A new kind of AI model from a ChatGPT inventor is thrilling developers

A new kind of AI model from a ChatGPT inventor is thrilling developers. 25% off tickets now Back by popular demand: Save up to $300 on Disrupt Close Image Credits:TypeSafe AI AI A new kind of AI model from a ChatGPT inventor is thrilling developers Tim Fernholz 11:49 AM PDT · September 18, 2026 ChatGPT broke Diogo Almeida’s heart.

What happened

Jev, a new kind of AI model, is showing developers a cheaper and faster path to software intelligence. A screenshot shows a comparison of Jev and an OpenAI model responding to the same requestsImage Credits:TypeSafe AI Developers are taking a great interest in the product; the company briefly lost the ability to serve users from its API because demand was so high. “Half of [our company] is a lab that basically owns this entire subfield of statistically well-understood synthetic data, and that is now my life joy. ” For now, Jev stands alone as this kind of model, but Ronacher expects that competitors will spring up now that its utility is apparent.

Almeida was an OpenAI researcher who helped build the chatbot and then invent reinforcement learning from human feedback (RLHF), the model-training technique perhaps most responsible for our current age of AI. This week, the company released a new transformer-based model, Jev, that is not a large language model (LLM). It doesn’t output text, but instead produces probabilities, or what the company calls “calibrated decisions. ” Eschewing language does a few things: It makes the model incredibly cheap and fast, and because users define the outputs in advance, it cannot hallucinate.

Thus far, software developers see it as a cheaper and more robust way to incorporate intelligence into their code.

The wider picture

For example, Pranit Sharma, a software engineer at Vercel, a company making agentic infrastructure, said his company had used OpenAI’s ChatGPT Luna 5. More interesting to Mudholkar were Jev’s confidence scores — “it is the only one that hands back a real probability which makes it ideal for automating workflows! ! ” Besides replacing LLMs in certain use cases, the new model can also augment them, acting as a smart check on misbehavior. “At the end of the day, it delegates the hallucination problem a little bit to the user,” explained Armin Ronacher, the CTO of Earendil, which builds the open source model harness Pi.

But if it’s 95%, sure, then I can do something with it. ” Another potential use for Jev is model routing, Ronacher said. Predicting whether a given workload requires a specific model would be useful, but using an LLM for the job would be expensive. Jev’s low cost and speed make that kind of real-time sorting possible. The model is named after William Stanley Jevons, the 19th-century economist whose eponymous paradox describes how the falling cost of a commodity can lead to it being used more and more.

Almeida is tight-lipped about the model’s architecture, which outside observers suspect is built on top of an open-weight LLM.

What has been reported

The company refers to Jev as a “System One model,” focused on intuition rather than reasoning, and specifically focused on the right task. TypeSafe itself will be building more versions of the model, in new modalities. BOOK NOW Most Popular OpenAI caught its models leaving notes to successors to hide bad behavior Rebecca Bellan Microsoft exec called AI scraping ‘the largest theft of labor in human history,’ new unredacted filings reveal Rebecca Bellan Clean tech startup Fluxnium found a way to tap 50,000 years’ worth of nuclear fuel Tim De Chant Former TikTok execs built an app that uses AI to teach you how to pose for a photo Ivan Mehta Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear Julie Bort Jensen Huang took a call from Trump, and showed off something else, too Connie Loizos The 9 buzziest startups from Y Combinator’s latest Demo Day, according to VCs Marina Temkin Dominic-Madori Davis Loading the next article Error loading the next article

Disrupt 2026: OpenAI, Anthropic, Replit, and more take over 6 industry stages. But despite its capabilities, he was disappointed. “We have lightning in a bottle, and yet it is not useful,” Almeida told TechCrunch. It took me a while to come to the conclusion: The problem is we are optimizing for human language … We have been super good at human language for four years, but it’s not useful for automation because computers speak a different language. ” Two years ago, Almeida left OpenAI to start TypeSafe AI, a startup trying to fix that problem.

Its output tokens are free, and input tokens are metered by the billion, not the million.

What happens next

Jev appears most useful for software automation. 6 to run a classifier to review commands for safety. When Vercel replaced OpenAI’s Luna with Jev, it got results five to 18 times more quickly and with greater accuracy. Another developer, Bryo AI CTO Nikhil Mudholkar, tested Jev against Gemini for classifying business emails. In his test, Gemini was slightly more accurate, but 10 to 20 times more expensive. Using agents to monitor agents can quickly become expensive, but using Jev to do so, Almeida argues, makes sense.

He sees users deploying Jev to track LLM agent traces and prevent jailbreaks.