Gusler

@cruciaall most people upgrade the model before fixing the map

YOUR AI AGENT IS BURNING AN HOUR OF YOUR DAY DOING SOMETHING A STICKY NOTE COULD FIX it digs through old projects, opens the wrong files and wastes 90 seconds on something that should take 5. one developer tracked this across 200 tasks and found he was losing over an hour a day just to bad navigation he added one index file per major folder - every connection mapped, the agent knowing exactly what lives where. tasks dropped from 2 minutes to 10 seconds overnight no model upgrade, nothing to install. one afternoon of work that permanently changed how fast everything runs full breakdown in the article below ↓

@pilsnoir wild how the smartest model still loses to bad signage

HIS AI AGENT SPENT 2 MINUTES ON WHAT SHOULD TAKE 10 SECONDS AND THE REASON WAS UNEXPECTED he ran Hermes on Opus, GPT-5 and the best models on the market but all of them opened 7 files just to find one the problem wasn't the model, he built his folder structure for himself, not for the agent and it was walking in the dark every single time he added one INDEX.md file to each major folder that tells the agent where everything lives 2 minutes and 7 files became 10 seconds and 1 file the model didn't change, one text file changed everything

50 FANVUE SUBS AT $9.99 A MONTH NET $425 AFTER THE PLATFORM CUT, THE $5,300 SECOND MONTH THE ARTICLE OPENS WITH CAME FROM PPV MESSAGE PRICING THE MCP AUTOMATES AND THE ARTICLE BURIES IN ONE LINE 00:04 the frame swaps from the creator to an AI blonde standing in the same room with the same lamp, the same globe on the shelf and the same airpod in her ear a Fanvue sub costs $9.99 a month and the platform takes 15% off the top, 50 subs from a viral reel nets $425 in monthly recurring, the article's $5,300 second month cleared a floor twelve times higher than the sub base could produce every dollar past that floor came from pay per view messages priced individually per conversation, a nude clip starts at $15 and scales to $200 on a warm buyer, one whale on autopay outsells fifty base subs in a single week the Fanvue MCP the article credits for reply drafting reads every conversation for buying signal and prices each PPV send by temperature, the article gives this one line about "what pricing you should set" and spends six sections on ComfyUI LoRAs and Kling reels the ComfyUI stack is the beginner filter and the PPV pricing layer is the money, the creator who cleared $600 to $5,300 in one month did it by letting the MCP send $50 messages at 3am to buyers Claude flagged as ready, the face swap gets you subs and the PPV pricing gets you paid follow now. read the article below tonight

240 GENERATIONS OF A RABBIT AI COMPOUNDED ON ONE FITNESS FUNCTION WITH ZERO ARTIFACT FILES, THE ARTICLE'S 8 SECTION OUTER LOOP FRAMEWORK IS THE 1998 NEAT PATTERN WITH NEW NAMES 00:23 the rabbit's output layer picks Rest at 0.08 with Flee Hide MoveToFood and Eat all pinned at 0.01, "generation two hundred and forty, it stopped fleeing every fox two nights ago" the network wires 6 sensors into four hidden layers into 5 actions, NEAT selects whichever rabbit lived longest each generation and mutates its weights into the next population the whole training loop runs on one scalar fitness value with no signal.md, no LOG.md, no loop contract and no verifier agent watching a Playwright clip, either the rabbit survived or it didn't the article maps a 4 component outer loop plus a codebase harness plus a 3 type artifact system plus a global log to compound the same way this rabbit does on one fitness reading, business loops need all of it because "did this ticket resolve" has no ground truth the rabbit compounded in 240 generations on a desk with an rgb keyboard, the article's outer loop compounds after five loops share a folder for months and someone reads LOG.md by hand, one runs on a fitness function and the other on discipline that decays the moment nobody enforces it follow now. read the article below tonight

@Xyroxxl great post, bookmarked

THIS DEVELOPER WAS SPENDING $459 A MONTH ON AI SUBSCRIPTIONS AND DIDN'T EVEN NOTICE UNTIL HIS RENT BOUNCED on a tuesday night in march he opened his banking app and saw his card at minus $187 cancelled every subscription within 20 minutes and ordered a used RTX 3090 the same night for $700 4 months later the card paid for itself twice and now runs bigger models locally than what Claude Code Max was serving him and when hes not using it it rents itself out on Vast ai and clears $500 to $700 a month while he sleeps by month 6 the total swing was over $1,100 a month in his favor the math after 3 years is $42,000 difference from one used GPU sitting on a desk and thats just one option there are 5 levels to this starting from $249 a $249 box runs 7B models all day a $599 Mac Mini replaced Claude Pro for thousands of developers a $700 used GPU beats Anthropics flagship on benchmarks a $1,700 mini PC runs 200 billion parameter models locally the whole subscription stack that made sense in 2024 broke by mid 2026 and almost nobody is talking about it clearly full breakdown of all 5 levels drops next follow so you dont miss it

