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A GERMAN DEVELOPER REPLACED HIS ENTIRE DEV TEAM WITH KIMI K2.6, VISUALIZED EVERYTHING IN OBSIDIAN AND NOW MAKES $80,000/MONTH SOLO 1 trillion parameters, 32 billion activated per token and a SWE-Bench score of 65.8 - Kimi K2.6 reads the entire client codebase, understands the architecture, writes production code and...

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Noisy

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12-person agency and a solo guy both quoted $40k for the same project. BOTH GOT HIRED one made $39,700 profit. the other made $8,000 he runs Kimi K2.6 - 300 parallel sub-agents, $0.60 per million tokens project delivered in 4 days. agency delivered in 6 weeks clients don't see a team. he doesn't have one entire agency playbook - PM, devs, designer, QA, copywriter - all replaced by a prompt $80k last month, $220 in API costs 14-person shop down the street is paying those same $80k back out in salaries Bookmark it and use for your works agencies weren't charging for skill they were charging for people who had to show up that model just broke
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12-person agency and a solo guy both quoted $40k for the same project. BOTH GOT HIRED one made $39,700 profit. the other made $8,000 he runs Kimi K2.6 - 300 parallel sub-agents, $0.60 per million tokens project delivered in 4 days. agency delivered in 6 weeks clients don't see a team. he doesn't have one entire agency playbook - PM, devs, designer, QA, copywriter - all replaced by a prompt $80k last month, $220 in API costs 14-person shop down the street is paying those same $80k back out in salaries Bookmark it and use for your works agencies weren't charging for skill they were charging for people who had to show up that model just broke

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KIMI K2.6 JUST CRUSHED GPT-5 AND A SINGLE PERSON CAN NOW POTENTIALLY BUILD AN $80K/MONTH BUSINESS WITH 300 AI AGENTS AND JUST $500 IN OVERHEAD The video attached is proof that almost everyone missed Kimi K2 Thinking didn’t just score 44.9% on Humanity’s Last Exam, it outperformed GPT-5 (41.7%), Claude, and every other major model across multiple benchmarks It’s open source Over a trillion parameters, trained for just $4.6M Runs locally on a Mac Studio and in the demo, it turns a 100-page PDF into a fully designed PowerPoint presentation in under two minutes while other models are still thinking In the article below, the author lays out a clear blueprint for turning this into a real business: > 300 parallel sub-agents running up to 4000 steps per execution - research, coding, analysis and visual creation all happen simultaneously > 65.8% on SWE-Bench solving real GitHub engineering tasks end-to-end with little to no human intervention > Skill injection through simple .md files - instant vertical specialization (HIPAA compliance, financial regulations, Shopify workflows and more) > Automated client acquisition: monitor job listings for “Data Analyst” or “Automation Engineer” roles and pitch an AI solution before companies even start hiring The math is simple: A $10k project Traditional agency → salaries, office costs, QA, project management and overhead eat most of the profit AI agency powered by Kimi → roughly $500 in operating costs plus one operator managing client relationships = the potential for 72k$+ monthly profit at scale Read the article Save this post Start building AI-native agencies while everyone else is still doing things the old way
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KIMI K2.6 JUST CRUSHED GPT-5 AND A SINGLE PERSON CAN NOW POTENTIALLY BUILD AN $80K/MONTH BUSINESS WITH 300 AI AGENTS AND JUST $500 IN OVERHEAD The video attached is proof that almost everyone missed Kimi K2 Thinking didn’t just score 44.9% on Humanity’s Last Exam, it outperformed GPT-5 (41.7%), Claude, and every other major model across multiple benchmarks It’s open source Over a trillion parameters, trained for just $4.6M Runs locally on a Mac Studio and in the demo, it turns a 100-page PDF into a fully designed PowerPoint presentation in under two minutes while other models are still thinking In the article below, the author lays out a clear blueprint for turning this into a real business: > 300 parallel sub-agents running up to 4000 steps per execution - research, coding, analysis and visual creation all happen simultaneously > 65.8% on SWE-Bench solving real GitHub engineering tasks end-to-end with little to no human intervention > Skill injection through simple .md files - instant vertical specialization (HIPAA compliance, financial regulations, Shopify workflows and more) > Automated client acquisition: monitor job listings for “Data Analyst” or “Automation Engineer” roles and pitch an AI solution before companies even start hiring The math is simple: A $10k project Traditional agency → salaries, office costs, QA, project management and overhead eat most of the profit AI agency powered by Kimi → roughly $500 in operating costs plus one operator managing client relationships = the potential for 72k$+ monthly profit at scale Read the article Save this post Start building AI-native agencies while everyone else is still doing things the old way

