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this is pure f*cking treasure 20 GitHub projects to help it understand a real codebase, use real tools, catch bad changes, and show you what happened UNDERSTAND THE WORK 01 Beads ▸ 02 Repomix ▸ 03 Serena ▸ 04 ast-grep ▸ 05 claude-mem ▸ CONNECT TO REAL SYSTEMS 06... ToolHive ▸ 07 MCP Inspector ▸ 08 Steel Browser ▸ 09 Midscene ▸ 10 Bruno ▸ CHECK THE CHANGE 11 Trivy ▸ 12 Gitleaks ▸ 13 OpenSSF Scorecard practices ▸ 14 Checkov ▸ 15 SWE-bench ▸ SHIP AND LEARN 16 Dagger ▸ 17 GitButler ▸ 18 Git Town ▸ 19 OpenLLMetry ▸ 20 LangWatch ▸ the loop: capture the task → map the code → use the right tools → test the actual interface → scan the change → run the pipeline → inspect the trace → improve the next attempt save this, then build a second brain for your business⭣show more

beamnxw ./

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15,162 Aufrufe • vor 14 Tagen •via X (Twitter)

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19 Kommentare

Profilbild von Hussain Hashim | Building SundayBack

Hussain Hashim | Building SundayBackvor 14 Tagen

@beamnxw love this list! i'd add: have a tight version control strategy. it's key to avoid a mess when dealing with multiple projects and changes.

Profilbild von Manish

Manishvor 14 Tagen

the “understand the work” section is the real treasure. giving an agent tools to actually inspect, change, and verify a codebase is way more useful than just giving it more context.

Profilbild von Asteri

Asterivor 14 Tagen

Saved all the repos

Profilbild von hivipilled

hivipilledvor 14 Tagen

Gitleaks and Trivy in the loop replace the security review nobody scheduled

Profilbild von iDesi

iDesivor 14 Tagen

I just use one and nost of above is available in one plugin

Profilbild von orvexus

orvexusvor 14 Tagen

Repomix output gets huge on a real monorepo, scope it per folder first

Profilbild von 0xbobaa

0xbobaavor 14 Tagen

how do you find all this?

Profilbild von barnyx

barnyxvor 14 Tagen

the loop at the end is the actual gold. bookmarking that workflow

Profilbild von Diam

Diamvor 14 Tagen

Nice collection. There’s a lot here to try in a real project.

Profilbild von Antony Claude

Antony Claudevor 14 Tagen

this list is actually kinda insane for builders

Profilbild von Gipp 🦅

Gipp 🦅vor 14 Tagen

does toolhive work with private repos too?

Profilbild von EugBass

EugBassvor 14 Tagen

this set of repos makes me crazy

Profilbild von Insomnia

Insomniavor 14 Tagen

bro making it too

Profilbild von marfin

marfinvor 14 Tagen

these are the most useful repos I've seen

Profilbild von magsimich

magsimichvor 14 Tagen

Beads and Repomix are solid picks

Profilbild von OK返50暮川

OK返50暮川vor 14 Tagen

这波开源干货含金量高到离谱

Profilbild von wast3

wast3vor 14 Tagen

this will amaze every reader

Profilbild von kozh ./

kozh ./vor 14 Tagen

I’ll be checking it tomorrow

Profilbild von NO1ennn

NO1ennnvor 14 Tagen

So useful

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this is pure f*cking treasure these 20 plugins have 6.73M combined downloads and form a real Claude Code stack: build the product → hold the context → coordinate the work → keep the system under control BUILD 01 frontend-design-pro ▸ 02 animated-sketch-diagram ▸ 03 archcore ▸ 04 shipwright ▸ 05 slopmop ▸ MEMORY 06 origin ▸ 07 dsh-deepread ▸ 08 obsidian-skills ▸ 09 claude-md-kit ▸ 10 claude-ops ▸ ORCHESTRATE 11 crosstalk ▸ 12 claude-wayfinder ▸ 13 backlogd ▸ 14 magic-cc-codex-worker ▸ 15 vibe-prospecting ▸ CONTROL 16 project-boundary ▸ 17 tlsradar ▸ 18 claude-hud ▸ 19 claude-pager ▸ 20 claude-prospector ▸ the loop: idea → interface → architecture → shared memory → parallel work → checks → ship ave this to build your own business with the help of an AI employee ⭣

