Fahdoo retweeted
With genAI there is a whole new field of “performative visualizations”. The “artist” understands neither the art nor the subject of what is being visualized, but there is quasi-coherence in the visuals and cultural weight attached to the dataset that it becomes a spectacle.
TLにMarc Ngui氏によるドゥルーズ=ガタリ『千のプラトー』のダイアグラムが流れてきて、かっK〜と思ったので、試しにシェーダにしてみたら結構イケてるbumblenut.com/drawing/art/pl…
Fahdoo retweeted
12 years ago I founded Boom, as a software engineer doing hardware for the first time. I’m probably the least handy founder in hard tech. My 12 y/o son does my soldering and 3D printing for home projects, and I’ve struggled with imposter syndrome the whole way through. What business does a software guy have building supersonic jets and turbines?
More than a decade in, the most insane realization is that software is the key to reaccelerating hardware engineering. But in a way that I don’t think is widely understood or implemented, even in the burgeoning hard tech community.
Most hardware engineering is actually software engineering in disguise. It’s spreadsheet “code,” engineering calculations done as one-offs. Eg wing structural loads in, spar sizing design out. Thermal loads in, air conditioning system sizing out.
Everything is a calculation, and calculation is software. But these calculations are done essentially by hand, as if we are doing arithmetic but have not yet discovered algebra.
Hardware engineers have baby software, built in spreadsheets, the kind of crappy software I wrote as a kid before I understood architecture, unit tests, APIs, version control, and everything else that makes modern software good.
Our airplanes and engines are built with the software sophistication of a script kiddie.
So what we tell our engineers: don’t design the hardware, design the *algorithm* for designing the hardware. And take the algorithm seriously—as an algorithm and as a first-class engineered software system.
Never design a piece of hardware, such that you couldn’t redesign it tomorrow with a different set of assumptions.
This all sounds obvious, yet our experience at Boom is that it changes everything.
Ten years ago we couldn’t afford to build much software. We had a small team—and there were few software engineers with the curiosity, brilliance, and vision required to learn hardware engineering.
But now AI changes the equation. Now everyone can code. The software engineers define the architecture. The hardware people bring the physics and engineering know-how.
We have a turbomachinery design tool that lets one engineer do in realtime what previously took 100 engineers six months. Another tool auto-generates 65% of entire aircraft structure. I’m sure we’ll figure out the other 35% too. Eventually these should not be multiple tools, but one integrated physics model of a complete vehicle, airframe and powertrain.
The results speak for themselves. A boomless supersonic airplane built by 50. A full scale supersonic turbine made by 150. And with this approach, I don’t think we’ll need that many more people to build and certify a supersonic airliner.
You don’t need a big team to build big things—not when everyone on the team is a software engineer.
Fahdoo retweeted
This post keeps getting better and better at every turn. What an incredible company.
Today, Zipline raised $1.5b at a $21.5b valuation.
When we started Zipline, flying autonomously in the US was illegal. Which made it really hard to convince investors to give us money! But we were too naive to think that meant we shouldn’t try.
We started the company on a cow farm. We worked out of run-down construction trailers so that we could keep engineering, manufacturing, and flight test all unified and in one place. Hiring people from normal companies like Google was hard because we didn’t have a cafe or laundry service. But enough risk takers and rebels wanted to go on an insane adventure with us. They became the early team.
We decided to launch in smaller countries and focus on life-saving use cases. We hired incredible entrepreneurs and operators in Rwanda, Ghana, Cote D’Ivoire, and other countries. For eight years, Zipline expanded our service across Africa, serving thousands of hospitals and health facilities and reducing maternal mortality by 51%. Today, the network saves over 14k lives every year and is cash flow positive.
Last year, Zipline launched at scale in the US and the service exploded. We grew flight volumes about 100x over the last 18 months, and now make more than a million deliveries a year per metro. We’re now expanding with our partners to millions of deliveries per day. Normal families love having access to anything they need in 10-20 minutes, no matter where they live. Spend more time with loved ones and less time worrying about errands.
