@getenergy_, previously first engineer at @lovable
San Francisco
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- Following 582
- Followers 8,732
- Likes 6,246
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I was the first engineer at Lovable. I recently left to build @getenergy_ with my good friends @gabriel1 and @da_fant.
AI is already good enough to do most of the work on your computer, but almost nobody works that way yet. We're fixing that.
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In our internal knowledge work evals, GPT 6.1 Sol is the best model we've tested.
It completed more of the work independently than Claude Opus 5.5, at 40% of the cost and nearly twice the speed, and led in every industry we measured.
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Energy can now remember your logins, sign in for you, and even pay with your credit card.
Your credentials are only stored locally, in your Mac's secure storage, and never exposed to LLMs.
We also support 1Password.
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emil retweeted
Emil is the best engineer I've ever worked with
super excited to have him onboard
I was the first engineer at Lovable. I recently left to build @getenergy_ with my good friends @gabriel1 and @da_fant.
AI is already good enough to do most of the work on your computer, but almost nobody works that way yet. We're fixing that.
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emil retweeted
It's somewhat sad that Wired's article is behind a paywall but here's my favourite part:
Stanislav Smirnov, a professor at the University of Geneva and a 2010 Fields Medalist, is Mostik’s chief scientist. He says finding common ground between two AI models is surprisingly difficult. "There seems to be no appropriate mathematical language yet," he says. In the interim, Mostik’s approach is a way to quite literally bridge the gap.
Smirnov says Mostik’s work could also perhaps reveal new things about how AI models actually function and how this compares to the workings of the human brain. Smirnov says a deeper mathematical analysis may reveal a commonality in the way both AI models and human beings reason over difficult problems.
Full article about @mostik_ai is here:
wired.com/story/russian-star…
meet @mostik_ai!
what happens when you put 12 PhDs in one room for four months? first place on the ARC-AGI leaderboard, which I can't say much about while the competition is still running. and this, which I can.
everyone's arguing about whether open models will catch up to frontier models. we think it's the wrong question. here's the one we pose: why does a frontier model have to generate your answer at all, when the only thing you need from it is the reasoning?
we do this by enabling models to communicate in latent space. through our protocol, hidden states pass straight from a frontier model into a small one running on your infrastructure -- no text between them, and neither model is fine-tuned. two models from different families, sharing reasoning, both left untouched.
how do we know it works? we tested it on a setup where a 753B model reads the problem, and a 4B edge-class model writes the answer. with this approach, we get results 80% as accurate as the frontier model, but at 20x faster performance.
we're committed to preventing frontier model lock-in and are already partnering with inference providers to accelerate open-weight adoption. we've done this between 15 of us, in four months, 12 PhDs and a Fields medalist, backed by @generalcatalyst
WIRED has the first external account of the company and the work: wired.com/story/russian-star…
full writeup, the setup, and all the numbers: mostik.ai/read-more
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thank you bun
Bun v1.4.1 reduces idle memory usage
ALT Table: "Bun v1.4.1 reduces idle memory usage." Resident memory 3 minutes after 60 seconds of sustained load, lower is better. Columns: Bun 1.4.1, change vs 1.4.0, Bun 1.4.0, Bun 1.3.14, Node.js 26.7. Next.js SSR: 142 MB (−36%), 222, 1303, 195. Vite dev: 157 MB (−17%), 189, 303, 155. Express: 54 MB (−17%), 65, 77, 81. Fastify: 57 MB (−16%), 68, 80, 91. Elysia: 44 MB (no change), 46, 69, 96. Hono: 34 MB (no change), 35, 53, 92. Method: 60 s at a fixed request rate (40k req/s Elysia and Hono, 25k Express and Fastify, 5k Vite dev, 3k Next.js SSR), 64 connections, then 180 s idle; RSS sampled every 100 ms on Linux x64.
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BREAKING: Lovable's first engineer @emilahlback has left to build @GetEnergy_ with OpenAI defectors @gabriel1 and @da_fant.
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welcome emil to the team!
he wrote some of lovables first lines of code and took initiative and led lovables enterprise efforts
its been 5 years since i last worked with him. he is the strongest engineer i have worked with, and im super excited to work together again!
I was the first engineer at Lovable. I recently left to build @getenergy_ with my good friends @gabriel1 and @da_fant.
AI is already good enough to do most of the work on your computer, but almost nobody works that way yet. We're fixing that.
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I was the first engineer at Lovable. I recently left to build @getenergy_ with my good friends @gabriel1 and @da_fant.
AI is already good enough to do most of the work on your computer, but almost nobody works that way yet. We're fixing that.
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3 months ago i resigned from @OpenAI. today we are launching Energy
everyone will soon use AI for all work on their computers, but very few do today even though AI is good enough
our users do days of work in hours. we'll onboard the world to working with ai
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emil retweeted
Excited to introduce Nativ 🚀
Run frontier open models locally on your Mac. No accounts, no subscriptions, no cloud.
⚡ Built on mlx-vlm — multimodal + fastest on Apple Silicon
🔒 100% private — every token generated on your machine
🛠 Plug your coding agents into a local endpoint
📊 Live telemetry — tokens/sec, memory, usage
🆓 100% open source, MIT licensed, free forever
Your Mac is more capable than you think. Stop renting intelligence.
Download for macOS 👇
blaizzy.github.io/nativ/
Github repo 🌟
github.com/Blaizzy/nativ
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Three years ago I was writing some of the first lines of Lovable's code, and yesterday was my last day.
Grateful for the amazing people I met and everything we built together.
More soon.
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A cat in my neighborhood has a qr code with a Lovable link around his neck
Even cats code their apps with Lovable
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emil retweeted
We’re joining YC S26 to build the easiest solution for any enterprise to build internal tools.
Blaise builds all your enterprise software, deployed on your own infrastructure. Doing the work of an entire consultancy, but faster.
Apply to become a customer: blaise.new
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