this is pure f*cking treasure these 20 plugins have 6.73M combined downloads and form a real Claude Code stack: build the product → hold the context → coordinate the work → keep the system under control BUILD 01 frontend-design-pro ▸ 02 animated-sketch-diagram ▸ 03 archcore ▸ 04 shipwright ▸ 05 slopmop ▸ MEMORY 06 origin ▸ 07 dsh-deepread ▸ 08 obsidian-skills ▸ 09 claude-md-kit ▸ 10 claude-ops ▸ ORCHESTRATE 11 crosstalk ▸ 12 claude-wayfinder ▸ 13 backlogd ▸ 14 magic-cc-codex-worker ▸ 15 vibe-prospecting ▸ CONTROL 16 project-boundary ▸ 17 tlsradar ▸ 18 claude-hud ▸ 19 claude-pager ▸ 20 claude-prospector ▸ the loop: idea → interface → architecture → shared memory → parallel work → checks → ship ave this to build your own business with the help of an AI employee ⭣

beamnxw ./

25,005 Aufrufe • vor 23 Tagen

this is pure f*cking treasure 15 GitHub projects with 1.21M combined stars that can form a real agent stack specs. memory. web data. documents. context. sandboxes. monitoring. video 01 hermes-agent ▸ 02 OpenSpec ▸ 03 caveman ▸ 04 Scrapling ▸ 05 Docling ▸ 06 PageIndex ▸ 07 mem0 ▸ 08 headroom ▸ 09 Daytona ▸ 10 TrendRadar ▸ 11 Fabric ▸ 12 spec-kit ▸ 13 hyperframes ▸ 14 OpenMontage ▸ 15 AI Engineering Hub ▸ the loop: define the job → collect the evidence → parse the docs → save the memory → compress the context → run the code safely → watch what changes → ship the output the entire stack is open source save this to build your own business with the help of an AI employee ⭣

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beamnxw ./

156,581 Aufrufe • vor 26 Tagen

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beamnxw ./

140,651 Aufrufe • vor 18 Tagen

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beamnxw ./

26,555 Aufrufe • vor 25 Tagen

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beamnxw ./

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beamnxw ./

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beamnxw ./

34,441 Aufrufe • vor 21 Tagen

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

rody

18,089 Aufrufe • vor 13 Tagen

this is pure f*cking treasure for motion design 20 GitHub repos to build a motion design studio with Opus 5.5 pick the tools for each layer: agent skills, animation, 3D, assets, sound and export 01 Remotion → turn React code into editable videos 02 Remotion Skills → give Claude Code official video workflows 03 Motion Canvas → animate diagrams and explainers in TypeScript 04 Motion AI Kit → give Claude Code Motion docs and guidance 05 Motion → animate live UI layouts and gestures 06 GSAP → sequence SVG and text with precise timelines 07 Anime.js → animate SVG paths, text and interface elements 08 GSAP Skills → teach Claude Code timelines and React cleanup 09 Rive Web → connect vector animations to app states 10 dotLottie Web → play and control Lottie animation assets 11 Three.js → build 3D shots with cameras and lighting 12 React Three Fiber → build 3D scenes as React components 13 Drei → reuse 3D cameras, text and controls 14 React Three Rapier → add collisions, joints and rigid bodies 15 React Postprocessing → add bloom, depth of field and finishing effects 16 SVGO → clean SVG files before animating 17 Satori → generate SVG title cards from JSX 18 Howler.js → control sound effects and fades in web demos 19 Mediabunny → encode and convert video in the browser 20 FFmpeg → encode, resize and inspect final exports the loop: brief → type → animate → build the scene → add sound → render → review → ship save this + read the article below to build your own motion design studio ⭣

this is pure f*cking treasure for motion design 20 GitHub repos to build a motion design studio with Opus 5.5 pick the tools for each layer: agent skills, animation, 3D, assets, sound and export 01 Remotion → turn React code into editable videos 02 Remotion Skills → give Claude Code official video workflows 03 Motion Canvas → animate diagrams and explainers in TypeScript 04 Motion AI Kit → give Claude Code Motion docs and guidance 05 Motion → animate live UI layouts and gestures 06 GSAP → sequence SVG and text with precise timelines 07 Anime.js → animate SVG paths, text and interface elements 08 GSAP Skills → teach Claude Code timelines and React cleanup 09 Rive Web → connect vector animations to app states 10 dotLottie Web → play and control Lottie animation assets 11 Three.js → build 3D shots with cameras and lighting 12 React Three Fiber → build 3D scenes as React components 13 Drei → reuse 3D cameras, text and controls 14 React Three Rapier → add collisions, joints and rigid bodies 15 React Postprocessing → add bloom, depth of field and finishing effects 16 SVGO → clean SVG files before animating 17 Satori → generate SVG title cards from JSX 18 Howler.js → control sound effects and fades in web demos 19 Mediabunny → encode and convert video in the browser 20 FFmpeg → encode, resize and inspect final exports the loop: brief → type → animate → build the scene → add sound → render → review → ship save this + read the article below to build your own motion design studio ⭣

