Dalton Caldwell

Congrats to @getreflex (W23) on their $14M Series A! They build the platform companies use to create custom software around their own operations. Reflex started as an open source framework for building web apps in pure Python. Now the same platform takes a business problem all the way to a working app, with AI writing the software and Reflex engineers putting it into production. The open source framework has now passed 29,000 GitHub stars, powers internal tools at ~30% of the Fortune 500, and has been used to build more than 1 million apps. reflex.dev/blog/series-a-ann…

We're announcing the public beta of datavendor.ai We spent the last two years building the best solution for people buying and selling data, whether you're a researcher in a lab or a company trying to sell data. Data is the fundamental bottleneck for AI progress, and DataVendor will be the infra that solves it.

We built a $150M ARR business twice. The first time took 8 years. The second took 2.5. Today, Podium crossed $150M in AI annual recurring revenue. Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building. And we decided to start over. The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete. As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it. When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow. But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers. Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers. We massively underestimated what we'd signed up for. We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium. Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated. When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business. We effectively started a second startup inside an already successful company. And we're still at the very beginning. Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them. And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades. Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big. In the age of AI, you can either disrupt your own company or wait for somebody else to do it. I'd rather do it ourselves.

Today we're launching MagicOS. And we've come to the conclusion that designers are NOT getting replaced. most of the industry moved to the same answer this year: give the agent its own canvas, let it run, hand you the output. we made a different bet: the canvas should be yours and the agent is your collaborator. that’s MagicOS. most AI design tools are a linear conversation: prompt, generate, iterate, repeat. a hundred prompts in, you might have a great final design, but the reasoning, rejected directions, and inspiration that got you there are buried in a chat log nobody will ever scroll back through. MagicOS is a persistent, spatial canvas. Your PRD, inspiration images, design system, variations, rejected directions, final picks - all of it lives together, all in one place, instead of stacked on top of itself and lost. it’s voice-first. talk to it in real time and watch work land directly on the canvas as you speak. it’s also multiplayer. your whole team works on the same canvas together. and it still runs on your design system and components because none of this matters if the output doesn’t look like your actual product. three months ago, this was internal only at Magic Patterns, my co-founder's weekend project. it’s now live for everyone. Design everything, everywhere, all at once.

Introducing Mo, the world's first AI QA engineer Point it at your app and 100+ agents bug bash it in parallel. Every bug comes back with repro steps, logs, and a video In our evals vs Codex with Playwright MCP: → 3.8x more bugs → 9x more bugs per hour → half the cost per bug RT + reply "Mo" for $250 in free credits. Drop your app URL, Mo will bug bash it and DM you the report today

Today we’re Releasing Weave Router 2.0. Weave Router now performs better, faster and cheaper than GPT-6 Astra on Terminal-Bench and SWE-Atlas.

when we started Archil back in 2024, the roadmap was super simple: build the world's best file system, partner with application teams to purpose-optimize for them, and then launch a compute product to deliver best-in-class price/performance the workloads we were building for were slightly different (we couldn't have anticipated post-training models on bash driving unimaginable new demand for file systems), but the roadmap has stayed the same we're really excited for how real, network addressable compute allows us to simplify how our users build higher-level infrastructure on top of Archil. persistent sandboxes will make it as simple as pressing a button to get your own: - agent hypervisor (running a "brain" loop w/ secure bash "hands") - postgres database - or even a "cursor origin"-like git remote it's deeply important to us that we're not only serving the best agent builders today, but that we're also building the substrate which will allow agents to build and manipulate stateful infrastructure themselves persistent sandboxes are the first step in that journey. please check them out, we're excited to see what you're able to build!

I'm super excited to share that we have raised $250M at a $2.3B valuation to build a LOT more AI compute capacity in orbit 🚀 Thanks so much to our supporters, including Manhattan West, who led the round, and new investors, @NVIDIA, @Cisco_Invests, @CedarCapital, Goanna Capital, and @Standard_Cap, as well as continued investment from existing backers @Benchmark, @EQTVentures, @Soma_Capital, @NFX, @SevenSevenSix, and others. Next week, @Starcloud_ will move into a new 100,000 square ft facility that will enable us to ramp up our production rate to 100 satellites/week. This is just the beginning! @EzraFeilden, @AdiOltean🏃🏻‍➡️🏃🏻‍➡️🏃🏻‍➡️

We filmed three data engineers in their natural habitat. Not shown in the doc: > Monitoring a pipeline that was 'definitely fine' five minutes ago. > Reading logs like they’re a crime scene. > Doing recovery math while someone asks if the dashboard is up to date yet. Moving data is easy. What’s difficult is keeping data correct and current, and knowing how to recover when pipelines restart, schemas change, or data falls behind. That’s why Artie now has a Free plan: so anyone can run real-time replication without building and operating the infrastructure themselves. Deploy a pipeline and watch your data replicate in real time. Try it: go.artie.com/free-plan