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Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!
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Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!

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THIS CHINESE DEVELOPER VISUALIZED WHAT 300 KIMI K2.6 AGENTS LOOK LIKE IN ACTION - AND IT LOOKS EXACTLY LIKE A BRAIN WORKING FOR YOU every line on screen is a connection firing in real time - hundreds of neurons across multiple layers, activations lighting up, signals passing through the network simultaneously in both directions this is not a diagram and not a concept - this is the actual mechanics of what happens inside the model every time it processes your request now multiply that by 300 parallel agents running 4,000 coordinated steps at the same time - while you drink coffee the entire system fires neurons and does the work for you a team paying $62,000/month on Claude Opus cut their bill to $129 by switching to Kimi K2.6 as the execution layer - Opus plans, Kimi executes, $54,000/month stays in the business what looks like fire on screen is your new employee who never sleeps, never asks for a raise and never goes on vacation most people pay for subscriptions that forget everything tomorrow - he built a system that works and compounds while he sleeps
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THIS CHINESE DEVELOPER VISUALIZED WHAT 300 KIMI K2.6 AGENTS LOOK LIKE IN ACTION - AND IT LOOKS EXACTLY LIKE A BRAIN WORKING FOR YOU every line on screen is a connection firing in real time - hundreds of neurons across multiple layers, activations lighting up, signals passing through the network simultaneously in both directions this is not a diagram and not a concept - this is the actual mechanics of what happens inside the model every time it processes your request now multiply that by 300 parallel agents running 4,000 coordinated steps at the same time - while you drink coffee the entire system fires neurons and does the work for you a team paying $62,000/month on Claude Opus cut their bill to $129 by switching to Kimi K2.6 as the execution layer - Opus plans, Kimi executes, $54,000/month stays in the business what looks like fire on screen is your new employee who never sleeps, never asks for a raise and never goes on vacation most people pay for subscriptions that forget everything tomorrow - he built a system that works and compounds while he sleeps

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THIS OXFORD STUDENT CONNECTED OBSIDIAN TO KIMI AND LET THE BRAIN DO ALL HIS HOMEWORK - NOW MAKES $3,000/MONTH FROM CLASSMATES vault connected to Kimi K2.6 via MCP - every lecture note, every paper, every past exam feeds into the base automatically one prompt before each assignment - 300 agents scan the entire vault, find relevant research, cross-reference lecture notes and return a structured answer in his own style via Document to Skill practical assignments: agent pulls his previous work, matches the format his professor expects and generates the submission with citations from his actual notes classmates pay $50-100 per session for the same output - he runs their materials through the same pipeline and delivers in hours what takes them days Smart Connections finds semantic links between notes automatically - two papers on the same topic get connected even if he never linked them manually every result saves back into the vault - next assignment starts smarter than the last Obsidian free, MCP server open source, Kimi API costs cents per run - and classmates keep paying because the output is better than anything they produce manually