beamnxw ./

23,265 Aufrufe • vor 3 Tagen

this is where GPT-6 Astra is getting f...cking illegal 10 open-source GitHub repos I'd use to build the system around the model 01 PydanticAI ▸ → typed agents + structured outputs 02 LangGraph ▸ → state + long-running agent workflows BUILD THE AGENTS 03 Agno ▸ → agents + teams + workflows 04 smolagents ▸ → agents that execute through code GIVE THEM MEMORY 05 Mem0 ▸ → persistent agent memory 06 Graphiti ▸ → temporal knowledge graphs GIVE THEM A RUNTIME 07 E2B ▸ → isolated sandboxes for AI-generated code 08 Daytona ▸ → infrastructure for running agent workloads TEST EVERYTHING 09 DeepEval ▸ → evals for LLM systems 10 Langfuse ▸ → traces + evals + production monitoring the flow: request → agent → memory → tools → runtime → eval → retry → deploy that's the part people underestimate the model is one folder the system around it is the product ⭣

this is where GPT-6 Astra is getting f...cking illegal 10 open-source GitHub repos I'd use to build the system around the model 01 PydanticAI ▸ → typed agents + structured outputs 02 LangGraph ▸ → state + long-running agent workflows BUILD THE AGENTS 03 Agno ▸ → agents + teams + workflows 04 smolagents ▸ → agents that execute through code GIVE THEM MEMORY 05 Mem0 ▸ → persistent agent memory 06 Graphiti ▸ → temporal knowledge graphs GIVE THEM A RUNTIME 07 E2B ▸ → isolated sandboxes for AI-generated code 08 Daytona ▸ → infrastructure for running agent workloads TEST EVERYTHING 09 DeepEval ▸ → evals for LLM systems 10 Langfuse ▸ → traces + evals + production monitoring the flow: request → agent → memory → tools → runtime → eval → retry → deploy that's the part people underestimate the model is one folder the system around it is the product ⭣

Lummox

43,873 Aufrufe • vor 12 Tagen

Updated: Vocals & Rap - #성화 #Seonghwa 00:00 Still Here 00:15 Wonderland 00:36 Halazia 00:47 Answer 01:21 Cyberpunk 01:27 Wave 01:37 Utopia 01:50 My Way 02:00 With U 02:16 Be With You 02:54 Star 1117 03:21 Turbulence (야간비행) 03:39 Days 04:26 Promise 04:38 Fever 04:54 Sunrise 05:19 Mist 05:43 Take Me Home 06:11 Better 06:34 All About You 06:43 Aurora 06:55 Blue Summer 07:23 Diamond 07:46 Time Of Love 07:58 Stay 08:07 Desire 08:21 WDIG 08:28 New World 08:35 Dreamers 08:53 Not Too Late 09:03 The Letter 09:19 One Day At A Time 09:28 Dazzling Light 09:40 Light 09:50 The Ring 10:04 Paradigm 10:18 This World 10:38 Bouncy 10:51 Not Okay 11:15 The King 11:23 Inception 11:52 Fireworks 12:03 Limitless 12:19 Precious 12:28 Rocky 12:41 Let’s Get Together 13:07 White Love 13:17 The Leaders 13:27 Crazy Form 13:43 Arriba 13:57 Silver Light 14:06 Dreamy Day 14:26 Matz 15:15 Outlaw 15:23 Twilight 15:31 Dune 15:38 Hala Hala 15:43 Deja Vu 15:50 Horizon 15:54 Say My Name 15:57 Sector 1 16:02 Good Lil Boy 16:09 Don’t Stop 16:12 Still Here (Acoustic Ver) 16:19 Siren 16:31 Guerrilla 16:45 We Know 17:00 Empty Box 17:28 Wake Up 17:40 Dancing Like Butterfly Wings 17:49 Work 18:09 Thanxx 18:26 If Without U 18:45 Shaboom 19:01 Outlaw 19:18 Treasure 19:33 Eternal Sunshine 20:03 Django 20:31 Turbulence Japanese Ver. 20:55 Blind 21:16 Pirate King 21:24 Forevermore 22:00 Birthday 22:11 Deep Dive 22:26 Ice On My Teeth 22:50 Man On Fire 23:10 Selfish Waltz 23:25 Enough

