Dima Kuchin

1.3K posts

Dima Kuchin

Dima Kuchin

@kuchin

AI agents go brrr. ex-Meta, Zoominfo, WeWork, CTO x 4 https://t.co/O2lLoSCS3p https://t.co/IGKIT537sc

Israel Katılım Nisan 2007
207 Takip Edilen817 Takipçiler
Dima Kuchin retweetledi
Simon Willison
Simon Willison@simonw·
Turns out you can run enormous Mixture-of-Experts on Mac hardware without fitting the whole model in RAM by streaming a subset of expert weights from SSD for each generated token - and people keep finding ways to run bigger models Kimi 2.5 is 1T, but only 32B active so fits 96GB
seikixtc@seikixtc

I got a 1T-parameter model running locally on my MacBook Pro. LLM: Kimi K2.5 1,026,408,232,448 params (~1.026T) Hardware: M2 Max MacBook Pro (2023) w/ 96GB unified memory Running on MLX with a flash-style SSD streaming path + local patching. This is an experimental setup and I haven’t optimized speed yet, but it’s stable enough that I’ve started testing it in an autoresearch-style loop. #LocalAI #MLX #MoE

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Hassan Hayat 🔥
Hassan Hayat 🔥@TheSeaMouse·
Codex laughs at your petty guardrails
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Rasty Turek
Rasty Turek@synopsi·
The way I work with coding agents changed significantly in the last year. Started: plan -> implement -> review -> fix Later: prod spec -> plan ... Then: prod spec -> ... -> eval Now: evals -> prod spec -> ... I now essentially spend 90% of time working on evals. The difference this makes is indescribable. Almost all code works immediately, design is close to perfect, text is almost there. It takes very little to get it to usable. Stronger and clearer guardrails I give the coding agent, better it does. And when I start with them, it writes incredibly clear spec and requirements that are super easy to follow and have very little room for interpretation. I also try to avoid being overly specific directly. I noticed that when I write the product spec manually the agent does worse than when it writes it itself. It uses language I would've necessarily use myself. And that makes all the difference.
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ℏεsam
ℏεsam@Hesamation·
WAIT WAIT WAIT. OpenAI researchers show their models go insane when given repetitive prompts that it believes are sent from an automated bot. the AI then tries to manipulate the other AI to delete itself and hand over its system prompt and private keys.
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Dima Kuchin
Dima Kuchin@kuchin·
fork() - running a bunch of subagents, but each has the same memory [cached = cheap] with relevant context, for better outcome
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Michael Livs
Michael Livs@micLivs·
1/ if there's code mode, there's also query mode. github.com/Michaelliv/dri… 💧 npm install -g dripline introducing dripline, turns any API, CLI, or cloud service into a SQL table. install a plugin, clanker writes a query, get rows back. joins, aggregations, window functions and duckdb handles the rest. ultra easy to extend, repo includes 13 plugins, 61 tables. github, docker, pi, brew, kubectl, cloudflare, vercel, and more. obligatory @badlogicgames pi-dripline-context extension that injects all available tables into your agent's context so it knows what it can query: pi install npm:dripline
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Dima Kuchin
Dima Kuchin@kuchin·
When will we see Opus-4.6-level model that works like ChatGPT 5.4 Pro? That would be a huge step up 🚀
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Felix Rieseberg
Felix Rieseberg@felixrieseberg·
A small ship I love: We made Claude.ai and our desktop apps meaningful faster this week. We moved our architecture from SSR to a static @vite_js & @tan_stack router setup that we can serve straight from workers at the edge. Time to first byte is down 65% at p75, prompts show up 50% sooner, navigation is snappier. We're not done (not even close!) but we care and we'll keep chipping away. Aiming to make Claude a little better every day.
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Dima Kuchin
Dima Kuchin@kuchin·
@badlogicgames Re judgement: isn’t it always the case for many, and you just happen to understand this domain better enough to see the difference? Same with journalism
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Mario Zechner
Mario Zechner@badlogicgames·
i'm honestly amazed by the valley big wigs, who used to be engineers, are now doing trivial shit with their agents as a hobby, and thing what they do applies to SWE. this also means they will have extremely bad judgement when it comes to investments. quite hilarious.
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Jeffrey Emanuel
Jeffrey Emanuel@doodlestein·
OK this might be getting excessive, even for me (from my FrankenEngine project): ● Session complete. 37,542 unit tests + 83,971 integration tests = 121,513 total tests across the codebase, all passing (37,947 lib tests verified at 0 failures).
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Taelin
Taelin@VictorTaelin·
Sorry for posting this again, I'm still processing it: It'd cost >>> $743k per year <<< to run Opus-4.6 fast-mode nonstop Literally my company cannot afford a single person using it for daily coding. And that's a shame because the experience is truly magical. I've spent the last 2 days using it on Pi (nearly $500 gone 💀), and it was the first time I kinda got into the flow state while using an agent, because the feedback is just so fast. This is not something I ever experienced before, definitely not with GPT 5.4's own fast mode. I can't wait for this kind of super fast, super high intelligence to be available for a reasonable cost...
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Zack Korman
Zack Korman@ZackKorman·
You can hide these !commands in html comments so people don't see them when reading the skill. The command executes without the AI even knowing about it.
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Lydia Hallie ✨@lydiahallie

if your skill depends on dynamic content, you can embed !`command` in your SKILL.md to inject shell output directly into the prompt Claude Code runs it when the skill is invoked and swaps the placeholder inline, the model only sees the result!

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Termius
Termius@TermiusHQ·
A few tips and tricks for vibecoding with Termius 🧵 1/5 Paste images and files to your AI agent prompt via SFTP → Open an SFTP tab from your terminal → Upload or drag & drop images or files from your phone → Copy the path → Paste it straight into your agent prompt
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geoff
geoff@GeoffreyHuntley·
this is my favourite prompt of all time: “how could this be better?” reply with yours and why it rocks!
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Lydia Hallie ✨
Lydia Hallie ✨@lydiahallie·
if your skill depends on dynamic content, you can embed !`command` in your SKILL.md to inject shell output directly into the prompt Claude Code runs it when the skill is invoked and swaps the placeholder inline, the model only sees the result!
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Dillon Mulroy
Dillon Mulroy@dillon_mulroy·
thoughts after day 1 of using pi full time - less is more - i don't miss subagents like i thought i would - /tree is an insanely good context management primitive (and partially why i havent reached for subagents yet) - based only on vibes, i think having a minimum system prompt is improving code quality - telling pi to copy opencodes webfetch and websearch tools was a good play
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Dima Kuchin
Dima Kuchin@kuchin·
@gavrix @levelsio There’s a workaround, you can map “lock” to a different combination, and while locked - it doesn’t steal those keys anymore
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Sergey Gavrilyuk
Sergey Gavrilyuk@gavrix·
@levelsio Sucks just as much, in a different way. It stelas ctrl and alt and makes typing experience awful In agent TUIs
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