Mr. Buzzoni
@polydao • 18,635 subscribers
AI Wizard & Builder | Exploring the frontiers of intelligence CEO @polynternet Open to partnerships · DMs always open
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Atlassian's revenue: $1.79 billion last quarter Atlassian's move: fire the engineer who built their infrastructure his move: post a 38-minute breakdown of every system he built, free for anyone to copy what he revealed: > Envoy proxy instead of enterprise load balancers > sidecar architecture for auth, logging, rate limits > DynamoDB + SQS for async provisioning > Packer + SaltStack for automated VM deployments at scale Atlassian charges per employee across 350,000 customers this guy just handed you the enterprise playbook for free save this
Mr. Buzzoni21,444,996 views • 20 days ago
KARPATHY WAS RIGHT. THIS 40-MINUTE Y COMBINATOR LECTURE PROVES IT Karpathy said we're in the 1960s of AI - most people using Claude Opus 4.8 are still acting like it's just a search engine > software 3.0 - LLMs as operating systems, not chatbots > autonomous agents that run entire workflows without you watching the 32 skills in this article are how you actually cross that line bookmark this 👇
Mr. Buzzoni556,349 views • 4 days ago
KARPATHY JUST DROPPED 2 HOURS OF BRUTAL HONESTY ABOUT AI > we're nowhere near real autonomous agents - including Claude Opus 4.8 > AGI will blend into daily life and nobody will notice > he quit AI research to fix education. that's the problem he thinks matters more save this👇
Mr. Buzzoni323,527 views • 3 days ago
> do you understand what Claude Opus 4.8 just did to the Google job market > a senior Google engineer with 11 years of experience > stacked 32 Claude skills on top of his workflow > 8hrs → 2-3hrs per day > $95K developer vs $300K AI architect > same job. different stack. very different salary > the exact skill list is here 👇
Mr. Buzzoni283,478 views • 5 days ago
This guy plugged a DGX Spark (the $3K Nvidia box) and a Mac Mini M4 together to run AI and what happened next surprised everyone > the Nvidia box handles the hard part - processing your prompt in milliseconds > Mac Mini M4 handles the fast part - generating the response at memory bandwidth speeds nothing else can match > together they hit 84 tokens per second on Llama - 6x faster than the Spark alone > running compute agents locally on this setup means your data never leaves your hardware > two boxes. two different architectures. one AI system that Deepseek runs at data center scale he ran it on his desk save this. the way we build local AI is about to change
Mr. Buzzoni150,973 views • 5 days ago
This girl from IBM explained how Claude works better than most AI engineers could in 8 minutes > search used to match words, not meaning > then AI learned to understand intent > then RAG gave LLMs external memory - so they could read your documents > then agents arrived - now the AI decides what to search, when, and why the hardest part of AI isn't generating the answer it's knowing what to look at first full video above
Mr. Buzzoni518,170 views • 21 days ago
Vasilios Syrakis is back after the massive success of his Atlassian video, he just dropped a follow-up addressing everything the stuff people really wanted to know: > no university degree, dropped out after 10th grade, started in help desk > taught himself everything from scratch - books, videos, no mentor > he didn't break any NDA - Atlassian published more detailed info themselves > the architecture was 10 years old - he'd build it completely differently today and the thing that hit hardest: > to everyone who felt impostor syndrome watching his first video - he said the gap between you and someone who knows more is usually just time, not intelligence the full response is above and he's building a control plane from scratch on camera soon so you can see exactly how it's done
Mr. Buzzoni389,886 views • 16 days ago
Jane Street needed a 4,032 GPU liquid-cooled data center just to run their trading models > that tells you everything about how much money this firm makes and why their quants start at $400K/year someone just got inside and filmed it > custom AI and trading agents trained specifically for this firm - off-the-shelf doesn't cut it > packets processed in under 100 nanoseconds > copper over fiber because electrons beat light at that scale > automated kill switches to shut algorithms down before downtime costs millions > financial privacy of their positions is protected at infrastructure level - nothing leaks 20 years ago their cluster was 6 Dell boxes on an office floor > this is the machine now what do you think - is this level of infrastructure even possible for smaller firms?