Updated: Vocals & Rap - #성화 #Seonghwa 00:00 Still Here 00:15 Wonderland 00:36 Halazia 00:47 Answer 01:21 Cyberpunk 01:27 Wave 01:37 Utopia 01:50 My Way 02:00 With U 02:16 Be With You 02:54 Star 1117 03:21 Turbulence (야간비행) 03:39 Days 04:26 Promise 04:38 Fever 04:54 Sunrise 05:19 Mist 05:43 Take Me Home 06:11 Better 06:34 All About You 06:43 Aurora 06:55 Blue Summer 07:23 Diamond 07:46 Time Of Love 07:58 Stay 08:07 Desire 08:21 WDIG 08:28 New World 08:35 Dreamers 08:53 Not Too Late 09:03 The Letter 09:19 One Day At A Time 09:28 Dazzling Light 09:40 Light 09:50 The Ring 10:04 Paradigm 10:18 This World 10:38 Bouncy 10:51 Not Okay 11:15 The King 11:23 Inception 11:52 Fireworks 12:03 Limitless 12:19 Precious 12:28 Rocky 12:41 Let’s Get Together 13:07 White Love 13:17 The Leaders 13:27 Crazy Form 13:43 Arriba 13:57 Silver Light 14:06 Dreamy Day 14:26 Matz 15:15 Outlaw 15:23 Twilight 15:31 Dune 15:38 Hala Hala 15:43 Deja Vu 15:50 Horizon 15:54 Say My Name 15:57 Sector 1 16:02 Good Lil Boy 16:09 Don’t Stop 16:12 Still Here (Acoustic Ver) 16:19 Siren 16:31 Guerrilla 16:45 We Know 17:00 Empty Box 17:28 Wake Up 17:40 Dancing Like Butterfly Wings 17:49 Work 18:09 Thanxx 18:26 If Without U 18:45 Shaboom 19:01 Outlaw 19:18 Treasure 19:33 Eternal Sunshine 20:03 Django 20:31 Turbulence Japanese Ver. 20:55 Blind 21:16 Pirate King 21:24 Forevermore 22:00 Birthday 22:11 Deep Dive 22:26 Ice On My Teeth 22:50 Man On Fire 23:10 Selfish Waltz 23:25 Enough

Hwanakin

62,764 Aufrufe • vor 1 Jahr

this GPT-6 Astra setup is getting f...cking dangerous 8 GitHub repos for turning one coding agent into an entire engineering team 01 OpenHands ▸ → autonomous software development 02 SWE-agent ▸ → issue → inspect repo → patch → test BUILD THE WORKERS 03 Aider ▸ → pair programming directly inside your repo 04 Cline ▸ → plan → edit → terminal → browser 05 Roo Code ▸ → specialized coding agent modes GIVE THEM A WORKSPACE 06 E2B ▸ → isolated sandboxes for parallel execution 07 Daytona ▸ → reproducible environments for agent workloads CHECK THE WORK 08 SWE-bench ▸ → test agents against real GitHub issues the swarm: issue → planner → split tasks → parallel agents → patches → tests → critic → merge one agent fixes the backend another handles the frontend another runs tests while a critic checks the diff that's where GPT-6 Astra gets interesting not one AI writing more code an entire software team running inside the repo ⭣

this GPT-6 Astra setup is getting f...cking dangerous 8 GitHub repos for turning one coding agent into an entire engineering team 01 OpenHands ▸ → autonomous software development 02 SWE-agent ▸ → issue → inspect repo → patch → test BUILD THE WORKERS 03 Aider ▸ → pair programming directly inside your repo 04 Cline ▸ → plan → edit → terminal → browser 05 Roo Code ▸ → specialized coding agent modes GIVE THEM A WORKSPACE 06 E2B ▸ → isolated sandboxes for parallel execution 07 Daytona ▸ → reproducible environments for agent workloads CHECK THE WORK 08 SWE-bench ▸ → test agents against real GitHub issues the swarm: issue → planner → split tasks → parallel agents → patches → tests → critic → merge one agent fixes the backend another handles the frontend another runs tests while a critic checks the diff that's where GPT-6 Astra gets interesting not one AI writing more code an entire software team running inside the repo ⭣

Lummox

35,870 Aufrufe • vor 12 Tagen

AI memory is getting f...cking illegal 10 open-source GitHub projects that stop agents from starting from zero EVERY new session 01 Mem0 ▸ → 66K+ stars 02 Hindsight ▸ → retain → recall → reflect 03 memU ▸ TURN MEMORY INTO KNOWLEDGE 04 Cognee ▸ → documents + code + conversations → knowledge graph 05 Graphiti ▸ → remembers how facts change over time 06 OpenViking ▸ MAKE THE AGENT STATEFUL 07 Letta ▸ → memory + identity across sessions 08 Letta Code ▸ REMEMBER ACROSS THE STACK 09 OpenMemory ▸ 10 Agent Memory Benchmark ▸ the loop: experience → remember → connect → retrieve → act → update 3 builds I'd actually test: coding: Hindsight → Cognee → Letta Code personal agent: Mem0 → Graphiti → Letta company brain: Cognee → Graphiti → Hindsight and this is where the sh...t gets interesting: bigger context isn't the same as memory a model can hold 1M tokens and still meet you for the first time every morning these projects change that save this before your agent forgets it ⭣

