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Atlassian's CEO after firing the engineer who built their $1.79B infrastructure and the guy released a 38-minute breakdown of everything he built, free for anyone to copy

Atlassian's CEO after firing the engineer who built their $1.79B infrastructure and the guy released a 38-minute breakdown of everything he built, free for anyone to copy

17,549,528 Aufrufe

THIS DOCUMENT FROM ANTHROPIC WILL LITERALLY GET YOU PROMOTED > the fastest way to reach a senior position is to automate your current job this technical paper shows how to encode your daily workflows into Claude build custom "Skills" to force the AI to do the heavy lifting: > package your routines into automated folders > the agent executes your tasks flawlessly in the background > it connects directly to your local tools via MCP servers hand off the junior work to the agent and easily claim your promotion grab the exact blueprint right here 👇

THIS DOCUMENT FROM ANTHROPIC WILL LITERALLY GET YOU PROMOTED > the fastest way to reach a senior position is to automate your current job this technical paper shows how to encode your daily workflows into Claude build custom "Skills" to force the AI to do the heavy lifting: > package your routines into automated folders > the agent executes your tasks flawlessly in the background > it connects directly to your local tools via MCP servers hand off the junior work to the agent and easily claim your promotion grab the exact blueprint right here 👇

372,196 Aufrufe

this is straight f*cking gold the full harness guide for Kimi K3, the #1 open source frontend model the premise: the model underneath keeps changing. the harness is the part that stays yours what one night of it looks like: 02:00 - the trigger fires, every node that needs work gets picked > 212 agents fan out, one per node > a bad return gets rejected, retried once with the reason attached > one agent tries to write outside its folder. blocked. nobody woken up > +41 nodes and +96 edges land in the graph > a drafted email hits pre_send and waits for you 02:41 - the loop stops on its own, inside a 45 minute budget 07:30 - you read one file and make two decisions the whole machine is one folder, one config file, five short scripts two rules hold it together: > the model sits behind one line, so a better model is a config change > the verifier lives outside the agent, so nothing grades its own work now the money part companies burn whole quarters building internal agent platforms a harness setup for a small team goes for four figures, one time then a monthly retainer to run the swap test on every new model release models come and go. the person who owns the harness keeps getting paid

this is straight f*cking gold the full harness guide for Kimi K3, the #1 open source frontend model the premise: the model underneath keeps changing. the harness is the part that stays yours what one night of it looks like: 02:00 - the trigger fires, every node that needs work gets picked > 212 agents fan out, one per node > a bad return gets rejected, retried once with the reason attached > one agent tries to write outside its folder. blocked. nobody woken up > +41 nodes and +96 edges land in the graph > a drafted email hits pre_send and waits for you 02:41 - the loop stops on its own, inside a 45 minute budget 07:30 - you read one file and make two decisions the whole machine is one folder, one config file, five short scripts two rules hold it together: > the model sits behind one line, so a better model is a config change > the verifier lives outside the agent, so nothing grades its own work now the money part companies burn whole quarters building internal agent platforms a harness setup for a small team goes for four figures, one time then a monthly retainer to run the swap test on every new model release models come and go. the person who owns the harness keeps getting paid

13,054 Aufrufe

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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

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

21,787,064 Aufrufe • vor 5 Monaten

this one page turns Obsidian + Opus 5.5 + Jev into a second brain that thinks with you around the clock built on Karpathy's ideas Jev reads every note before Opus does Opus writes only what matters your vault keeps working while you don't cuts 80% off your weekly chat time frees you up for the work your manager actually pays for the people who set this up early are the ones the next raise finds first

this one page turns Obsidian + Opus 5.5 + Jev into a second brain that thinks with you around the clock built on Karpathy's ideas Jev reads every note before Opus does Opus writes only what matters your vault keeps working while you don't cuts 80% off your weekly chat time frees you up for the work your manager actually pays for the people who set this up early are the ones the next raise finds first

