Cofounder & CTO https://xitter.cf/t.co/SsAv0DJQS3 • Cofounder https://xitter.cf/t.co/0In4mwY8NF • Brooklyn, NY • formerly Microsoft, Thomson Reuters, Agility • Blog: https://xitter.cf/t.co/KnZX8DMqlp
New York, NY
Joined March 2026
- Tweets669
- Following223
- Followers34
- Likes968
Cheng Lou's Handwired compiles plain JavaScript into a neural net: no training, exact results, runs in a browser.
The part worth stealing isn't the trick. It's that type declarations decide how big the network gets. #MachineLearning #JavaScript #WebGPU
Caveats: compiling programs into weights has precedent (DeepMind's Tracr, 2023). And gradients through step functions are ~zero almost everywhere, so training tunes constants more than it learns logic.
Practical payoff: branch-free code is what GPUs want. Regex + JSON parsing written as single-threaded JS runs as WebGPU kernels over 100k documents.
chenglou.me/handwired/
This essay "Taste" by @saranormous moved me when I first read it but it lands harder now, where our moat as founders is really just our taste. You ARE the moat! So read this because it might be exactly what you need to hear: saranormous.substack.com/p/t…
A few quotes below 🧵1/3 :
"The relentless, almost painful ability to know what should exist, what shouldn’t, and where quality matters. It’s the difference between shipping a product and shipping a point of view." 🧵2/3 #founders #startups #ProductDesign
"The best founders understand that taste is a competitive advantage that compounds. It runs deeper than pixels—it’s in your codebase, your culture, your cap table." 🧵3/3 #founders #startups #ProductDesign
Neat daily lesson from MindStaq today (these are short lessons that get shared in my Today screen based on my role - as a cofounder/CTO)
The 90-day promise audit
Once a quarter, list every commitment you made out loud — to customers, investors, candidates, your team — with the date you said it. Anything without an owner and a date is a wish wearing a promise's clothes. The audit takes an hour and usually reveals two or three things you've quietly stopped believing in but never withdrew. Suggestion: Block an hour this week; the list doubles as your real roadmap and your next investor update.
Sai Prakash retweeted
A 40B coding model running more than 125 tokens a second on a MacBook, at short contexts. Open weights, Apache 2.0.
@recursive_si had their own AI research system help build it, from scratch, in under four months.
I've wanted to do all my coding locally for years.
This gets close.
🤝 Paid partnership
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
Sai Prakash retweeted
We open sourced a *really fast* HTML artifact builder. It's powered by libfx, making the agent durable.
Building the low-level plumbing for v0 to survive server crashes, flaky LLMs, function limits was a huge pain.
Now it's easy, free, and OSS: fx0.vercel.dev.
PS: I built this floating container in a few minutes… it's delightful, and it's just HTML!
We built a 'mini v0' on libfx to showcase its speed and durability:
• Design or prototype anything in seconds
• 200+ models from Vercel AI Gateway
• Outputs are pure HTML artifacts
• Fork it & make it your own
Try it free ↓ fx0.vercel.dev
Sai Prakash retweeted
"I want the executive to have a dashboard light up" is "not a motivation in itself."
Sai Prakash, CTO and co-founder of MindStaq, on the hardest lesson in adoption.
leadershipsovereignty.com/ep…
I’ve started playing AI subway surfer. Prompt the next instruction into a remote session, lose connection between stops, arrive at the next stop and read the response. Then quickly type in a response if needed to keep it going. Save the big notes for the bridge🤘🏾
MindStaq's daily lesson for me today really hit a point I wanted to share immediately:
Reallocation, not replacement — redeploying people when tasks get automated
When a task gets automated, the leader's job is not to defend the role but to name the adjacent work the person is now freed for. Practical version: for each automated task, write down (1) the task, (2) the judgement it was hiding, (3) who now owns that judgement, and (4) what the freed hours are for. Leaders who answer (4) before announcing the automation keep trust; leaders who leave it blank get attrition and quiet resistance.
Sai Prakash retweeted
Hello Software Engineers, I lead TypeSafe AI Model Capabilities team. We are hiring. Here are a few qualities we are looking for:
• strong plus for people who resonate with the title "Experience Engineers": mobile engineers, full stack engineers, or even (virtual) reality engineers.
• strong coder (you need to be able to manually write code)
• product oriented thinker
I promise are fun! I trust that you will figure out how to apply.
Sai Prakash retweeted
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
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?
Sai Prakash retweeted
"Enhance every person so that they're the hero of their role. But don't try to replace the role itself."
Sai Prakash, CTO and co-founder of MindStaq, on the line AI should not cross.
leadershipsovereignty.com/ep…