@pilsnoir old gaming pc under the desk quietly earning while he sleeps

THIS CANADIAN ENGINEER BOUGHT A GPU FOR $700, MADE $2,400 IN HIS FIRST MONTH AND STOPPED PAYING FOR AI COMPLETELY he had an old gaming PC under his desk that booted up for Spotify and shut down again, meanwhile his credit card was showing $412 a month in AI subscriptions 0:10 he holds up the RTX 3090 and drops it into that same PC, pointing it at local AI models that now run entirely on his own hardware automated jobs handle everything while he sleeps, his inbox gets sorted, notes archived and phone only buzzes when it matters then by the end of the first week his setup was generating more than he used to pay in subscriptions $2,400 in passive income the first month from a $700 card and his AI bill dropped from $412 to $20 while you're reading this, his GPU is already running

@cruciaall people leaving projects unfinished told you everything

THE US GOVERNMENT TRIED TO BURY THE MOST POWERFUL AI MODEL EVER BUILT - AND FAILED fable 5 is back in claude and the people who used it the first time already know what that means three weeks ago developers were finishing in one session what used to take a full team a week. entire web platforms, 40-page reports, complex analysis - done without a single follow-up prompt then washington panicked. export controls landed 3 days after launch and anthropic pulled it globally overnight with no warning people left active projects unfinished. they knew no other model came close and would rather wait than settle now it's back with up to 50% of weekly usage included until july 7th. after that it runs on credits at $50 per million output tokens - about 7 cents per thousand words some testers say this build feels even sharper than the original. others think it was quietly adjusted. the next two weeks will answer that don't scroll past it , the full breakdown is below ↓

FOUR MILLION AMD MINING PULLS FROM THE ETHEREUM MERGE SIT ON THIS SHENZHEN FLOOR AT $220 A CARD, THE ARTICLE'S USED GPU TIER SKIPS EVERY ONE OF THEM 00:14 the operator lifts a PowerColor Hellhound off the top of a pallet, "these came out of a farm in inner mongolia last month, twenty thousand of them, they sell faster than we can bench them" a used RX 6800 16GB ships from this shenzhen warehouse at $220 with 16GB of GDDR6 and a gfx1030 die that ROCm 6.x supports first class, most cards on the pallet never rendered a single game frame ollama shipped native ROCm backend in november 2025 and the same install command from the mac path works on any RDNA2 card, qwen 2.5 14B holds at 40 tokens per second on a single 6800 against 22 on the Tesla M40 the article opens the used tier with the article maps a $130 Maxwell M40 on one end and a $700 Ampere 3090 on the other, the RDNA2 merge dump tier this warehouse ships daily sits between them at $220 with 3090 class throughput on any workload that fits in 16GB the article assumes one card in an existing gaming pc, the density buyer on this floor stacks two 6800s on a $70 B450 board for 32GB pooled VRAM at $500 total silicon, the whole box costs less than one month of the $412 subscription stack the article opens with follow now. read the article below tonight

@pilsnoir client thinks it's an 8 person studio, one guy and a config

@GVausort nice post, man

his clients pay $6,000 retainers thinking an 8 person studio is behind every commit. chen wei runs it solo from his kitchen in chengdu with claude code and one AGENTS.md file chen wei was 3 months behind on rent in january when he found the AGENTS.md pattern stripe used to migrate a 50 million line ruby codebase in a single day that weekend he built 5 skill files for frontend backend security database and deployment. by monday he shipped a car dealership crm in 2 days that his old freelance rate would have quoted at 2 weeks the dealership owner asked how big his team was and chen wei said just him. the owner made him pull up every commit diff and walk through the pull requests one by one until a $6,000 retainer landed in stripe that afternoon every project now runs through the same loop of research planning coding and review subagents. chen wei only touches the keyboard to approve the plan at the start and merge the pull request at the end three months later he runs 4 clients on retainer plus 2 saas products he shipped solo. monthly revenue lands at $44,500 against a $67 tool bill with nobody else on payroll follow now. read the article below tonight

CEO de Palo Alto Networks: "en 6 semanas encontramos vulnerabilidades que nos hubieran tomado 5 a 7 años en encontrar. estamos a 3 meses de que esto esté disponible en open source." - All-In Podcast · 31 min con Nikesh Arora · min 2:54 Mythos · Claude · ultra mode · RL vale más que cualquier curso de "AI para hackers" de $1.000

