I should probably also mention, @dragonfly is investing in @typesafeai's latest round! :) My quick thesis on decision models, since I've been having a lot of conversations about this lately: LLMs are amazing because they are fully general. You can use them for pretty much anything. But they are slow, expensive, and too unreliable to embed in software at runtime. Unless your product is literally chat, real-time LLM calls are unworkable for the majority of use cases. (Especially in finance!) Decision models change that. To abuse an analogy, they are the ASICs of LLMs. They give up the generality of an LLM, but in exchange for constraining your outputs, you get MASSIVE gains in cost-efficiency, throughput, and latency. In the early days of the AI boom, people understandably tried to shove LLMs into everything. But like with ASICs, you will eventually constrain your problem enough to burn it into the machine. Once your problem is an if-else, a buy or sell, a label, a choice, or a well-defined state machine like an onchain smart contract, a decision model will clobber the LLM on cost, speed, and reliability. Most systems are not language-in, language-out. Going forward, LLMs will write our code (since coding is high-dimensional and general), but that code will embed decision models to make runtime software intelligent and capable. That's the bet we're making with Typesafe. They identified this path and proved that it works. 25%+ of the Fortune 500 is already using Jev, and it launched less than a month ago. Of course, there are murmurings on the timeline that decision models are easy to copy. OpenAI, Microsoft, Amazon, and Cloudflare have all launched decision models in the weeks since Jev launched, realizing that this is going to be an enormous market and they don't want to lose it. To be sure, anyone can lop off the last layer of Qwen, fine-tune it to create a classifier, and copy the Typesafe SDK's API. But there's a lot more that goes into a world-class decision model, and there's a reason why Jev is still cheaper, faster, and more general than these other alternatives. (Decision model benchmarking started all of 10 minutes ago, but if you ask devs who've tried them, they'll tell you Jev is far and away the best right now.) There's no guarantee that lead lasts forever though. Decision models are too big of a market to be able to coast into a monopoly. From here, the onus is on them. They have to keep training better models ($$ helps), ship great products, serve their models better, faster, and cheaper than anyone else (many more tricks there), and win developers with their community-first philosophy. But they've been at this for years and have a lot up their sleeves (they were expecting a bevy of copycats if Jev took off). Diogo knows from his years at OpenAI how to sustain a research advantage. And as with all startups, focus is how you beat the incumbents. Super bullish on this team. And if you're a dev and you haven't tried Jev yet, get on it.