AI memory is getting f...cking illegal 10 open-source GitHub projects that stop agents from starting from zero EVERY new session 01 Mem0 ▸ → 66K+ stars 02 Hindsight ▸ → retain → recall → reflect 03 memU ▸ TURN MEMORY INTO KNOWLEDGE 04 Cognee ▸ → documents + code + conversations → knowledge graph 05 Graphiti ▸ → remembers how facts change over time 06 OpenViking ▸ MAKE THE AGENT STATEFUL 07 Letta ▸ → memory + identity across sessions 08 Letta Code ▸ REMEMBER ACROSS THE STACK 09 OpenMemory ▸ 10 Agent Memory Benchmark ▸ the loop: experience → remember → connect → retrieve → act → update 3 builds I'd actually test: coding: Hindsight → Cognee → Letta Code personal agent: Mem0 → Graphiti → Letta company brain: Cognee → Graphiti → Hindsight and this is where the sh...t gets interesting: bigger context isn't the same as memory a model can hold 1M tokens and still meet you for the first time every morning these projects change that save this before your agent forgets it ⭣

Lummox

329,600 Aufrufe • vor 16 Tagen

OpenAI Dots is f*cking insane for building a 24/7 AI company... here's a one-person company architecture to build around it: one founder. five workstreams. one connected operating loop 01 research customer signals + documents → a source-backed brief with the evidence behind each decision 02 product the brief + recurring feedback → scoped changes, tested code and PRs ready for review 03 content product updates + your voice → launch materials, clips and social drafts 04 sales account history + customer requirements → proposals, proof-of-concept work and a test plan 05 operations business records + open commitments → prepared invoices, follow-up drafts and work ready for approval the useful part is how the branches connect: research shapes the product. product changes feed content. sales requirements feed testing. your corrections improve the next run the loop: set the goal → connect the context → collect evidence → prepare the work → review and approve → feed corrections back the rollout starts with one primary dot. the five branches in this map are workstreams around it set app permissions and approval rules upfront. proactive background research uses read-only tools save this, then build your company with Dots ⭣

OpenAI Dots is f*cking insane for building a 24/7 AI company... here's a one-person company architecture to build around it: one founder. five workstreams. one connected operating loop 01 research customer signals + documents → a source-backed brief with the evidence behind each decision 02 product the brief + recurring feedback → scoped changes, tested code and PRs ready for review 03 content product updates + your voice → launch materials, clips and social drafts 04 sales account history + customer requirements → proposals, proof-of-concept work and a test plan 05 operations business records + open commitments → prepared invoices, follow-up drafts and work ready for approval the useful part is how the branches connect: research shapes the product. product changes feed content. sales requirements feed testing. your corrections improve the next run the loop: set the goal → connect the context → collect evidence → prepare the work → review and approve → feed corrections back the rollout starts with one primary dot. the five branches in this map are workstreams around it set app permissions and approval rules upfront. proactive background research uses read-only tools save this, then build your company with Dots ⭣

beamnxw ./

98,232 Aufrufe • vor 11 Tagen

This is EVERYTHING you need to know about building a Company Brain in 28min. From connecting all your tools into one intelligence layer to the new org chart around it. This is the new way to work in the AI era. Here's the full breakdown: 00:00 Introduction & AI Adoption 01:45 The Four Levels of AI Maturity 02:30 The Single Brain Concept 05:30 Building an AI-Powered Org 07:20 Specialist Agents & Agent Fleets 11:20 Workflows & Closed Loops 14:30 Real Agent Examples in Slack 18:00 AI ROI & Token Economics 20:45 Business-to-Agent Commerce 24:10 Action Steps & Future of Work

This is EVERYTHING you need to know about building a Company Brain in 28min. From connecting all your tools into one intelligence layer to the new org chart around it. This is the new way to work in the AI era. Here's the full breakdown: 00:00 Introduction & AI Adoption 01:45 The Four Levels of AI Maturity 02:30 The Single Brain Concept 05:30 Building an AI-Powered Org 07:20 Specialist Agents & Agent Fleets 11:20 Workflows & Closed Loops 14:30 Real Agent Examples in Slack 18:00 AI ROI & Token Economics 20:45 Business-to-Agent Commerce 24:10 Action Steps & Future of Work