47,119 Aufrufe • vor 4 Tagen

Claude Code tip, and it's absolute free f*cking gold: run Opus 5.5, Sonnet 5.5 and Fable 5.1 as one team and stop burning Opus tokens on routine work the setup in one line: plan on high, delegate on medium, keep Fable on call • who does what > Opus 5.5 on high - plans and ships the code > Sonnet 5.5 on medium - explorer reads code, worker edits and runs tests, researcher pulls docs > Fable 5.1 via /advisor fable - reads the whole session and speaks up only when it matters • when Fable 5.1 steps in -> before a plan: is this the right approach? -> when an error repeats: am I digging in the wrong place? -> before "done": what did I miss? Jev engineering takes it one layer lower: which file, which tool, retry or stop all go to Jev in under half a second, so the big models only see the real forks paste this into Claude Code ↓ "Rebuild my Claude Code setup: 1. Find subagents in ~/.claude/agents and .claude/agents that fit explorer, worker and researcher. Draft only the missing ones. Set each to model: sonnet, effort: medium. List any that pin a different model and leave them 2. In ~/.claude/settings.json set effortLevel to high and advisorModel to fable. 3. Report anything that disables the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, flag-fetching blockers) and CLAUDE_CODE_EFFORT_LEVEL. Change nothing. 4. Add to ~/.claude/CLAUDE.md: consult the advisor before a large plan, when an error repeats, and before calling a long task done. Show every change as a diff. No edits until I say go." ↳

Claude Code tip, and it's absolute free f*cking gold: run Opus 5.5, Sonnet 5.5 and Fable 5.1 as one team and stop burning Opus tokens on routine work the setup in one line: plan on high, delegate on medium, keep Fable on call • who does what > Opus 5.5 on high - plans and ships the code > Sonnet 5.5 on medium - explorer reads code, worker edits and runs tests, researcher pulls docs > Fable 5.1 via /advisor fable - reads the whole session and speaks up only when it matters • when Fable 5.1 steps in -> before a plan: is this the right approach? -> when an error repeats: am I digging in the wrong place? -> before "done": what did I miss? Jev engineering takes it one layer lower: which file, which tool, retry or stop all go to Jev in under half a second, so the big models only see the real forks paste this into Claude Code ↓ "Rebuild my Claude Code setup: 1. Find subagents in ~/.claude/agents and .claude/agents that fit explorer, worker and researcher. Draft only the missing ones. Set each to model: sonnet, effort: medium. List any that pin a different model and leave them 2. In ~/.claude/settings.json set effortLevel to high and advisorModel to fable. 3. Report anything that disables the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, flag-fetching blockers) and CLAUDE_CODE_EFFORT_LEVEL. Change nothing. 4. Add to ~/.claude/CLAUDE.md: consult the advisor before a large plan, when an error repeats, and before calling a long task done. Show every change as a diff. No edits until I say go." ↳

144,421 Aufrufe • vor 17 Tagen

I'm sharing with you one of the best papers I've read on Harness Engineering it takes apart Claude Code (Opus 5.5), Codex, Gemini CLI and more, and boils all of them down to one line: agent = model + harness what you walk away with: > what a harness actually is > how today's coding agents are built under the hood > the patterns every one of them repeats > where the whole category is heading > their checklist for building your own the model gets the headlines. the harness decides whether the agent works loop and graph engineering on top of it - in my article below

I'm sharing with you one of the best papers I've read on Harness Engineering it takes apart Claude Code (Opus 5.5), Codex, Gemini CLI and more, and boils all of them down to one line: agent = model + harness what you walk away with: > what a harness actually is > how today's coding agents are built under the hood > the patterns every one of them repeats > where the whole category is heading > their checklist for building your own the model gets the headlines. the harness decides whether the agent works loop and graph engineering on top of it - in my article below

83,143 Aufrufe • vor 12 Tagen

this is pure f*cking gold for anyone running coding agents Jev founder Diogo Amogo wrote a PDF on building a Jev harness the promise: > 200x faster > 400x cheaper the model hasn't been the slow part for a while the speed and the cost sit in the harness wrapped around it • how to use it > drop this PDF and the article below into Claude Code or Codex > let it rebuild its own setup one evening of setup and your agent starts next week on a harness most teams still don't have 👇

this is pure f*cking gold for anyone running coding agents Jev founder Diogo Amogo wrote a PDF on building a Jev harness the promise: > 200x faster > 400x cheaper the model hasn't been the slow part for a while the speed and the cost sit in the harness wrapped around it • how to use it > drop this PDF and the article below into Claude Code or Codex > let it rebuild its own setup one evening of setup and your agent starts next week on a harness most teams still don't have 👇

