We forked the @CantonNetwork quickstart, built a live invoice factoring demo, and wrote up everything we ran into and learned.
https://t.co/IKes5qTq4p
Built by @yachtyyachty . Go break it.
I use @blackbird weekly to find new local LA restaurants while also earning dining rewards. It's a dream scenario for the @Lazer_HQ team where we get to build and use one of our client's products everyday.
You walk into a restaurant. Open the Blackbird app to check in and pay. Earn points.
That's @Blackbird.
Here's why we're excited about how they're improving the restaurant experience for customers and restaurant operators.
@AtownBrown Just post a link to that site in Claude code and ask it to pull the favicon, image assets, style guide. You can grab a lot from the render html
Enterprises are spending millions on subscriptions to Anthropic, OpenAI and other AI tools. Most are hitting the same wall: they bought the technology and haven't seen the ROI.
The gap isn't the technology. It's the implementation.
Dropping an LLM into an existing workflow doesn't transform it. It just adds a layer. The real unlock comes from rethinking the workflow itself.
This is where process engineering has become the most in-demand AI engagement in enterprise. Before a single agent gets built, someone needs to map how the business actually operates. Where do tasks bottleneck? Where is human effort being spent on work AI could handle? Where does judgment still need to stay human?
Think of it as the "Enterprise Process Engineer" role. Part systems thinker, part operator, part technical builder. Their job is to identify the highest-leverage workflows, map data flows, define the future-state process, then deploy and manage agents against it.
The economics are compelling if they can be realized. ServiceNow has reported hundreds of millions in AI-driven savings. Block is targeting $2M in gross profit per employee, up from $750K a year ago. But those results come from re-engineering operations, not simply from buying a subscription.
For every dollar enterprises spend on software, six are spent on services. The companies that can audit operations, identify automation opportunities and deploy agents against them will capture an enormous share of that spend.
The hottest trend in enterprise AI isn't a new model or product. It's the unsexy work of understanding how a business runs and rebuilding it for a world where intelligence is cheap. Companies that audit their processes, redesign their workflows and deploy agents against them will capture the most value from AI.
The transformation isn't coming from the tool. It's coming from the work.
I experimenting with a new idea, it involves social, current events, prediction markets, perps, options etc.
I am looking for some people to do 15 min calls with to demo what I am building and get first reactions and feedback on what would get you to use this
If you are open to chatting with me please hit my dms
We need more innovators building and testing ideas onchain.
That's why I pushed our Crypto team at Lazer to explore how we could easily equip agents with the needed context and skills to build and publish apps on @base, @farcaster_xyz, and soon @worldnetwork
That evolved into the Lazer Mini App CLI. Simply install, run /lazer, and describe what you want. The agent handles auth, wallets, contracts, onchain data, and any platform adapters needed to publish your app.