Zipline builds drone delivery that is silent and safe. No one wants to hear an extremely loud “swarm of bees” delivering to their backyard or their neighbor’s. Automated delivery needs to be insanely quiet, which guided the overall architecture of our technology delivering from 330 ft in the air. We are 6 times quieter than the closest competitor during delivery. Zipline also now has over 150m commercial autonomous miles (10x the rest of the industry combined) and no safety incidents. Neighborhoods should demand silent and safe delivery!
Today, Zipline is announcing two things. First, we just signed the largest autonomous vehicle contract in human history to expand automated delivery nationally with Walmart, our first and biggest partner in the US. We’re starting by scaling to 300 supercenters throughout the country. Second, we’ve raised $1.5b at a $21.5b valuation from existing and new investors, led by Paradigm, WCM, and Layer.
Zipline was a hard company to believe in for the first ten years of our history. Investors didn’t think the company was “investable”. Most people didn’t even think Zipline was an economic venture. Thanks to those who have rooted for us along the way. To all of the tens of millions of customers and families who rely on Zipline day in and day out: thank you for helping us build the future. Zipline has grown more than @ryanzip, @keenanwyrobek, I, and all others at the company could have imagined.
There is a big opportunity to build a new layer of infrastructure for humanity over the coming years. We want to approximate teleportation. We can build a logistics network that connects and serves all people on earth. We can free human flourishing from the choking constraint of traffic and roads. There are no roads where we’re going. 🚀🌎
You can't call this AI slop anymore.
One self-taught working mom made this 9-minute AI fantasy film.
An she won 4 awards at the New York International Film Awards, including Best AI Film and Best Screenplay.
This is what real AI filmmaking looks like 👇
Fahdoo retweeted
We just published our blueprint for the Self-Driving Company.
At Replit, engineers nearly tripled code output in the first half of the year. Incidents stayed flat. Then design and technical support started shipping too. Today we use Replit wall-to-wall to build every function of our company.
Over time, it became clear that models are the easy part. The hard part is the Agent Habitat: access control, data governance, security.
We are making useful intelligence accessible to everyone. As it was always meant to be.
replit.com/blog/rise-of-self…
Now anyone can now bring their ideas into the company codebase on Replit.
Replit Cloud Agents can turn natural language into a tested pull request, and engineers still approve the final code before it ships.
Our own design team used Replit to safely ship over 250k lines of code in the last 6 months, reviewed and approved by engineers.
replit.com/blog/anyone-can-b…
Fahdoo retweeted
Software ate the world, now it's learning to run it. View article
Its been quite the journey from the inside seeing how @Replit itself grows into a self-driving company and then making it happen for everyone else! We're just at the starting line and next year is going to be something 🚀
We believe by the end of 2030, every Fortune 500 will be a Self-Driving Company.
That doesn’t mean AI replaces people.
It means people remain in the driver's seat leading judgment, creativity and taste, while agents fuel execution.
This is the Self-Driving Company.
replit.com/blog/rise-of-self…
Fahdoo retweeted
This is obviously the future of video games.
Streamers and their community building the game together, then playing it.
When Astra came out I streamed a call of duty clone, with 10 loadouts, vehicles, kill streaks etc, and in between matches people we're shouting in the voice chat (that we vibe coded into the game), what changes they wanted.
But i see a world where they can send in their prompts and the team of the streamer can moderate those prompts and send them through, and the agents will make 20 changes at once, and then 30 min later everyone could be playing the next version of the game.
And every month that goes by, as models improve, these games will look more and more professional. Some company will figure out how to make these games easily forkable, hostable, monetizable, social, fast, and fun.
I have spent 3 weeks and two claude max accounts vibe coding a 50-person battle royale.
Kong Royale.
We invented hive coding, chats messages prompt 20 agents working overnight to fix and improve the game.
and today we finally launch 🦍🍌
live playtest TODAY 1 PM ET. drop in with us 👇
youtube.com/watch?v=b5n1K_IA…
Fahdoo retweeted
Hi, I'm Felix. I'm an eng lead working on Claude. I love watching people take flight and do things they never thought possible.