128,424 Aufrufe • vor 22 Tagen

SpaceXAI put out a 12-page PDF on the best GrokBot use cases - read it and you'll use GrokBot better than 95% of people what the bot is, which use cases work today, and how to deploy it without burning trust: step 1 -> every working use case has one shape: read, check, apply a rule, write a draft. if your task fits, the bot can take it step 2 -> five checks before handoff: repeatable, cross-system, rule-based, draft-first, cheap to get wrong. fails one? add a gate or wait step 3 -> start with sales. 36 LinkedIn drafts queued overnight, none sent without review. no team has more agent-ready work step 4 -> engineering gets bug repro, CI/CD watch and dependency audits. the bot picks up the ticket, hits staging and hands back a repro pack step 5 -> operations hands over inbox, expenses and travel. the bot logs into portals that have no API, and finance gets 8-12 hours back at month-end step 6 -> marketing owns 13 of the 56 roles: paid media, content calendars, competitor watch. all overnight, all draft-first step 7 -> the approval line: every documented use case stops before external action. nothing gets sent, booked or paid without you step 8 -> roll out over four weeks: watch, review everything, review flags, then a scheduled routine. skip a week and the risk stacks up step 9 -> the fleet: a Chief of Staff bot on top, specialists below, bots messaging each other. you stop being the middleman step 10 -> rank tasks by the cost of a mistake. the bot nails 49 in a row, then does something strange on the 50th with full confidence. keep a human at every exit the result: 56 roles, one playbook. the bot takes the 80% that repeats, you keep the 20% that matters then read how to build a 24/7 GrokBot agent team in the article below

SpaceXAI put out a 12-page PDF on the best GrokBot use cases - read it and you'll use GrokBot better than 95% of people what the bot is, which use cases work today, and how to deploy it without burning trust: step 1 -> every working use case has one shape: read, check, apply a rule, write a draft. if your task fits, the bot can take it step 2 -> five checks before handoff: repeatable, cross-system, rule-based, draft-first, cheap to get wrong. fails one? add a gate or wait step 3 -> start with sales. 36 LinkedIn drafts queued overnight, none sent without review. no team has more agent-ready work step 4 -> engineering gets bug repro, CI/CD watch and dependency audits. the bot picks up the ticket, hits staging and hands back a repro pack step 5 -> operations hands over inbox, expenses and travel. the bot logs into portals that have no API, and finance gets 8-12 hours back at month-end step 6 -> marketing owns 13 of the 56 roles: paid media, content calendars, competitor watch. all overnight, all draft-first step 7 -> the approval line: every documented use case stops before external action. nothing gets sent, booked or paid without you step 8 -> roll out over four weeks: watch, review everything, review flags, then a scheduled routine. skip a week and the risk stacks up step 9 -> the fleet: a Chief of Staff bot on top, specialists below, bots messaging each other. you stop being the middleman step 10 -> rank tasks by the cost of a mistake. the bot nails 49 in a row, then does something strange on the 50th with full confidence. keep a human at every exit the result: 56 roles, one playbook. the bot takes the 80% that repeats, you keep the 20% that matters then read how to build a 24/7 GrokBot agent team in the article below

36,742 Aufrufe • vor 6 Tagen

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 👇

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 👇

568,465 Aufrufe • vor 4 Monaten

this is free f*cking gold for anyone building a second brain his second brain article pulled 8 million views, so he packed the whole system into one repo the repo, the guide, the tools, the learning path, all free • the guide > 10 sections, 65 pages, from the core idea to troubleshooting > 5 tracks on top, 44 pages, 15 of them build guides with working code • the machine (.claude/) > 18 agent skills, one per workflow > 72 slash commands - /ingest-pdf, /ingest-youtube, /ingest-voice, /backfill > 6 subagents - curator, linker, researcher, reviewer, ingestor, graph-analyst > 4 are read-only, so nothing rewrites your vault behind your back • the scripts (plain Python, zero dependencies) > graph export, link checker, vault stats, chat converter, site builder • the starter vault > its own CLAUDE.md with page contracts and linking rules > raw/ stays untouched once it lands, wiki/ is what the agent keeps up > log.md - one line per run, so every change is traceable • 87 vetted resources > 28 tools, 26 Obsidian plugins, 15 repos, 12 skills, plus papers and articles five tracks to choose from: > knowledge graphs > Jev engineering > agent harnesses > loop engineering > eval engineering new to this? start with the second brain guide. already deep in it? jump straight to the tracks the Jev engineering and loop engineering tracks alone are worth the clone a consultant bills four figures to build you a research system like this. here it's a public repo under MIT ↳

