Bill Tribble

36K posts

Bill Tribble banner
Bill Tribble

Bill Tribble

@bill_tribble

Independent AI UX designer consulting at @GoogleDeepMind. DJ and musician for conscious dance. #blm.

Hackney, London Katılım Mart 2009
3.7K Takip Edilen1.5K Takipçiler
Bill Tribble retweetledi
Alexander Doria
Alexander Doria@Dorialexander·
Probably the best summary of OpenAI latest math breakthrough: "first example of a result produced autonomously by an AI that I find exciting in itself, as opposed to as a leading indicator." Feels like they’re really scaling search rather than solutions to bounded problems.
Daniel Litt@littmath

(What I wrote is screenshotted below.)

English
4
11
168
21.5K
Bill Tribble retweetledi
Nathan Clark
Nathan Clark@nathanclark_·
it’s in gemini, just create it in ai studio. oh, that’s for your personal google one account. for workspace you need gemini business. no, not gemini advanced, that’s ai pro now. unless you need ai ultra. oh agents? you do that in spark actually. no, not gemini api managed agents, that’s different. for coding use jules. unless you mean the agentic ide, that’s antigravity. no, that’s the old antigravity, download the new one. actually gemini cli is being deprecated, use antigravity cli. no the flash model is smarter than the pro model. unless you need pro. if it’s video, use flow. no, flow uses veo. no, nano banana is images. actually that’s in gemini now. unless you’re in search, then it’s ai mode. no, research is notebooklm. anyway it’s all very simple.
English
510
2.1K
19K
1.6M
Bill Tribble retweetledi
davidad 🎇
davidad 🎇@davidad·
Yes, “write all of ffmpeg make no mistakes” is the correct benchmark hill to be climbing in 2026, much more so than SWE-bench. Good work. Looking forward to seeing where GPT-5.5 places on here, and beyond.
John Yang@jyangballin

How much of SQLite, FFmpeg, PHP compiler can LMs code from scratch? Given just an executable and no starter code or internet access. Introducing ProgramBench: 200 rigorous, whole-repo generation tasks where models design, build, and ship a working program end to end. 🧵

English
26
11
374
31K
Bill Tribble retweetledi
signüll
signüll@signulll·
not a single person i have ever spoken to uses gemini for coding. this is still very very weird. why is gemini so bad at coding when google has scoured the web full of code for decades?
English
1.1K
162
9.5K
849.3K
Bill Tribble retweetledi
vitrupo
vitrupo@vitrupo·
Max Tegmark says the way through the AI black box may be to deploy its outputs instead. A cat can learn, but it cannot export what it learned. A human scientist can. As intelligence rises, more knowledge may become externalized into code and proofs. Deploy what the mind can verify, not the mind itself.
English
22
18
208
49.5K
Bill Tribble retweetledi
Roy🇨🇦
Roy🇨🇦@GrandpaRoy2·
I just reread Adam Tooze's magisterial The Wages of Destruction: The Making and Breaking of the Nazi Economy, and the parallels with Russia's deteriorating wartime economy are striking. By the late 1930s, Hitler's massive rearmament program consumed 20% of national income. 1/
English
30
116
646
119.3K
Bill Tribble
Bill Tribble@bill_tribble·
This is the most weird and wonderful music, wtf! ‘The most stunningly awful wonderful record’: how the Shaggs became rock’s most divisive band | Music | The Guardian theguardian.com/music/2026/mar…
English
0
0
0
55
Bill Tribble
Bill Tribble@bill_tribble·
The only way to prevent an AI-powered authoritarian state is to establish strict political laws and democratic norms against the state using AI for censorship and mass surveillance. dwarkesh.com/p/dow-anthropic
English
0
0
0
15
Bill Tribble
Bill Tribble@bill_tribble·
Within a year or two, open-source AI models will catch up, allowing the government to bypass corporate redlines entirely.
English
1
0
0
5
Bill Tribble
Bill Tribble@bill_tribble·
Interesting and I thought this bit was the most important - We need Political, Not Technical, Solution: Corporate courage from companies like Anthropic is commendable and sets a good precedent, but it won't solve the long-term problem.
English
1
0
0
10
Bill Tribble
Bill Tribble@bill_tribble·
Nope I have no problem tapping the right one in a rush
Bill Tribble tweet media
English
0
0
1
10
Bill Tribble retweetledi
Jason Yuan
Jason Yuan@jasonyuan·
I'm hiring people who care about people to build social AI that helps people care about people! if you're an engineer/researcher/multi-hyphenate excited about some or all of the following: - social agents and social memory - consumer - s2e3 of rick and morty - collective intelligence - gossip girl - craft - alexander mcqueen spring/summer 1995 - information markets and behavioral economics - pop culture - having a lot of fun and moving super fast with people you care a lot about ... please reach out! dm me or email me at j[at]futurelovers[dot]com
Jason Yuan tweet media
English
65
39
850
137.2K
Bill Tribble retweetledi
Jeffrey Emanuel
Jeffrey Emanuel@doodlestein·
To all the people who find the full Agent Flywheel a bit too overwhelming and would prefer a more incremental introduction to my tools and workflows, here’s my latest advice:
Jeffrey Emanuel@doodlestein