We often describe that as "being more ambitious" when using AI, which is tricky advice to follow. I wrote a tutorial:
felixrieseberg.com/how-to-be…
Fahdoo retweeted
personal agents, the end of friction, economic consequences of finally getting around to it
How does one know their artwork is done? This reminds me of when I’d get an itch to make “just one more brushstroke” and somehow end up repainting the whole damn thing.
Fahdoo retweeted
Asking Claude to review your code is a slot machine.
Every review finds brand new bugs. Review again: more. Review a tenth time: it still finds something.
It never runs out of bugs to find... so how do you decide your code is actually done?
Fahdoo retweeted
Starting to think about engineering work as "product engineering tasks" and "factory engineering tasks."
Product engineering: improve the product
Factory engineering: improve the agents that improve the product
I heard @poteto call this "gardening," which I really like!
I think of these categories as inner and outer loops, where the inner loop is your team of agents building everything, and the outer loop is your team of supervisors / gardeners watching over those agents and spotting room for improvement.
We're exploring how to automate that second loop. Right now, we have one "outer loop" of agents on our software factory that focuses on agent skill improvement.
One batch of agents scores the quality of agent conversations:
- was the agent efficient, or did it waste tool calls trying to understand its environment?
- did the agent write good code by our standards, or was there, say, excessive test coverage?
Then on a schedule, another agent looks for low-scoring conversations and suggests skill improvements based on them. We've merged quite a few skill changes so far, and the scores help us gauge whether those skill changes are helping.
I'm interested to try another "outer loop" agents focused on code architecture / abstraction and adding static analysis checks. These are even better guardrails for agents than skills to prevent bad code viruses from spreading.
Curious if other people are at setting up supervisor / gardener agents like this.

ALT Two side-by-side loops. Left, a blue dashed circle titled "Inner loop – improve the product" connects eight steps clockwise: New work assigned, Triage, Spec writing, Implementation, Verification (computer use), Code review, Ship, Monitor usage, then back to New work assigned. Right, an orange dashed circle titled "Outer loop – improve the factory" runs "Every 24 hr" and centers on a "Core factory loop" of four steps: Review agent conversations, Score quality, Isolate failures, Propose improvements. Callouts show scoring rubrics (efficiency and code quality checked, test coverage failed), a failure note ("5 conversations wrote redundant tests"), and a proposed edit to test-writing/SKILL.md that adds a "Coverage pyramid" section.
Fahdoo retweeted
You need both taste and judgement. You need taste to know what is good, and you need judgement to understand the price of quality.
If you ask a model for a component or migration plan, it will create a lot of options, very quickly. Most of those drafts seem OK. So once you have a collection of work that meets the basic criteria, you can no longer use taste to select between them. You must choose.
I like to think of this as two filters. There is the taste, and there is the judgement. And I think a lot of people mix those up.
The first filter is taste. Taste is the feeling for what makes a thing good.
Taste is that feeling you get first, before you're able to put into words what is good or bad about something. You've had that experience where something is bad but you're not sure why, until you've worked it through and can describe it. "This user experience was really clumsy" or "that error message was really aggravating." Taste is built up by experience and practice.
It comes from looking at a lot of things, and making a lot of things, and remembering the good bits. Kant's great insight into aesthetic taste was that you could appreciate the form, without having a stake in the outcome. Engineers care about the outcomes much more than the forms, but the feeling is the same.
Taste can disqualify a lot. It can disqualify 90% of drafts very quickly. But it's not enough to make a decision between the few remaining options.
The second filter is judgement. Judgement is understanding the price of quality. The most perfect solution may not be finished by the time that you need it. The sanest architecture may require the users to migrate while you're in the middle of the final upgrade.
Judgement is the understanding of what you give up in time and risk to get good things, for the sake of the users, for the sake of the team. Judgement is made from domain knowledge and experience from previous decisions.
People with great taste but poor judgement make beautiful work too late. They make the right thing at the wrong time, or the wrong thing at the right time. People with judgement but no taste make on time but don't make things people love.
Both taste and judgement are essential. Filter to a few options with taste, and filter to one option for delivery with judgement.

























