playing https://xitter.twitterapi.xyz/t.co/T48MlltzFi
nyc
Joined May 2022
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Turned my portfolio into a New York City subway station
infinite.games
yea swarm riders is a cyberpunk af name
Swarm riders and Swarm-native companies
AI-use even among highly AI-native people is power-law distributed.
There seems to be a new class of people — call them “swarm riders” — who are capable of consistently commanding large swarms of agents to productive ends.
This is a new kind of managerial skill, analogous to the skill it takes to manage large organizations of people, but wholly different in nature and of course more technical.
Based on the swarm riders we know (including many at @Tempo and @Paradigm), these people are capable of productive token spend that is 1000x-10000x higher than median software engineers, and 100x higher than top 5% Claude Code users.
The art of swarm riding is different from software engineering and more akin to machine learning, where practitioners grapple with black box systems: defining reward functions and evals, transmuting non-verifiable problems into verifiable problems, running experiments, etc.
Swarm-native companies are a new class of company founded by and populated by swarm riders. These companies are organized around swarms in a way that conventional companies will struggle to replicate, as the cost of internal human coordination is sand in the gears of an effective swarm. Effective swarm-native companies will define the right reward functions and evals, remove functional and bureaucratic barriers, and then let the swarms cook.
We’ve gotten to see a few swarm-native companies up close — reshaping financial rails @Tempo, building a new gaming platform @Spawn, cyber swarms at Cathedral Systems — and it’s clear these teams wield a significant advantage over pre-AI teams.
Some questions I’ve been wondering about:
1) How fast will swarm riding diffuse through the economy? The implications for token spend could be significant.
2) Can swarms be effectively adopted by existing companies or will it generally track the formation of new swarm-native companies?
3) What becomes scarce as swarm capabilities themselves commoditize (through frontier models becoming better at swarming, swarm capabilities built into harnesses, etc)? Cultures and teams that can define reward functions well and otherwise get out of the way?
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Turned my portfolio into a New York City subway station
infinite.games
I'm not sure whether this counts but it might xitter.twitterapi.xyz/jamesonhodge/status/21…
my vocal synth models the vocal tract as a network of branching acoustic tubes, unlike vocaloid which stitches together and pitch-shifts phoneme recordings. still working on improving naturalness by tuning it against recordings of real singers, but I'm already impressed at how cool it sounds!
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Idk if this is a valid comparison anymore for these two firms
Cursor seems far more focused on the future of knowledge work via Grok Bot, and Cognition is focused on diffusing agentic software engineering into the economy / traditional enterprises
Though it's possible Cognition also gets to the former via being embedded in those orgs already and arriving at their own Grok Bot version (the poke thing)
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Fable 5.2 actually paints Sam Altman
This is not painting with code or using scripts to convert image pixel data into digital paint. Instead, it works on a digital simulation of real oil paint, where new colors can only be created by properly mixing existing paints with the available brushes
Fable looks at the reference image and creates the painting by working in the browser and looking at screenshots of its own work as it progresses
Fable 5.2 actually paints Sam Altman
This is not painting with code or using scripts to convert image pixel data into digital paint. Instead, it works on a digital simulation of real oil paint, where new colors can only be created by properly mixing existing paints with the available brushes
Fable looks at the reference image and creates the painting by working in the browser and looking at screenshots of its own work as it progresses
The final result is pretty mid! Though certainly better than an amateur human would be able to create I think
I'm sure there are also plenty of improvements to be made to the "painting harness" as well as the tool itself. That said I think this is around what I would expect an advanced model to be able to achieve on something that does not involve writing code/text
this ad feels meh:
- poor use case. specs for realtime mini golf directions takes the fun out of the game, which feeds into the idea that smart glasses are antisocial products. something like cooking would be a far better example imo
- RDJ doesn't strike me as someone who can really influence consumer purchasing decisions in 2026 (ik they have more of an enduring partnership and it's not just a one-off ad, but this applies to that too)
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ramp and openrouter both do a good job of taking their proprietary data and using it for content marketing ("data storytelling"). establishes them both as authoritative - former with business spend and latter with token consumption / model usage
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I made Wikipedia Gacha
Every Wikipedia article is a trading card, with rarity based on how many views that article gets. Claim $100 every day to rip packs and pull Wikipedia cards, which you can keep or instantly sell back
wikigacha.infinite.games
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the most important form of assimilation for immigrants coming to America is using MM/DD/YYYY format
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.@SpaceXSI should buy @pangram to integrate natively into platform for hiding bot replies
Then also sell as service packaged with existing cursor/grokbot B2B offerings
Anyone who says a social network wants bots is deeply mistaken. Human interaction is already scarce on social networks, since most people are passive consumers.
Bots displace this scarce resource:
Each bot reply means one human reply is not seen or engaged with by another human.
It’s nearly a 1-to-1 drop in product & business value—and likely has much bigger compounding losses when you account for people churning out of frustration.
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