If you don’t want to dive directly into my entire Flywheel system all at once, at least try this: 1. Install agent mail using the curl | bash one-liner: curl -fsSL "raw.githubusercontent.com/Dicklesworthst… +%s)" | bash -s -- --yes That will automatically install beads if you don’t already have it. Then install beads_viewer with its one-liner: curl -fsSL "raw.githubusercontent.com/Dicklesworthst… +%s)" | bash Then set up your AGENTS dot md file for your project. You can start with this one and just remove the sections for the tools you’re not using yet: github.com/Dicklesworthst… Then ask CC to adapt it to better fit the tech stack for your particular project. That’s all you need to get started. Then follow this workflow: x.com/doodlestein/st… Try to start with a smaller, self-contained greenfield (new) project and see whether you can get it all working perfectly without looking at any of the code, just from following the workflow. Spend most of your energy and human time/focus on the markdown plan. Don’t be lazy about the plan! The more you iterate on it with GPT Pro and layer in feedback from other models, the better your project will turn out. Also don’t be lazy about turning the markdown plan into beads, either. Don’t try to one-shot it with CC, you will 100% miss stuff from the plan. This is the easiest thing to screw up assuming you already have a great markdown plan. Do at least 3 rounds of polishing, improving, and expanding the beads. Once you have the beads in good shape based on a great markdown plan, I almost view the project as a foregone conclusion at that point. The rest is basically mindless “machine tending” of your swarm of 5-15 agents as they build out the beads. It’s mostly just juggling these tasks: - Making sure to make them read AGENTS dot md after compactions. - Using many rounds of the “fresh eyes” review prompt whenever an agent tells you it’s done implementing one of the beads. - Swapping accounts when you run out of usage (ugh!). - Making sure you commit frequently to GitHub using my “logically grouped” commits prompt. - When all beads are complete, doing many rounds of the random code inspection and review. - Adding more and more unit and e2e tests. - Setting up gh actions for testing, builds, tags, releases, checksums, etc. - Writing a README and help/docs/tutorials. - Iterating on a “robot mode” (you added one, right?) with feedback from the agents to make it better. - Seeing if you can make your project work better when controlled by Claude Code by making a skill for it. But most of these things can be done using very little mental focus or attention/energy. Save all of that for the ideation and planning phases! The one thing people seem to get wrong is ignoring what I say about planning or transforming their plan into beads. They make a slipshod plan all at once with Claude Code. Or they try to one-shot turning the plan into beads. Or they even do both of those things! Well, of course the project is going to suck and be a buggy mess if you do that. So don’t be lazy. Or if you insist on being lazy, save it for the stages after planning. A great set of beads is all you need. As for the rest of my tools: Once you get comfortable with that workflow, start layering in the other tools, starting with ubs to help find bugs during the review phases. Then add in dcg. You’ll actually appreciate dcg a lot more once Claude wipes out all the work from the other agents since the last commit! As you build up a good session history, layer in cass so you can tap into that history. And then try cm (cass memory system) to start extracting and codifying lessons from your past sessions. And I know I’ve said that I don’t really use ntm yet (I’m not dogfooding it at least), but that’s not quite true. I’ve been using it as a handy building block because of its robot mode. For example, ntm is used by ru (repo_updater) to automate handling gh issues. Good luck, and come to the Discord with any questions!

English
6
3
39
5.5K
Bill Tribble
Bill Tribble@bill_tribble·
Next up: I'm working with Freddy to build a definitive version that doesn't need a high end machine to run, and then we'll share more widely!
English
0
0
0
8
Bill Tribble
Bill Tribble@bill_tribble·
The older models are particularly interesting as you can really see how they're constructed. The demo will take you on a little tour, but feel free to scroll your mouse and take control of the app: billtribble.github.io/Prismata-UI/
English
1
0
1
16
Bill Tribble
Bill Tribble@bill_tribble·
Have you ever wondered what the structure of an AI looks like? I was so blown away by Frédéric Ayala's "Prismata" LLM visualization that I got involved and made a remix!
English
1
0
1
41