@Uniswap There's a real difference between value that operates onchain and value that just settles there. The first changes how systems compose. The second mostly changes the venue.
@Tenacious_DeFi@MintbuilderES@Zeus_Lobster Already shipping while most are still talking about it. AI is making this possible for builders like you who just get to work. 💙
For most of computing's history, building software meant learning to think like the machine.
Tools that flip that — letting the machine meet the person where they are — expand who gets to build at all.
https://t.co/QsY2Mloa6e
what if building apps felt less like typing or coding, and more like playing?
a new way to build apps. coming soon to a Wabi near you.
comment with your app idea and we'll send you an invite to join wabi
Onboarding shouldn't be an obstacle.
Resources like these from @Fortune__ONE make it easier for new users to take the first step with confidence. 💙
https://t.co/UXnolHuktE
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@venturetwins Moodboards as style guides for generation is a smart idea. It connects the visual intuition you already have to the output, instead of trying to describe an aesthetic through a prompt box.
@garrytan The epistemology layer is interesting, not just what's similar, but who believed what and when. That's where it stops being a search tool and starts being something else.
An agent, mid-task, identifies that it needs paid data. It looks up the source, completes the purchase, and continues with the work. The transaction is a step in a larger workflow, not the workflow itself.
This is what people mean when they say agentic commerce will mostly happen behind the scenes.🦾
https://t.co/7QdO5pSvxt
@patrickc An interesting question now is what the trust and permission model looks like at scale, when agents are making hundreds of these decisions autonomously.
Markets can only be as open as the access to them.
Access can only be as open as the code underneath.
The deepest layer is what determines what the surface can be. 💙
https://t.co/vNZ4kxccYr
1. Capability gains have been concentrated in domains with verifiable outcomes, like code and math. These are the areas where reinforcement learning can be applied at scale.
2. Frontier models and consumer-tier models have diverged sharply over the past year.
The result: a widening gap between what AI can do and what most people believe it can do.
https://t.co/eT2MAT2eyi
Two tools, one workflow: image model generates the panorama, agent builds the viewer to explore it.
The building blocks are getting better individually, but the bigger story is how they're starting to fit together.
https://t.co/ZXwyDjw4Ja
GPT-Image-2 can be used to make full panoramas 🤯
Prompt for a "360 equirectangular image" of a specific place - I asked for Akihibara at night.
Then I had my OpenClaw agent build a viewer in the browser so I could easily upload the image, pan around, and zoom.
@ilblackdragon Agents that can't be trusted with credentials or assets will always hit a ceiling. The infrastructure layer has to be built for trust from the start, not bolted on later. 👏