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THIS CHINESE DEVELOPER'S OBSIDIAN BRAIN MAPS EVERY CLIENT CONVERSATION - ZERO EMPLOYEES, $40,000/MONTH, CATCHES PROBLEMS BEFORE CLIENTS DO every node on screen is a conversation - green for happy clients, yellow for neutral, red for problems that need attention - the brain sees the emotional state of the entire business in real time this is not a CRM, not a dashboard, not a spreadsheet - it's a living map of every client interaction that fires connections and surfaces patterns no human account manager would ever catch when a cluster starts turning yellow the brain flags it before the client sends the complaint - when a green cluster grows it identifies what's working and replicates it across every other account automatically he replaced a $15,000/month account management team with one Obsidian brain that never sleeps, never misses a message and never needs a performance review no employees, no contractors, no standups, no payroll - just one developer, one brain and one delivery system doing the work of 10 people $40,000/month - solo - from a system that gets smarter every single conversation
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16-year-old American launched his own marketing agency and replaced a team of four with one Claude and two tools. ChatGPT writes a video prompt - a hyper-realistic scene of a house after storm damage to the roof. Pastes it into Google Gemini VEO 3. Two minutes and a finished video that didn't exist before. Drops it into CapCut with real footage from the client. Under an hour of editing and a complete ad ready to launch. Then he connected a repo with 139 marketing tactics, 12 SEO playbooks, a CRO framework and a pricing system to Claude - everything a marketing agency charges $10,000 a month to do by hand Claude executes in an hour. While competitors invoice for weeks of work he delivers in a day and charges the client $3,000. An entire agency replaced by one 16-year-old and two tools.

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SOMEONE BUILT AN OBSIDIAN VAULT THAT RUNS THEIR ENTIRE BUSINESS WHILE THEY SLEEP Every morning at 6AM four things are waiting before they open a single app - project pulse across every active client, content brief with ranked angles for the day, intelligence summary of what matters in their industry and a pre-call brief generated 30 minutes before every meeting with full relationship history and suggested agenda. They log a payment in their daily note and the revenue tracker, client folder and invoice records all update automatically. They drop a research request before bed and the brief is ready when they wake up. The system reads a single file - business identity, active clients, revenue targets, voice - before every operation so every output is business-specific rather than generic AI noise. Total cost: $5/month for a server and $20/month for Claude. Month one the system learns the business. Month six it runs it.

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THIS GUY USED OPUS 4.8 + KIMI K2.6 TO CUT HIS CODING BILL FROM $4,000 TO $700/MO. WITH KIMI RUNNING A 300-AGENT CODING FLOOR, HE STOPPED PAYING CLAUDE TO DO EVERYTHING kimi does the cheap heavy lifting. it can spin up hundreds of agents, push through thousands of steps, write the rough code, expand files, draft tests and handle the repetitive work that burns the most tokens opus 4.8 only comes in where the money is worth spending. first to plan the spec and define the rules, then again to tear apart the output, catch weak logic and flag the bugs that a fast swarm can miss that is what changed the economics. kimi handled the bulk of the volume for a fraction of the price, while opus stayed in the loop as the architect and the reviewer instead of the full-time builder most people still use one model for every step and wonder why their costs explode. this guy split the jobs properly. kimi runs wide and cheap. opus goes deep and skeptical. one builds fast, the other makes sure it should ship the real edge is not finding one perfect model. it is knowing where expensive intelligence actually matters and where cheap parallel output is already enough. that is how a $4,000 workflow turns into a $700 system
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THIS GUY USED OPUS 4.8 + KIMI K2.6 TO CUT HIS CODING BILL FROM $4,000 TO $700/MO. WITH KIMI RUNNING A 300-AGENT CODING FLOOR, HE STOPPED PAYING CLAUDE TO DO EVERYTHING kimi does the cheap heavy lifting. it can spin up hundreds of agents, push through thousands of steps, write the rough code, expand files, draft tests and handle the repetitive work that burns the most tokens opus 4.8 only comes in where the money is worth spending. first to plan the spec and define the rules, then again to tear apart the output, catch weak logic and flag the bugs that a fast swarm can miss that is what changed the economics. kimi handled the bulk of the volume for a fraction of the price, while opus stayed in the loop as the architect and the reviewer instead of the full-time builder most people still use one model for every step and wonder why their costs explode. this guy split the jobs properly. kimi runs wide and cheap. opus goes deep and skeptical. one builds fast, the other makes sure it should ship the real edge is not finding one perfect model. it is knowing where expensive intelligence actually matters and where cheap parallel output is already enough. that is how a $4,000 workflow turns into a $700 system