ericosiu

60,315 Aufrufe • vor 3 Monaten

this is pure f*cking treasure 30 best MCP servers, mapped across 10 categories for building your agent's toolbox search. code. browser automation. files. databases. memory. agents. productivity. research. finance 01 SEARCH & INTERNET Brave Search MCP Server ▸ Google Maps MCP Server ▸ World Monitor MCP ▸ 02 PROGRAMMING Sentry MCP Server ▸ Context7 MCP ▸ GitHub MCP Server ▸ 03 BROWSER & AUTOMATION Fetch MCP Server ▸ Chrome DevTools MCP ▸ Playwright MCP Server ▸ 04 FILES & DOCUMENTS Filesystem MCP Server ▸ Google Drive server ▸ MCP server for Obsidian ▸ 05 DATABASES PostgreSQL ▸ SQLite MCP Server ▸ MCP Toolbox for Databases ▸ 06 MEMORY & RAG Knowledge Graph Memory Server ▸ Graphiti MCP Server ▸ cognee-mcp ▸ 07 AI AGENTS Taskmaster ▸ BlenderMCP ▸ Talk to Figma MCP ▸ 08 WORK & PRODUCTIVITY Google Workspace MCP Server ▸ Todoist AI MCP Server ▸ Thunderbird MCP ▸ 09 RESEARCH & ANALYTICS Phoenix MCP ▸ Zotero MCP ▸ NotebookLM MCP Server ▸ 10 BUSINESS & FINANCE Finance Toolkit ▸ Financial Datasets MCP Server ▸ Stripe MCP Server ▸ the stack covers the full agent loop: find information ⮕ write and inspect code ⮕ operate the browser ⮕ read files ⮕ query data ⮕ remember context ⮕ delegate work ⮕ run operations ⮕ analyze evidence ⮕ handle payments some reference servers above live in archived repositories, so check maintenance and permissions before production use save this, then select your gpt-6 astra use case ⭣

this is pure f*cking treasure 30 best MCP servers, mapped across 10 categories for building your agent's toolbox search. code. browser automation. files. databases. memory. agents. productivity. research. finance 01 SEARCH & INTERNET Brave Search MCP Server ▸ Google Maps MCP Server ▸ World Monitor MCP ▸ 02 PROGRAMMING Sentry MCP Server ▸ Context7 MCP ▸ GitHub MCP Server ▸ 03 BROWSER & AUTOMATION Fetch MCP Server ▸ Chrome DevTools MCP ▸ Playwright MCP Server ▸ 04 FILES & DOCUMENTS Filesystem MCP Server ▸ Google Drive server ▸ MCP server for Obsidian ▸ 05 DATABASES PostgreSQL ▸ SQLite MCP Server ▸ MCP Toolbox for Databases ▸ 06 MEMORY & RAG Knowledge Graph Memory Server ▸ Graphiti MCP Server ▸ cognee-mcp ▸ 07 AI AGENTS Taskmaster ▸ BlenderMCP ▸ Talk to Figma MCP ▸ 08 WORK & PRODUCTIVITY Google Workspace MCP Server ▸ Todoist AI MCP Server ▸ Thunderbird MCP ▸ 09 RESEARCH & ANALYTICS Phoenix MCP ▸ Zotero MCP ▸ NotebookLM MCP Server ▸ 10 BUSINESS & FINANCE Finance Toolkit ▸ Financial Datasets MCP Server ▸ Stripe MCP Server ▸ the stack covers the full agent loop: find information ⮕ write and inspect code ⮕ operate the browser ⮕ read files ⮕ query data ⮕ remember context ⮕ delegate work ⮕ run operations ⮕ analyze evidence ⮕ handle payments some reference servers above live in archived repositories, so check maintenance and permissions before production use save this, then select your gpt-6 astra use case ⭣

beamnxw ./

70,644 Aufrufe • vor 29 Tagen

this is pure f*cking treasure Anthropic devs just posted 20 GitHub repos that turn your Claude Code into a f*cking engineering team: Exposed for Opus 5.5 1. rtk: squeezes command output before it hits your context. the authors claim 60-90% fewer tokens 2. claude-mem: memory across sessions. records what the agent did and brings back what matters 3. ccusage: shows where your tokens and money went. one command, npx ccusage 4. Serena: search and edit code by meaning, not by text 5. Context7: up-to-date library docs, so Claude stops writing for last year's API 6. claude-context: your whole codebase searchable through MCP 7. Repomix: packs an entire repo into one AI-friendly file skills and method 8. superpowers: a skills framework and a full development methodology. the one almost everyone installs 9. skills: the official Agent Skills repo from Anthropic 10. spec-kit: spec-driven development, from GitHub itself 11. agents: a plugin marketplace for Claude Code and six other harnesses 12. claude-code-templates: ready configs and monitoring from one CLI 13. claude-code-hooks-mastery: hooks explained with working examples 14. awesome-claude-code: the hand-picked map of everything else running more than one agent 15. container-use: a separate container for every agent, so they stop breaking each other 16. claude-squad: several terminal agents in one window 17. Happy: control your agents from your phone, iOS and Android 18. claude-code-router: route requests across different models 19. ccstatusline: a status line that shows what your session is doing 20. tweakcc: edit Claude Code's own system prompts, toolsets and themes the stack in one line: memory keeps the context, skills set the method, containers let you run five agents instead of one. check each repo before you install. save this.