this is free f*cking gold for anyone building a second brain his second brain article pulled 8 million views, so he packed the whole system into one repo the repo, the guide, the tools, the learning path, all free • the guide > 10 sections, 65 pages, from the core idea to troubleshooting > 5 tracks on top, 44 pages, 15 of them build guides with working code • the machine (.claude/) > 18 agent skills, one per workflow > 72 slash commands - /ingest-pdf, /ingest-youtube, /ingest-voice, /backfill > 6 subagents - curator, linker, researcher, reviewer, ingestor, graph-analyst > 4 are read-only, so nothing rewrites your vault behind your back • the scripts (plain Python, zero dependencies) > graph export, link checker, vault stats, chat converter, site builder • the starter vault > its own CLAUDE.md with page contracts and linking rules > raw/ stays untouched once it lands, wiki/ is what the agent keeps up > log.md - one line per run, so every change is traceable • 87 vetted resources > 28 tools, 26 Obsidian plugins, 15 repos, 12 skills, plus papers and articles five tracks to choose from: > knowledge graphs > Jev engineering > agent harnesses > loop engineering > eval engineering new to this? start with the second brain guide. already deep in it? jump straight to the tracks the Jev engineering and loop engineering tracks alone are worth the clone a consultant bills four figures to build you a research system like this. here it's a public repo under MIT ↳

56,795 Aufrufe • vor 13 Tagen

I can't believe this is f*cking free how to build your first AI agent (full guide, with a Jev decision layer) a year ago I burned two weeks on my first agent. this guide gets you there in an afternoon in the right hands it makes one builder ship like a small team:

I can't believe this is f*cking free how to build your first AI agent (full guide, with a Jev decision layer) a year ago I burned two weeks on my first agent. this guide gets you there in an afternoon in the right hands it makes one builder ship like a small team:

61,929 Aufrufe • vor 16 Tagen

Jev + Claude Opus 5.5 is a f*cking goldmine... i can't understand why everyone isn't wiring this up yet the forks alone drop from about $110 a day to $4 once Jev takes them over. right now it's the best way i know to run Opus where Jev steps in: -> ranks which project notes matter before the context loads -> passes the easy steps to a faster worker -> chooses a recovery path when a tool fails, so nothing retries blind -> runs the targeted checks before the full test suite Opus does the hard reasoning. Jev chooses between options the harness already built and checked every choice comes back with a probability, so the harness can set a confidence floor and push anything below it back up to Opus Jev engineering fits in one line: the expensive model reasons, the cheap one decides $106 a day saved on the same work ends up in your performance review start with the paper, then the full Jev guide below

Jev + Claude Opus 5.5 is a f*cking goldmine... i can't understand why everyone isn't wiring this up yet the forks alone drop from about $110 a day to $4 once Jev takes them over. right now it's the best way i know to run Opus where Jev steps in: -> ranks which project notes matter before the context loads -> passes the easy steps to a faster worker -> chooses a recovery path when a tool fails, so nothing retries blind -> runs the targeted checks before the full test suite Opus does the hard reasoning. Jev chooses between options the harness already built and checked every choice comes back with a probability, so the harness can set a confidence floor and push anything below it back up to Opus Jev engineering fits in one line: the expensive model reasons, the cheap one decides $106 a day saved on the same work ends up in your performance review start with the paper, then the full Jev guide below

19,994 Aufrufe • vor 10 Tagen

Chinese researchers just published a paper with a brutal title: "The End of Software Engineering." their argument: writing code is finished as a skill a human brain holds only so much state and so many dependencies before it stalls an agent has no such ceiling, and its capacity climbs with compute so the person stops being the one typing the code you turn into the intent architect - you direct the agents and audit what comes back code turns disposable, judgment turns into the job that's why i wrote the guide below on building your own agent system from scratch the paper it's based on is down there too

Chinese researchers just published a paper with a brutal title: "The End of Software Engineering." their argument: writing code is finished as a skill a human brain holds only so much state and so many dependencies before it stalls an agent has no such ceiling, and its capacity climbs with compute so the person stops being the one typing the code you turn into the intent architect - you direct the agents and audit what comes back code turns disposable, judgment turns into the job that's why i wrote the guide below on building your own agent system from scratch the paper it's based on is down there too