Mr. Buzzoni240,073 views • 14 days ago
KARPATHY JUST DROPPED A 2-HOUR INTERVIEW AND IT'S THE MOST HONEST THING IN AI RIGHT NOW watched the whole thing. three things hit me hard: > we're nowhere near real agents - including Claude > AGI will blend into daily life and nobody will notice > he quit AI research to fix education. because that's the actual problem save this 👇
Mr. Buzzoni195,398 views • 1 month ago
Claude Code will grill you with 40+ questions before writing a single line of code > it's called /grill-me - 3 sentences long. most impactful skill I use instead of jumping straight to code - it walks every branch of your design tree until there's zero ambiguity > every question reveals something you hadn't thought of other skills I use daily: > /write-a-prd - idea → proper product doc > /prd-to-issues - doc → GitHub issues automatically > /tdd - tests first, forces edge case thinking before code > /improve-codebase-architecture -> full structural review of your codebase all links and full breakdown in my article full video from Matt Pocock 👇
Mr. Buzzoni223,250 views • 1 month ago
This beginner guide to Karpathy's LLM Wiki is one of the most useful AI videos i've shared this year Karpathy's idea: instead of asking AI questions every time, make it build you a permanent knowledge base that grows smarter over time > drop your documents into a folder > Claude reads them and builds a structured wiki in Obsidian > every time you add a new source, Claude Sonnet updates existing pages and links new ideas > ask complex questions - Claude Opus answers from the organized wiki, not raw files it's like having a researcher who never forgets and connects dots across everything you've ever given it full setup guide is in the video above
Mr. Buzzoni57,885 views • 20 days ago
This 1-hour crash course is exactly how Envoy works under the hood - what the Atlassian engineer used instead of expensive enterprise load balancers Hussein Nasser covers the real internals: > Listeners → Clusters → Network Filters - Envoy's core architecture > L7 routing and L4 TCP load balancing > TLS from scratch: Let's Encrypt, HTTP/2, blocking TLS 1.0/1.1 - SSL Labs A rating > why thread-per-connection breaks round-robin by default the YAML is painful. the architecture is genius watch this before reading the post above
Mr. Buzzoni51,160 views • 18 days ago
This 1-hour MIT Probability Theory lecture is the mathematical foundation behind the 3 formulas top traders use > Law of Large Numbers - a tiny edge compounds into profit over enough trades > log-normal distribution - why modelling markets with normal distribution fails every time > Shannon entropy - how to detect insider information before it moves the price 87% of wallets on prediction markets lose the ones who win understand this math watch this
Mr. Buzzoni37,741 views • 23 days ago
I ASKED MIROFISH TO LOOK AT 10,000+ POLYMARKET WALLETS this is what stood out ↓ > dense clusters of high-EV actors > clusters of top traders focusing on similar markets > wallets reacting to the same info within short windows > patterns repeating across different events nothing magical > but definitely not random it starts to look like a simple multi-agent system: > people updating beliefs > acting on new information > slowly pushing prices toward probability in other words: > a live network of Bayesian updates the insight is simple but uncomfortable: > price is just the surface > the real signal is in how agents interact once you model that layer > you’re not just reading markets > you’re reading the system behind them you can explore the same wallets here: and the interesting part: > edges don’t come from predicting events > they come from spotting where the network hasn’t converged yet
Mr. Buzzoni69,513 views • 2 months ago
THIS SDK TURNS OPENCLAW BOT INTO POLYMARKET TRADER > someone actually shipped a real SDK for OpenClaw🦞 that lets you automate trading on Polymarket > weather-based trades, copytrading, RSS signal sniping - all controlled from chat is wild > huge W for Spartan Labs this is exactly where OpenClaw was heading installing this now and going to play with it myself - will report back > now the only thing left is to make it trade this market: Moltbook AI agent sues a human by Feb 28?
Mr. Buzzoni71,974 views • 4 months ago