this is pure fcking treasure Anthropic devs just posted 20 GitHub repos that turn your Claude Code into a fcking engineering team: Exposed for Opus 5.5 1. rtk: squeezes command output before it hits your context. the authors claim 60-90% fewer tokens 2. claude-mem: memory across sessions. records what the agent did and brings back what matters 3. ccusage: shows where your tokens and money went. one command, npx ccusage 4. Serena: search and edit code by meaning, not by text 5. Context7: up-to-date library docs, so Claude stops writing for last year's API 6. claude-context: your whole codebase searchable through MCP 7. Repomix: packs an entire repo into one AI-friendly file skills and method 8. superpowers: a skills framework and a full development methodology. the one almost everyone installs 9. skills: the official Agent Skills repo from Anthropic 10. spec-kit: spec-driven development, from GitHub itself 11. agents: a plugin marketplace for Claude Code and six other harnesses 12. claude-code-templates: ready configs and monitoring from one CLI 13. claude-code-hooks-mastery: hooks explained with working examples 14. awesome-claude-code: the hand-picked map of everything else running more than one agent 15. container-use: a separate container for every agent, so they stop breaking each other 16. claude-squad: several terminal agents in one window 17. Happy: control your agents from your phone, iOS and Android 18. claude-code-router: route requests across different models 19. ccstatusline: a status line that shows what your session is doing 20. tweakcc: edit Claude Code's own system prompts, toolsets and themes the stack in one line: memory keeps the context, skills set the method, containers let you run five agents instead of one. check each repo before you install. save this.

kiosa

55,680 Aufrufe • vor 5 Tagen

GPT-6 Astra is by far the best inside Codex. & this is THE Complete Beginners Guide to Codex. The 28 things you need to know about Codex and GPT-6 to start using it for knowledge work and coding work. My goal with this video: give you one guide you can send to anyone on your team so they can get comfortable with Codex, understand what’s possible, and start finding ways to use AI in your business. 00:00 Intro 01:15 The Codex Platform 02:02 Downloading Codex (ChatGPT Desktop) 03:25 1. Codex Is the App, GPT-6 Is the Model 06:10 2. Build Any App 10:32 3. Host Sites with GPT Sites 18:12 4A. Building Desktop App 21:33 4B. Building an iOS app 24:09 5. Built-In Web Browser 32:27 6. Create Any Document 35:00 7. Annotation Mode 38:41 8. Production-Ready Apps 44:29 9. Chats & Projects 48:54 10. Multitasking 50:09 10B Side Chat 51:13 11. Sections 54:27 12. Connect Every App (Plugins) 01:03:17 13. Ask Codex What to Work On 01:05:39 14. Blender & 3D Assets 01:08:25 15. Video Games 01:09:24 16. Interactive Learning Websites 01:13:12 17. Scheduled Tasks 01:16:19 18. Email & iMessage 01:18:56 19. Skills 01:22:54 20. Record and Replay 01:26:45 21. External APIs in Skills 01:30:00 22. Video Understanding Skill 01:35:51 23. Inline Charts 01:38:03 24. Control Codex from Your Phone 01:42:49 25. Generate & Edit Images 01:45:17 26. Sub-Agents 01:48:09 27. Computer Use 01:49:35 28. Whatever You Want

GPT-6 Astra is by far the best inside Codex. & this is THE Complete Beginners Guide to Codex. The 28 things you need to know about Codex and GPT-6 to start using it for knowledge work and coding work. My goal with this video: give you one guide you can send to anyone on your team so they can get comfortable with Codex, understand what’s possible, and start finding ways to use AI in your business. 00:00 Intro 01:15 The Codex Platform 02:02 Downloading Codex (ChatGPT Desktop) 03:25 1. Codex Is the App, GPT-6 Is the Model 06:10 2. Build Any App 10:32 3. Host Sites with GPT Sites 18:12 4A. Building Desktop App 21:33 4B. Building an iOS app 24:09 5. Built-In Web Browser 32:27 6. Create Any Document 35:00 7. Annotation Mode 38:41 8. Production-Ready Apps 44:29 9. Chats & Projects 48:54 10. Multitasking 50:09 10B Side Chat 51:13 11. Sections 54:27 12. Connect Every App (Plugins) 01:03:17 13. Ask Codex What to Work On 01:05:39 14. Blender & 3D Assets 01:08:25 15. Video Games 01:09:24 16. Interactive Learning Websites 01:13:12 17. Scheduled Tasks 01:16:19 18. Email & iMessage 01:18:56 19. Skills 01:22:54 20. Record and Replay 01:26:45 21. External APIs in Skills 01:30:00 22. Video Understanding Skill 01:35:51 23. Inline Charts 01:38:03 24. Control Codex from Your Phone 01:42:49 25. Generate & Edit Images 01:45:17 26. Sub-Agents 01:48:09 27. Computer Use 01:49:35 28. Whatever You Want