57,376 Aufrufe • vor 1 Monat

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a fast browser agent ↳ 2. Fast-JEV-Compaction - context compression ↳ 3. JSON-Render - generative UI ↳ 4. Typesafe-MCP - use Jev with any client ↳ 5. JEV-MCP - a judgment toolkit ↳ 6. Semdecide - a classifier that lives in your CLI ↳ 7. JEV-Codex-Router - routes each task to the right model ↳ 8. Winnow - garbage collection for your context ↳ 9. JEV-Review - code review triage ↳ 10. Blink - a repo navigator ↳ 11. Agent-Desktop - desktop automation ↳ 12. Typesafe-Mario - an agent that plays Super Mario ↳ 13. JEV-Drone - drone control ↳ 14. OneVOneJev - a browser FPS ↳ 15. JEV-Trader - HFT market making ↳ 16. Prism - liquidity signal detection ↳ 17. Neo4Jev - knowledge graph traversal ↳ 18. JEV-Curate - training data screening ↳ 19. Canny - checks whether a task was actually completed ↳ 20. KillMyIdea - scores startup ideas before you build them ↳ pick by what you do: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > just for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone grab the one closest to your job and ship something on top of it this week

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a fast browser agent ↳ 2. Fast-JEV-Compaction - context compression ↳ 3. JSON-Render - generative UI ↳ 4. Typesafe-MCP - use Jev with any client ↳ 5. JEV-MCP - a judgment toolkit ↳ 6. Semdecide - a classifier that lives in your CLI ↳ 7. JEV-Codex-Router - routes each task to the right model ↳ 8. Winnow - garbage collection for your context ↳ 9. JEV-Review - code review triage ↳ 10. Blink - a repo navigator ↳ 11. Agent-Desktop - desktop automation ↳ 12. Typesafe-Mario - an agent that plays Super Mario ↳ 13. JEV-Drone - drone control ↳ 14. OneVOneJev - a browser FPS ↳ 15. JEV-Trader - HFT market making ↳ 16. Prism - liquidity signal detection ↳ 17. Neo4Jev - knowledge graph traversal ↳ 18. JEV-Curate - training data screening ↳ 19. Canny - checks whether a task was actually completed ↳ 20. KillMyIdea - scores startup ideas before you build them ↳ pick by what you do: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > just for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone grab the one closest to your job and ship something on top of it this week

29,619 Aufrufe • vor 23 Tagen

this is free f*cking gold Andrej Karpathy joined Anthropic to run a team turning Claude loose on Anthropic's own pretraining research a model helping build the model that replaces it. that part is on the record the quote doing the rounds - "two Anthropic seniors made his loop 1000x better with graph engineering" - has no source anywhere, so i'm not passing it off as fact what's public and checkable: Anthropic's own Claude cookbook on building knowledge graphs > extract - pull entities and claims out of raw text > resolve - work out which mentions are the same thing > assemble - wire them together with typed edges > query - ask what no single document could answer four steps, free, sitting in the repo while the timeline repeats a rumor learn them this weekend and you can build what that rumor was describing. that's the skill getting handed the AI architecture work this year start with the cookbook. then judge whether the article below was worth the click

this is free f*cking gold Andrej Karpathy joined Anthropic to run a team turning Claude loose on Anthropic's own pretraining research a model helping build the model that replaces it. that part is on the record the quote doing the rounds - "two Anthropic seniors made his loop 1000x better with graph engineering" - has no source anywhere, so i'm not passing it off as fact what's public and checkable: Anthropic's own Claude cookbook on building knowledge graphs > extract - pull entities and claims out of raw text > resolve - work out which mentions are the same thing > assemble - wire them together with typed edges > query - ask what no single document could answer four steps, free, sitting in the repo while the timeline repeats a rumor learn them this weekend and you can build what that rumor was describing. that's the skill getting handed the AI architecture work this year start with the cookbook. then judge whether the article below was worth the click