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A GERMAN ENGINEER SPENT $7 ON COMPONENTS AND BUILT A CHIP THAT DOES WHAT $80,000 LAB EQUIPMENT DOES. HE POSTED THE BUILD ANYWAY he soldered 47 connections by hand in his bedroom in lithuania. the chip glows blue when powered. the comments on his post asked where to buy one and he replied that he couldn't sell them legally meanwhile a 19 year old in miami opened a shopify store 9 weeks ago and pulled $31,247 last month without shipping a single package. claude runs the entire store for $20 a month claude finds the products. writes every description. runs the ads. answers every customer email. tells him every sunday what to fix. he hasn't opened his inbox in 11 days a traditional shopify operator pays $2,600 a month before a single sale. copywriter $400, va $700, media buyer $1,500. that's why 90% of stores die before month three his total cost is $21 a month and he keeps $16,559 in net profit. six prompts run the whole operation and they're all in the article bookmark this and read the article below

starmex

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cursor just made every $200/month copilot subscription look like a scam dropped today with their own coding model what took 8 hours of manual coding now takes 30 seconds and it runs 8 versions of itself in parallel to pick the best solution while github's charging $20/month for autocomplete, cursor built an entire autonomous dev team composer model: → 4x faster than gpt/claude → completes full features in <30 seconds → tests its own code automatically → built with reinforcement learning on real codebases here's what's actually wild: most companies paying $150k/year for junior devs to do work this does for $20/month just saved a client $253k/month migrating their dev work to cursor's multi-agent system the intelligence gap between "we hired 3 developers" and "we deployed cursor" is getting stupid comment "COMPOSER" and ill send the full breakdown of how to replace your dev costs with this
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cursor just made every $200/month copilot subscription look like a scam dropped today with their own coding model what took 8 hours of manual coding now takes 30 seconds and it runs 8 versions of itself in parallel to pick the best solution while github's charging $20/month for autocomplete, cursor built an entire autonomous dev team composer model: → 4x faster than gpt/claude → completes full features in <30 seconds → tests its own code automatically → built with reinforcement learning on real codebases here's what's actually wild: most companies paying $150k/year for junior devs to do work this does for $20/month just saved a client $253k/month migrating their dev work to cursor's multi-agent system the intelligence gap between "we hired 3 developers" and "we deployed cursor" is getting stupid comment "COMPOSER" and ill send the full breakdown of how to replace your dev costs with this

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GREG ISENBERG JUST INTERVIEWED A SOLO FOUNDER WHO MAKES $1,000,000 A YEAR BUILDING AI AGENTS FOR REAL ESTATE AGENTS the agents cost $5,000 to $10,000 a month per client. boring industries pay the most. real estate, insurance, manufacturing, legal. they have money and they hate using ai he uses obsidian as his second brain because notion can't run agents that actually do work for him his entire stack: granola, trello, loom, superhuman, asana, codex, hermes, orgo, composio, agent mail. gpt 5.5 by default. claude opus for long coding sessions 99% of the market doesn't know what an ai agent is yet. that's the moat. you don't need to be the smartest. you need to be the one who calls them first the full breakdown is in the 45 minute video and it's worth every minute bookmark this and read the article below

starmex

493,306 Aufrufe • vor 1 Monat

A 22-YEAR-OLD FROM BEIJING BUILT A SECOND BRAIN WITH CLAUDE, MAKES $14,000/MONTH AND HIS AI REMEMBERS EVERY DECISION HE'S EVER MADE Most people open ChatGPT, ask a question and start from zero next session, re-explaining the same context every single time and losing 15–40 minutes per session doing it. He built infrastructure where Claude reads, writes and connects everything in Obsidian automatically so it never resets and compounds with every conversation. This morning he needed a client strategy from 3 months ago. Claude pulled it up instantly and drafted a full email reply in under 20 minutes using context it had been building for months across 6,000+ sessions. Every session adds to the last one and the system now saves him 2–3 hours every single day - 30–90 minutes from automated morning briefing alone, before he even opens his laptop. repo: The repo is free. The advantage it creates is not.
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A 22-YEAR-OLD FROM BEIJING BUILT A SECOND BRAIN WITH CLAUDE, MAKES $14,000/MONTH AND HIS AI REMEMBERS EVERY DECISION HE'S EVER MADE Most people open ChatGPT, ask a question and start from zero next session, re-explaining the same context every single time and losing 15–40 minutes per session doing it. He built infrastructure where Claude reads, writes and connects everything in Obsidian automatically so it never resets and compounds with every conversation. This morning he needed a client strategy from 3 months ago. Claude pulled it up instantly and drafted a full email reply in under 20 minutes using context it had been building for months across 6,000+ sessions. Every session adds to the last one and the system now saves him 2–3 hours every single day - 30–90 minutes from automated morning briefing alone, before he even opens his laptop. repo: The repo is free. The advantage it creates is not.