Cofundador de OpenAI: "nunca me he sentido tan atrasado como programador. en diciembre algo cambió fundamentalmente. dejé de corregir al agente. simplemente confié más y más. ahora vibe codeo todo el día." (min 1:18) En la AI Startup School de Y Combinator, en una charla de 28 minutos, Andrej Karpathy explica por qué los devs que no se adaptaron en los últimos 6 meses ya están atrás. Claude Code + agentic engineering + context window Vale más que cualquier curso de "AI para devs" de $500 momentos clave: 3:44 - software 3.0 explicado con la instalación de OpenClaw 4:54 - el momento Menu Gen + Nanobanana que rompe paradigmas 11:18 - Opus 4.7 encuentra zero-days pero te dice que camines 50m a un car wash 16:55 - "10x ya no es el speedup" = el techo real del agentic engineering 28:05 - "puedes externalizar tu pensamiento, pero no tu entendimiento"

THIS GUY CONNECTED OBSIDIAN TO AN AI AGENT AND NOW HIS SECOND BRAIN RUNS 7 AUTOMATED WORKFLOWS WHILE HE SLEEPS he dropped 5 skill files into hermes agent on a saturday afternoon and configured one filesystem path pointing at his obsidian vault by sunday night the system was reading his notes, filing his inbox, generating morning briefs and updating his project health report without him touching anything his colleagues are still copying meeting notes into notion and wondering why they can never find anything two weeks later the only thing separating them is one connection between a knowledge base that stores everything and an ai agent that actually acts on it at 6am his vault generates a full brief from his own notes before he opens his eyes, at 8pm it empties his inbox automatically, every sunday it synthesizes the entire week and rewrites his priorities for monday

THIS DEV SPENT $47 ON KIMI K2 TOKENS AND NOW MAKES $28,735 A MONTH FROM A FITNESS APP he opened openrouter on a friday night, dropped one prompt and went to sleep by sunday he had a working mvp with stripe, supabase and an ai coach that adapts to every user automatically his former colleagues are still waiting for sprint approval and debating architecture in notion the only thing separating them is kimi k2 holding 256k tokens of context and seeing the entire project at once while other models lose the thread by file three he spent $47 on tokens to build it, charges $9.99 a month, and now has 3,000 users paying him every month without a team or an office bookmark this and check the full breakdown below

the same week nvidia launched a $249 ai box that replaces $200/month in cloud subscriptions, this person is selling a $45 diy kit that teaches you to build your own hardware from scratch and it sold out in 3 days the kit ships with a raspberry pi zero, pre-cut components, and a soldering guide. you build it yourself in an afternoon. no experience required. she started selling them from her apartment in london 8 weeks ago. first batch was 50 units. sold out in 72 hours. second batch was 200 units. sold out in 4 days. she is now on her third batch of 400 and has a waitlist of 600 people. total revenue in 8 weeks is $19,350. her margin is 71% because the components cost $13 and she ships in a flat envelope. the skills you learn building the kit take an afternoon. the understanding of how hardware actually works is something no youtube tutorial ever gave people before. her day job paid her $38,000 a year. she matched that in 8 weeks selling kits from her kitchen table. her employer found out and asked her to come back. she offered to sell them 50 kits for their engineering team instead. the gap between people who buy finished hardware and people who understand how it works compounds every single day.

a chinese developer linked 2 nvidia boxes with one cable, 256gb of unified memory, and now runs models that openai charges $3,000/month for. jensen just showed what comes after that the two boxes sit on his desk connected by a single cable. qwen 235b running locally, no cloud, no subscription, no data leaving the room. his monthly electricity bill for both boxes is $6. he was paying $2,800/month for cloud gpus before. he bought both devices for $6,000 total and broke even in 67 days. jensen huang walked on stage at computex holding the next generation of that hardware. models that currently take 3 weeks to train will train in 4 days. data centers running at capacity today will look like calculators compared to what this enables. in 2018 nobody believed the gpu bet. nvidia went from $100b to $3.3 trillion in 6 years. the developer in shanghai saw what was coming before anyone else. he already runs models on his desk that cost enterprises hundreds of thousands of dollars a year to access through the cloud. jensen just showed what the next version of that looks like. the gap between people who wait for the cloud to get cheaper and people who buy the hardware compounds every single day.

a 23-year-old spent 6 hours copy-pasting code and built a second brain with 1,400 notes that now generates $4,800/month in consulting work he had zero coding experience. he just followed a guide, copy-pasted the setup into a Mac Mini, connected Claude to his Obsidian vault, and watched it start reading 1,400 notes he had accumulated over 2 years. the first time he asked it a question about a client problem, it pulled a note he had completely forgotten about from 14 months ago that was exactly relevant. he had spent 3 hours researching the same thing twice. that moment changed how he worked. setup cost was $700 for the Mac Mini and $0 in monthly subscriptions. the system runs locally, nothing leaves his machine. within 90 days he had packaged his knowledge system into a consulting offer. he now charges $1,600 per client to build the same setup for their business. he closed 3 clients in the first month. his former employer offered him a raise to come back full time. he was already making more than the salary they offered. the gap between people who store notes and people who build systems that think with their notes compounds every single day.