32,138 Aufrufe • vor 1 Monat

CLAUDE + OBSIDIAN + LOOP ENGINEERING = AN AGENT THAT LIVES IN YOUR NOTES Karpathy's second brain runs on something close to this. two years of growth. he barely typed any of it four steps, on repeat: 1. read - Claude Opus 5 opens the vault, not a chat window 2. write - notes and links change inside a branch 3. check - a critic reads the diff, checks every link 4. keep - the good change sticks. nothing gets touched cost: 2-4x a single prompt. worth it past a 5% gain. zero notes overwritten. the vault only grows the whole system runs on six plain files: CLAUDE.md, skills, subagents, hooks, MCP, plugins. no black box three ways in: a desktop connector for three clicks, Claude Code for full control, or the Obsidian plugin if you never want to leave the app append, don't overwrite. measure the win before adding a step. never let it rewrite the whole vault in one turn a loop that never deletes a note is compound interest for your own thinking

CLAUDE + OBSIDIAN + LOOP ENGINEERING = AN AGENT THAT LIVES IN YOUR NOTES Karpathy's second brain runs on something close to this. two years of growth. he barely typed any of it four steps, on repeat: 1. read - Claude Opus 5 opens the vault, not a chat window 2. write - notes and links change inside a branch 3. check - a critic reads the diff, checks every link 4. keep - the good change sticks. nothing gets touched cost: 2-4x a single prompt. worth it past a 5% gain. zero notes overwritten. the vault only grows the whole system runs on six plain files: CLAUDE.md, skills, subagents, hooks, MCP, plugins. no black box three ways in: a desktop connector for three clicks, Claude Code for full control, or the Obsidian plugin if you never want to leave the app append, don't overwrite. measure the win before adding a step. never let it rewrite the whole vault in one turn a loop that never deletes a note is compound interest for your own thinking

59,214 Aufrufe • vor 2 Monaten

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a browser agent built for speed ↳ 2. Fast-JEV-Compaction - squeezes your context down ↳ 3. JSON-Render - UI generated on the fly ↳ 4. Typesafe-MCP - plugs Jev into any client ↳ 5. JEV-MCP - a toolkit for judgment calls ↳ 6. Semdecide - a classifier right in your terminal ↳ 7. JEV-Codex-Router - sends every task to the model that fits it ↳ 8. Winnow - clears the junk out of your context ↳ 9. JEV-Review - sorts code reviews by what needs eyes first ↳ 10. Blink - finds your way around any repo ↳ 11. Agent-Desktop - runs your desktop for you ↳ 12. Typesafe-Mario - an agent playing Super Mario ↳ 13. JEV-Drone - flies a drone ↳ 14. OneVOneJev - a shooter in your browser ↳ 15. JEV-Trader - high-frequency market making ↳ 16. Prism - spots liquidity signals ↳ 17. Neo4Jev - walks a knowledge graph ↳ 18. JEV-Curate - screens training data ↳ 19. Canny - confirms a task is really finished ↳ 20. KillMyIdea - scores a startup idea before you sink time into it ↳ start where your work is: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone pick one, build on it this week, and you'll be the person on your team who actually knows Jev engineering when it gets asked for

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a browser agent built for speed ↳ 2. Fast-JEV-Compaction - squeezes your context down ↳ 3. JSON-Render - UI generated on the fly ↳ 4. Typesafe-MCP - plugs Jev into any client ↳ 5. JEV-MCP - a toolkit for judgment calls ↳ 6. Semdecide - a classifier right in your terminal ↳ 7. JEV-Codex-Router - sends every task to the model that fits it ↳ 8. Winnow - clears the junk out of your context ↳ 9. JEV-Review - sorts code reviews by what needs eyes first ↳ 10. Blink - finds your way around any repo ↳ 11. Agent-Desktop - runs your desktop for you ↳ 12. Typesafe-Mario - an agent playing Super Mario ↳ 13. JEV-Drone - flies a drone ↳ 14. OneVOneJev - a shooter in your browser ↳ 15. JEV-Trader - high-frequency market making ↳ 16. Prism - spots liquidity signals ↳ 17. Neo4Jev - walks a knowledge graph ↳ 18. JEV-Curate - screens training data ↳ 19. Canny - confirms a task is really finished ↳ 20. KillMyIdea - scores a startup idea before you sink time into it ↳ start where your work is: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone pick one, build on it this week, and you'll be the person on your team who actually knows Jev engineering when it gets asked for

12,199 Aufrufe • vor 18 Tagen

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