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TypeSafe AI
@typesafeai
An AI lab building intelligence beyond chat.
15 Following    169.4K Followers
the creativity and productivity coming out of @coderabbitai 's Jev hackathon was nuts. lots of great tidbits in their video!
Congrats to TypesafeAI on the Series A! At the first ever Jevathon, we watched developers build some seriously impressive apps on their new System One model. Can't wait to see what's next!
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can we offer you a TypeGlizzy in these trying times?
hmm maybe a benchmark is okay if it makes you hungry
Is this a hot dog? find out what your favorite LLMs said over at
who benchmarks the benchmarkers? a good eval is: - ephemeral. it snapshots a moment in time and capabilities. - grounded. it directly measures performance on tasks and data you care about. - specific. it operates on the desired results and not some proxy of them. take notes!
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Typesafe's CEO @CompleteSkeptic does not trust public benchmarks. Neither do I, Diogo. So @p0 and I wrote a blog evaluating 8 decision models on real company training datasets we have personally audited and iterated on. For what it's worth though, Jev is still on top 👑
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pouring one out for everybody who thought einstein was running their agent and came back to mr bean
(cmd-) f the world indexing got you down? can't find your keys? f that. no really, f that Jev's got your back (demo replay for those who missed JevDay!)
our CEO @CompleteSkeptic tells the tale of Dr. Einstein and Mr. Bean > if AI responds like Einstein 95% of the time and Mr. Bean 5% of the time, how are you going to automate anything with it? @mattturck talks us through a wild first month of Jev
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Crazy launch! Copycats! Massive round! On the one-month anniversary of the launch of Jev, we unpack it all with @CompleteSkeptic, CEO of @typesafeai: what Jev is, how it fixes what's broken in AI, and why the fast-followers are missing the hard part. 00:00 “95% Einstein, 5% Mr. Bean” 1:09 Why intelligence per dollar matters 3:25 Why TypeSafe built in stealth for two years 5:50 “We could have had AGI last year” 6:48 Why the product carries the marketing 9:33 What is Jev? Machine-native AI, built for software 10:53 System One vs. System Two 12:26 From simple decisions to composable AI 15:21 Automating email: giant prompts vs. smart if-statements 20:03 Probabilities, thresholds, and developer control 23:43 Why Jev is faster and cheaper than chat models 25:39 “Classification is AI-complete” 27:16 RLHF: how OpenAI trained models to please humans 31:28 Sycophancy, refusals, and the hidden costs of RLHF 34:22 RLVR: why benchmark gains don’t mean reliable automation 37:51 RLCD: optimizing for machine-native intelligence 39:54 Why TypeSafe builds its training data in-house 41:49 The Bitterest Lesson: define the task before scaling 44:39 Building Jev from open-weight models 45:56 Is Jev just a classifier? Why that’s a compliment 48:35 “Build prod, not God” 50:11 Embedding AI in software, beyond coding assistants 53:05 Jev’s copycats: matching the interface vs. the intelligence 55:33 Why benchmarks mislead the users they should help 58:37 Open weights vs. APIs: how TypeSafe weighs the tradeoff 1:00:04 Jevons paradox: a new market for machine intelligence 1:02:50 Why Diogo is skeptical of recursive self-improvement 1:04:47 Can practical automation avert an AI winter?
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not a second stopped in bat country
Jev can cross America navigating by street signs alone Here's it completing the Cannonball Run from NYC to LA, picking a direction at every turn, given just a destination address and the name of the street it's on
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Jev 1.14 is now on OpenRouter. Per @typesafeai this release is "beautifully boring": • Everything: a tiny bit better • Multilingual: the biggest upgrade • Multimodal: it can see now (experimental) • Price: unchanged ($0.042/M input, output free) • Drama: none
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Filtering is the expensive half of a news digest. Every article needs a judgment call, and a judgment call has always meant an LLM call. Not anymore. $0.00004 per article. We teamed up with @n8n_io and built a weekday AI brief using @typesafeai's Jev. Now live on n8n blog as part of their Verified Node Spotlight. 🧵
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funny, suddenly all of these dynamic designs, structured workflows, and knowledge task solutions are appearing faster and faster, as though it were dramatically easier to automate them. wonder what happened 🤔 great work @Lovable
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If your app doesn’t have AI features you’re ngmi We made them simple to build: just ask Lovable. Now powered by even more models from @claudeai, @firecrawl, @GeminiApp, @OpenAI, @perplexity_ai, @p0, and @typesafeai.
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New @typesafeai Jev capabilities! Some decision models can ask questions about images but can they ask questions with images? 🧵 How to get the most out of the new Jev launch
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we announced Jev 1.14 on 10.14 at 1:14pm PT 🔥 a new and improved model, along with experimental features for our dreamers: • images • a new box type • longer context surprise, Jev was already able to see you! 👁️ BUT our bar for production-grade intelligence is quite high, so builders beware, these are preview features. enter the ~*~ danger zone ~*~ at your own risk. 🚨
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Jev was multimodal all along Yep, the Jev you know and love was an image model this whole time. We just chose to disable it because models tend to be less intelligent on other modalities. Header: TypeSafe-Danger-Zone-Images: true
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Here's another JEV TIP in honor of JEVDAY Jev can answer as many questions as you can fit into context in parallel. You can ask hundreds in one call, and since output is free, why not? 100 questions on a 32k token input document: ~$0.00001 per question ~1ms per question
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Today we're announcing that Modal has crossed $1B in annualized run rate, as well as raised a $750M Series D at a $15.75B valuation, led by @Accel. Since our Series C, usage has tripled and we’ve grown more than 15x year-over-year. We are deeply grateful to the developers and companies building on Modal. There's still so much more to build, and we can't think of a better time to be building software.
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jev can help significantly to reduce alert fatigue
we told @a16z we wanted to put intelligent software everywhere they asked how much compute that would take we said Uh Yes. announcing our really big Series A
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