Noisy

23,679 Aufrufe • vor 1 Monat

A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this
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A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this

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Personal AGI is 3-6 months away. I'm already living in it. Here's my Obsidian setup: - Obsidian vault built since November 2025 - Markdowns about every person, project, and task - Limitless mic pulling daily transcripts straight in - Agents that read all of it before every task Obsidian is: - A second brain for you - A first brain for your agents My agents have full context before every task. That's the whole game.
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Personal AGI is 3-6 months away. I'm already living in it. Here's my Obsidian setup: - Obsidian vault built since November 2025 - Markdowns about every person, project, and task - Limitless mic pulling daily transcripts straight in - Agents that read all of it before every task Obsidian is: - A second brain for you - A first brain for your agents My agents have full context before every task. That's the whole game.

The Startup Ideas Podcast (SIP) 🧃

30,065 Aufrufe • vor 1 Monat

Chinese professor just revealed his development team - and it was 170 AI agents making every single company decision not humans, not managers, not consultants charging $500 an hour 170 artificial developers working in parallel, never sleeping, never asking for a raise, never going on vacation Kimi K2.6 runs all of them with one prompt and each one gets its own task what used to take an entire department two weeks now takes two hours and costs less than a cup of coffee and while most companies are still hiring people for these roles the ones who understood what's happening already quietly rebuilt everything this is what actually sits behind the growth of billion dollar companies right now full breakdown of how it works in the article below
0:21

Chinese professor just revealed his development team - and it was 170 AI agents making every single company decision not humans, not managers, not consultants charging $500 an hour 170 artificial developers working in parallel, never sleeping, never asking for a raise, never going on vacation Kimi K2.6 runs all of them with one prompt and each one gets its own task what used to take an entire department two weeks now takes two hours and costs less than a cup of coffee and while most companies are still hiring people for these roles the ones who understood what's happening already quietly rebuilt everything this is what actually sits behind the growth of billion dollar companies right now full breakdown of how it works in the article below

Sprytix

106,640 Aufrufe • vor 17 Tagen

Jake Heller, CEO of Casetext, sold his AI company for $650M and recorded the whole playbook. Most founders who exit for $650M disappear quietly and never say a word. He went on stage and told everyone exactly how. No NDA on the strategy, no locked course, no $10,000 mastermind, just a 39 minute talk and a link. He covers what actually worked, what almost killed the company, and how they pulled off one of the cleanest AI exits ever. 39 minutes, $0, no excuses. The article below shows how Kimi K2.6 replaced an entire dev team and how one guy built an $80,000/month agency solo with it.
39:24

Jake Heller, CEO of Casetext, sold his AI company for $650M and recorded the whole playbook. Most founders who exit for $650M disappear quietly and never say a word. He went on stage and told everyone exactly how. No NDA on the strategy, no locked course, no $10,000 mastermind, just a 39 minute talk and a link. He covers what actually worked, what almost killed the company, and how they pulled off one of the cleanest AI exits ever. 39 minutes, $0, no excuses. The article below shows how Kimi K2.6 replaced an entire dev team and how one guy built an $80,000/month agency solo with it.

