Marlon

Founder & Engineer building AI systems that empower humans.

[Marlon @__marlonw]

American industry deserves a best-in-class product designed for the problems it actually has. We're partnering with a handful of manufacturers to help shape what AI means in the manufacturing space as part of our pilot program. If you've lived this gap, I want to hear from you.

[Marlon @__marlonw]

Over the past 2 weeks I spoke at 2 events run by MEP centers in 2 different states. I came away with one massive takeaway.

[Marlon @__marlonw]

This is the gap Damon was built for. It sees the entire manufacturing operation, from individual cells to the back office, so it reasons over the data that actually runs the plant.

It's quick to stand up and meets your data where it already lives, paper and spreadsheets included.

It's deeply configurable to how your shop runs, with real predictive power and contextual awareness of the people, parts, and processes across the whole operation — and it can be deployed where compliance demands it.

Purpose-built for manufacturing, from the ground up.

[Marlon @__marlonw]

Fable & Opus are priced at $50/M output tokens.
Kimi K2.7 is priced at $3.50

Is the output of Opus 14x as useful as Kimi's?

[Marlon @__marlonw]

@connorkapoor Awesome, may need to integrate this.

[Marlon @__marlonw]

I always think about this when I see companies do bizarre things - multiple people across levels had to agree, sign off, and implement something

[Priyansu Kumar @Automateby_Priy]

@joannejang Can't stop thinking about the fact that this probably wasn't one person's decision. A whole chain of people signed off on it

[Marlon @__marlonw]

Training models is beautiful because you're programming behavior via data. Really interesting intuition to develop about what works

[Standard Bots @standardbots]

Today, we’re thrilled to announce our $200M Series C funding round at a $1B valuation, led by @RoboStrategy and existing investors including @generalcatalyst.

Standard Bots is now America’s largest manufacturer of AI-native industrial robots. Our customers include Sunoco, Lockheed Martin, NASA, and the US Army along with hundreds of other manufacturers across the country. We’re proud to say that we’re on track to deploy 10% of all U.S. industrial robots by next year.

We are expanding our Glen Cove, New York facility to 70,000 square feet to scale our vertically integrated production process. We currently design almost all our own parts, including our own actuators, and we assemble every final product in-house. By 2027, we’ll manufacture everything — from metal in to robots out — right here in America.

We believe AI-native robots are the essential power tool of the 21st century — the tool that will grow American manufacturing and help every American worker to be a force at work. You just show your robot how it’s done, and it learns through demonstration. No coding, no consultants, just unbox and deploy faster than anything else on the market.

Right now it’s possible for the United States to revitalize our manufacturing base if we become the worldwide leader in this transformative technology.

We must build American robots, and put them to work in American factories. It’s a national imperative, and it’s our central mission. This fundraise gets us one step closer to the goal.

The future of American manufacturing is bright! Join Standard Bots, and show your robot how it’s done — we’re just getting started.

[Marlon @__marlonw]

the medical system is broken, insane what folks need to put up with

[Marlon @__marlonw]

@Dylan_Morri @zodiaceng @barbinbrad was going to mention carbon as well, love to see it

[Marlon @__marlonw]

Love seeing an agent get excited by completing a task it stuggled with

[Marlon @__marlonw]

@hthieblot club penguin. legendary times

[Ilir Aliu @IlirAliu_]

A policy that teaches robot hands to touch things the way humans do... not just grab and move, but feel and adjust in real time.

Robot manipulation research often stops at picking up objects and placing them.

CGP goes further: it handles tasks like opening jars, flipping objects in-hand, wiping dishes, and grasping fragile eggs, the kind of dexterous, contact-rich skills that require constant micro-adjustments based on what the fingers are actually feeling.

The robot doesn't just see what it's doing; it predicts what contact should feel like at each step, then checks whether reality matches the prediction. If a finger is slipping, the policy knows before the object drops.

Works on real robot hands (both 4-finger and 5-finger designs) with tactile sensors embedded in the fingertips

Robust to visual distractions!

The robot keeps flipping a box correctly even when the camera view is disrupted, because it's grounding decisions in touch, not just vision.

Baseline policies without contact grounding fail in predictable ways: slipping mid-task, incomplete motions, loss of grasp, CGP avoids these

This is a meaningful step toward robots that can handle the physical world with the kind of reliable, adaptive grip that humans take for granted.

Relevant for manufacturing, logistics, assistive robotics, and anywhere fragile or irregular objects need to be handled carefully.

Published at RSS 2026, developed with Meta Reality Labs Research.

Thanks for sharing, Zhengtong Xu / @XuZhengtong

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[Ilir Aliu @IlirAliu_]

Robotics companies: let us solve repetitive tasks like folding shirts.
Meanwhile, the factory floor:

[Marlon @__marlonw]

Biggest painpoint of running multiple git worktrees locally at this point is just finding an unclaimed port config