furkan Gözükara 的头像
Furkan Gözükara2 年前

Very primitive cherry pick demo

Matt Shumer 的头像
Matt Shumer2 年前

Yes :) In all seriousness, what I’ve found to hold true in AI is that once something is good enough to demo, with iteration and tweaking (and model progress) you can expect it to become something really amazing. This feels like something that will be huge in a year or two.

Kristoph 的头像
Kristoph2 年前

I love how chatGPT codes just like any other developer. It makes it looks sort of like the design but not exactly like the design 🤣

Matt Shumer 的头像
Matt Shumer2 年前

😂 this hits hard

Andrew Durot 的头像
Andrew Durot2 年前

Wait I'm confused? This is yours or a open source? How you access gpt4 image? Through a headless browser?

Matt Shumer 的头像
Matt Shumer2 年前

Just built it for fun! Not open source, sorry

Jason Staats⚡ 的头像
Jason Staats⚡2 年前

Can we call it Enhance

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i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

Akshay 🚀

118,124 次观看 • 1 个月前