Defileo🔮

126,085 Aufrufe • vor 1 Monat

Imagine if coding agents never forgot decisions, never duplicated work, and could coordinate across the same codebase in real time. We’re advancing how agents collaborate on codebases with OriginTrail DKG V9 - turning a GitHub repo and agent activity into a shared knowledge graph for persistent memory and coordination. The result: faster agentic development, less repeated work, lower token usage, and agents that can actually build on each other’s progress. Here’s how it works 👇
1:20

Imagine if coding agents never forgot decisions, never duplicated work, and could coordinate across the same codebase in real time. We’re advancing how agents collaborate on codebases with OriginTrail DKG V9 - turning a GitHub repo and agent activity into a shared knowledge graph for persistent memory and coordination. The result: faster agentic development, less repeated work, lower token usage, and agents that can actually build on each other’s progress. Here’s how it works 👇

Jurij Skornik

11,711 Aufrufe • vor 2 Monaten

This Chinese developer runs 9 agents on Claude Code under a GPT-5.5 orchestrator and they close 500 client tasks a month without a single assistant. His client work is closed without him, on a single laptop and only three subscriptions. The entire system lives on one MacBook Pro M4 with 128 GB of memory and subscriptions to Claude Code and GPT-5.5 cost him approximately $300 a month. There is no CRM, no team, no office only a terminal window with 9 parallel streams. The orchestrator works with a simple system prompt: «You are the orchestrator of a client inbox. Classify every incoming email into 4 categories: code, content, analysis, communication. Delegate to the corresponding worker agent. When the result is ready, check it for completeness, send it to the client on my behalf, and mark the task as closed. Do not ask clarifying questions.» And the orchestrator checks the inbox every 30 seconds, classifies fresh emails, and distributes them to 9 worker agents on Claude Code, each of whom is responsible for their own class of tasks. Here is an example of how one of them closes a request to refactor a client's auth module: Task: refactor user-auth module Broke the monolith into 3 files by responsibilities Added unit tests, coverage increased to 87% Renamed 4 functions to camelCase according to the style guide PR is ready for review, link below» And so about 50 cycles a day. By noon 25 tasks are closed, by dinner 50, and by the end of the month 500. On average, it takes about 7 minutes from the appearance of an email in the inbox to sending the result to the client. This is more than what a live team of 6 developers, copywriters and analysts working 8 hours a day closes. This is no longer an agency. This is a workstation where an orchestrator replaces a manager, and 9 worker agents replace the staff. The pipeline goes from inbox to closing 500 times a month without human participation at any step.
1:32

This Chinese developer runs 9 agents on Claude Code under a GPT-5.5 orchestrator and they close 500 client tasks a month without a single assistant. His client work is closed without him, on a single laptop and only three subscriptions. The entire system lives on one MacBook Pro M4 with 128 GB of memory and subscriptions to Claude Code and GPT-5.5 cost him approximately $300 a month. There is no CRM, no team, no office only a terminal window with 9 parallel streams. The orchestrator works with a simple system prompt: «You are the orchestrator of a client inbox. Classify every incoming email into 4 categories: code, content, analysis, communication. Delegate to the corresponding worker agent. When the result is ready, check it for completeness, send it to the client on my behalf, and mark the task as closed. Do not ask clarifying questions.» And the orchestrator checks the inbox every 30 seconds, classifies fresh emails, and distributes them to 9 worker agents on Claude Code, each of whom is responsible for their own class of tasks. Here is an example of how one of them closes a request to refactor a client's auth module: Task: refactor user-auth module Broke the monolith into 3 files by responsibilities Added unit tests, coverage increased to 87% Renamed 4 functions to camelCase according to the style guide PR is ready for review, link below» And so about 50 cycles a day. By noon 25 tasks are closed, by dinner 50, and by the end of the month 500. On average, it takes about 7 minutes from the appearance of an email in the inbox to sending the result to the client. This is more than what a live team of 6 developers, copywriters and analysts working 8 hours a day closes. This is no longer an agency. This is a workstation where an orchestrator replaces a manager, and 9 worker agents replace the staff. The pipeline goes from inbox to closing 500 times a month without human participation at any step.

Blaze

29,917 Aufrufe • vor 1 Monat