Self-employed by the guy who ran open source programs @blocks, @apple, @redhat. Building the plane as we fly https://xitter.cf/t.co/E1NdEX8WFS.

Calichusetts
Joined January 2009
The base reasoning behind the exploratory work I’ve done with Aileron and shareable, portable, skills. Reproducible where appropriate and auditable always Not everything is for inference
I predict the teams that best solve the deterministic / non-deterministic boundary will beat the teams throwing 100% of their work at models and agents. Just because a transformer can: - plan - choose tools - decide what to do next - keep reasoning - format outputs - route between actions doesn’t mean you should ask it to do all those things every time. Much of that work may be better expressed as deterministic code for your use case.
3
417
Never underestimate the amount of access and privacy we’re willing to give up for convenience.
1
4
351
Agentic Commerce is an inevitability. Damn good on Stripe for the partnerships, but the future has got to rest on interop and open protocols
Stripe locked in Instinct Stripe locked in Grok Bot Do you now believe that agentic commerce is here?
1
1
8
1,400
Corollary: Companies locking their data behind their own web apps with no APIs are going to be disrupted by challengers. The special fancy data is the moat until your UX is so poor it invites others to jump in with the alligators
companies building their own agent rather than exposing an mcp / cli for their uses is like if you had to download a separate browser for every website you use
1
265
Come work with me! We're looking for a Sr Technical Program Manager at the Agentic AI Foundation careers.linuxfoundation.org/…
5
35
3
102
12,143
The Red Sox are on a hell of a winning streak. – at Boston, MA
1
4
226
Responsible disclosure should be the norm. Important for everyone to understand why that is an established best practice. We shouldn't be celebrating premature public disclosure.
If you are pointing frontier models at FOSS code bases - cool. Let's ensure the ecosystem is safe, the more eyes the better. But don't recklessly tweet out to try to spread panic or chase clout. People are on edge from Coldcard. Responsibly disclose with the team that can actually verify your claims, respond the right way, and then most importantly, safely fix the issue (if it's real). We've been getting lots of engagement from people across the ecosystem. That's great. But, like with anything AI, even the cyber models can produce slop. I am not dismissing Floppy's claim here. I acknowledged it and we are looking into it within 30 mins of his posting. Any bug or vulnerability is urgent to us, and we are on it. But this should be done over email, and not in public where unverified claims can lead to false narratives and unnecessary panic.
3
12
74
4,742
Serious folks do not report security or open source vulnerabilities like this. Making unverified claims in public: * Overloads the dev team. Potentially pulls attention from serious and consequential work * Gives attackers an advantage We had set up secure disclosure reporting and bug bounty programs for a reason.
unavailable
1
1
4
830
Lot of good points but also fair bit of confusion on what shared compute gets you so let’s clarify 1. Shared compute does NOT mean model gets smarter over time. Weights are frozen at inference time. You’d need something like shared memory layer or plan to post train on data 🧵
I think the most interesting thing about Jack Dorsey's "Slack killer" is the idea around shared compute. I haven't seen people talk about it so here are my thoughts FWIW: Open models got good, close enough to the paid frontier stuff to run for real. But the strongest ones need expensive hardware most people probably won't buy alone, and it's kinda a pain to set up if you aren't technical. Shared compute solves exactly that. In Buzz, one person runs the machine, loads up an open model like Google Gemma, and everyone in the community plugs into that same model. Basically, a whole group has real AI they own and control together, running on their own hardware, learning from their own data. Once you see it, a bunch of things click into place. 1. A community can now run a top open model together, on a machine they own, instead of renting from a lab. 2. It learns from the group's private data and gets sharper over time, and all of that stays inside the community. 3. A narrow, private model can quietly get better than ChatGPT for the one world your group lives in. 4. It's impossible to copy, because the edge is the private data on your machine, not the model itself. 5. The moat stops being how smart your AI is and becomes whose data it learned from. 6. Compute becomes something you share like a building shares a gym. 10 people split one machine instead of 10 people each renting forever. 7. Idle compute becomes income!!! Your machine sits dead half the day, so it earns money renting that time to someone who needs it. 8. Communities become the unit of intelligence instead of companies. The group with the smartest shared brain wins, and being a member means owning a piece of it. 9. A shared brain becomes an asset you build equity in. You put in money and data, it appreciates, and your slice is worth something the day you leave. 10. The whole thing runs on open protocols, so the group keeps full control and nobody outside can throttle it or shut it off. You know me, obviously, my head went to what startup ideas come to mind here. Adding them to @ideabrowser soon. Well… 1. The vertical brain. Pick one profession, tax lawyers or real estate agents or indie game devs, and build the shared machine trained on everything that group knows between them. A year in it's the smartest AI in that field, impossible to copy, and you own the club it lives in. 2. The rental marketplace for collective brains. Once these private models exist, outsiders will pay to use them. You build the layer where a group lists its brain, an outsider pays per task, and the money flows back to the members while you take a cut. A marketplace for expertise, not compute. 3. The idle-compute exchange. Every shared machine sits unused half the day. You build the market that rents that dead time to whoever needs the power right then, so owners earn money off a machine that was just sitting there. Idk where Buzz goes, but it's cool to see Jack putting it out. Right now the way it works in AI is you rent your intelligence from a few giant labs that own the machine, set the price, and hold the off switch. Shared compute flips that, because a community can run the model together, feed it their own private data, and keep full control of the whole thing. It's one of those things that might look tiny today, but Jack does has a habit of being early.
2
5
1
11
3,146
Open source is the best engine of innovation on the planet
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. images.nvidia.com/pdf/Open-W…
2
3
528
I was adamant as lead of the @blocks OSPO that we give the company self-service open source. Anyone should be free to get moving on a new project in the open from the beginning. Thrilled that buzz.xyz was born from this.
1
9
465
Another thing give been thinking a lot about with multiplayer is context. Context is the only thing that any org has that’s uniquely their value. And the only thing that makes agents extra effective. You want: Access to all the context Loaded at the right time Available to the right people in your org Buzz has a brilliant context model, congrats y’all
1
2
305
Block team is really on to something with Buzz. I’ve been building Aileron around core principles: separating auth from the agents, making all artifacts auditable and cryptographically verifiable. Multiplayer and free of frontier lab lock in is the way forward.
6
408
I think more likely: Build the product that folks can BYOAgent to - and load it with context and tools necessary for it to do the job. Commoditize the LLMs, commoditize the agents, make each org successful on what only it can do
the agent you're building into your product is most likely not going to work just drop it, what's going to happen is there will be a few agent products that individuals and teams choose to use and they will want everything there. might mean they don't even want your product
1
401
The algorithm changes feel great, and they shouldn’t. They prove how one company’s incentives are bad for the one thing this platform was built to do: connect people. This is a poor town square and they don’t deserve to be our stewards.
1
3
399
Feels like our agents mirror our own competence. They amplify what you're good at. My background is in making application servers. The code I do now is backed with unit and system tests, has clear goals, is well-specified. At the same time, the horror that is my front-end design remains. And I know pros are getting much more out of their agents on this than I am.
2
1
657
Looking forward to trying some new design approaches on Fable, 5.6 Sol, and Allaire HomeSite.
192