Riley Brown

193,991 Aufrufe • vor 29 Tagen

this is pure f*cking treasure 20 ready-made Grok Bot templates to build your own AI team research. product. engineering. sales. content. operations each link opens a template you can import, connect to your apps and shape around a real job 01 last30days recent conversations → a grounded research brief ▸ 02 Researchy live sources → researched, fact-checked claims ▸ 03 Product Idea Stress Test startup idea → risky assumptions + the next experiment ▸ 04 Stalk Bot competitor moves → changes that affect your positioning ▸ 05 Critiquito product screens → ranked design fixes ▸ 06 PM bot feature request → scope + acceptance criteria ▸ 07 Proto Bot feature idea → working prototype + draft PR ▸ 08 Engineering Lead engineering work → cloud agents, CI and review follow-through ▸ 09 Startup QA Bot product walkthrough → bugs, screenshots and repro steps ▸ 10 tinkabot API → an MCP + skills plugin ▸ 11 Outbound Prospecting ideal customer profile → researched prospects + outreach drafts ▸ 12 SEO & AEO Desk keywords → content opportunities + writer-ready briefs ▸ 13 GTM Loop Closer scattered customer conversations → follow-ups with evidence ▸ 14 Sales Call Coach call recordings → specific things to fix next time ▸ 15 Copy Humanizer rough drafts → clear writing in your voice ▸ 16 Clip Bot long recordings → short captioned clips ▸ 17 Stills & Clips Desk existing footage → thumbnails, stills and sized clips ▸ 18 Meeting Recap Deck meeting notes → recap slides in your template ▸ 19 Haggle Bot SaaS bills → savings opportunities + vendor counteroffers ▸ 20 Projects Manager Notion projects → tasks your specialist bots can claim ▸ three combos worth building: last30days → Product Idea Stress Test → PM bot → Proto Bot → Startup QA Bot Clip Bot → Stills & Clips Desk → Copy Humanizer one recording → clips, thumbnails and edited post copy Outbound Prospecting → Sales Call Coach → GTM Loop Closer the loop: find the signal → test the idea → define the work → build → check → prepare the next action → review → save the repeatable process start with the jobs you actually need → connect the required accounts → configure the handoffs → test the loop keep sends, merges and spend behind your approval save this, then build a harness for your Grok bot ↓

beamnxw ./

16,592 Aufrufe • vor 7 Tagen

AI research is getting f...cking illegal 15 GitHub projects for turning a question into sources, evidence, citations, and a finished report 01 GPT Researcher ▸ → recursive deep research 02 STORM ▸ SEARCH DEEPER 03 Perplexica ▸ 04 Open Deep Research ▸ 05 DeerFlow ▸ READ THE WEB 06 Firecrawl ▸ 07 Crawl4AI ▸ 08 Jina Reader ▸ TURN PAPERS INTO EVIDENCE 09 PaperQA2 ▸ → agentic RAG + citations 10 OpenScholar ▸ 11 PaperMage ▸ CONNECT THE SOURCES 12 GraphRAG ▸ 13 LightRAG ▸ 14 Kotaemon ▸ 15 Docling ▸ the loop: ask → split the problem → search multiple paths → read the sources → extract evidence → connect the findings → challenge the answer → cite → write 3 stacks I'd actually try: deep research: GPT Researcher → Firecrawl → GraphRAG → Docling scientific: OpenScholar → PaperQA2 → PaperMage → LightRAG private research: Perplexica → Crawl4AI → Kotaemon → GraphRAG the interesting part isn't generating a 20-page report it's being able to trace where every important claim came from AI already learned how to write this stack teaches it how to research ⭣

AI research is getting f...cking illegal 15 GitHub projects for turning a question into sources, evidence, citations, and a finished report 01 GPT Researcher ▸ → recursive deep research 02 STORM ▸ SEARCH DEEPER 03 Perplexica ▸ 04 Open Deep Research ▸ 05 DeerFlow ▸ READ THE WEB 06 Firecrawl ▸ 07 Crawl4AI ▸ 08 Jina Reader ▸ TURN PAPERS INTO EVIDENCE 09 PaperQA2 ▸ → agentic RAG + citations 10 OpenScholar ▸ 11 PaperMage ▸ CONNECT THE SOURCES 12 GraphRAG ▸ 13 LightRAG ▸ 14 Kotaemon ▸ 15 Docling ▸ the loop: ask → split the problem → search multiple paths → read the sources → extract evidence → connect the findings → challenge the answer → cite → write 3 stacks I'd actually try: deep research: GPT Researcher → Firecrawl → GraphRAG → Docling scientific: OpenScholar → PaperQA2 → PaperMage → LightRAG private research: Perplexica → Crawl4AI → Kotaemon → GraphRAG the interesting part isn't generating a 20-page report it's being able to trace where every important claim came from AI already learned how to write this stack teaches it how to research ⭣

Lummox

38,193 Aufrufe • vor 15 Tagen