Dabl Club🦞

Omg.. this can't be true... I kept building AI agents on my eventually list because everything I read made it sound like a six month project requiring a technical background I did not have. One Reddit thread changed that by saying the one thing nobody had said clearly: pick the smallest possible problem and finish it completely before you try to build anything impressive. MY ARTICLE IS THE CLAUDE CODE VERSION OF THAT LESSON. Working agent - Under one hour - Zero coding. Full guide below.

Still the best 2 hours on AI ever recorded, Andrej Karpathy showing how he actually uses it on a daily basis: 18:03 - Which model to actually use 22:54 - When thinking models are worth it 42:04 - One prompt to a full research report 59:00 - Make the model run code for you 1:53:29 - Make it remember you across chats Most people use 10% of what these models can do, this is the other 90%. I took everything he covers and turned it into a guide of Claude features almost nobody knows about. Watch him first, then go to the article below, everything shown plainly, ready to use right away.

@dabit3 What do you use for sandboxes?

this sucks, there's a simple way to prevent this from ever happening: add a PreToolUse hook that hard-blocks any command touching paths outside the repo (works even in yolo mode) + maybe permissions.deny rules as backup. might as well install it on all local projects. github.com/dabit3/bash-gu… or just use a cloud agent, it runs on a throwaway machine.

New skill: /apple-design Apple’s WWDC videos are a goldmine of knowledge. I’ve combed through my favorite ones and came up with 17 design and motion principles. Use them to review existing work or when working on something new to get it right. github.com/emilkowalski/s…

We scaled to $3.5M ARR in less than 1 year. No one wants to hear this, but there’s no magic distribution channel. We scalled by testmaxxing every channel depending on our MRR level. €0 → $6k MRR: pure outbound. Cold email plus LinkedIn, using our own early product on ourselves. No brand, no audience, just us reaching out to people showing intent and starting conversations. Ugly, manual, effective. $10k → $25k MRR: Reddit. Our first real acquisition breakthrough. We posted educational breakdowns in SaaS subreddits and did 10M+ organic views. The traffic quality wasn't amazing, but the volume was so huge it flooded our trial funnel for months. Cost: basically zero. $25k → $75k MRR: content plus free blueprints. We went all-in on LinkedIn content, YouTube, motion-design videos, and giving away our internal systems as free "blueprints." Content got the reach, the blueprints earned the trust, and a chunk of readers converted. This is where founder-led content started compounding. $75k → $150k MRR: partnerships and X. We added Twitter, B2B influencers, sponsored newsletters, and a lifetime affiliate program that became a major lever. We also joined YC around here, and the intensity went vertical. $150k+ MRR: paid and hiring. Meta ads, Google ads, influencer agencies, and hiring seriously for the first time, growth, sales, engineering, product. None of these stages replaced the last one. They stacked. Outbound never stopped. Content never stopped. We just kept adding the next lever once the current one was clearly working. If you take one thing from this: don't chase five channels at once. Beat one until it works, then add the next.

My top open source repos: 1. Mission Control self-hosted AI agent orchestration dashboard tasks, multi-agent workflows, spend, governance 5.7k stars github.com/builderz-labs/… 2. awesome-hermes-agent curated skills, tools, integrations, and resources for Hermes Agent 4.6k stars github.com/0xNyk/awesome-… 3. council-of-high-intelligence 18 AI personas deliberate hard decisions across multiple LLM providers 3.4k stars github.com/0xNyk/council-… 4. xint X intelligence CLI for search, monitoring, analysis, and engagement github.com/0xNyk/xint 5. marketing-dashboard open-source marketing ops control center for AI agent teams github.com/builderz-labs/… 6. awesome-agent-cortex sovereign agent stack for memory, identity, and agent ownership github.com/0xNyk/awesome-… the thesis is simple: agents need infrastructure, not more demos. Follow @nyk_builderz for the daily build in public.

48 HOURS AFTER KARPATHY POSTED HIS LLM WIKI IDEA, A 26-YEAR-OLD BIRMINGHAM GRAD SHIPPED THE ONE COMMAND THAT MAKES IT WORK. IT NOW HAS 76,000 GITHUB STARS 1 command. 71.5x fewer tokens per query. 0 vector databases points graphify at any folder - codebase, docs, PDFs, screenshots, video. Tree-sitter parses the code, Claude reads the prose, the whole thing lands as a knowledge graph in graphify-out/ one flag - --obsidian - writes the entire graph as a fully-linked Obsidian vault: one markdown note per concept, every relationship a wikilink, every node linked back to its source. Drop the vault into Claude Code as a skill. Claude queries the graph instead of grepping through raw files, forever Safi Shamsi finished his MSc at Birmingham with Distinction in 2025. His thesis was a knowledge-graph RAG system for academic search. He shipped Graphify 48 hours after Karpathy's post, iterates every week, and has already been forked by Rootly AI Labs for incident data. Hacker News, Analytics Vidhya, Towards AI - all organic.76,000 stars. Three months old no neo4j server. no vector db. no embedding pipeline. no cloud. no monthly fee you're reading this on a device that could clone the repo, run one command, and have a Claude-native knowledge graph of your entire codebase in Obsidian before your next standup

Introducing Loopany 🔁 Stop prompting, Design the loop. A loop management space that connects to your team’s own local agents: - Scaffold loop contracts, state, and logs - Add programmable triggers - Run self-improving cycles - Start from built-in loop templates We baked in everything we’ve learned from running loops inside our own team. Free and open source. Keen to hear your feedback: github.com/superdesigndev…

@realAkashAnand VIDEO SKILLS

GPT-5.6 Sol is unbelievably good at creating and editing videos. It can do motion design, product demos, and animations like this one I made by simply giving it a screen recording. GPT 5.6 has the best design taste and significantly outperforms Fable, which relies heavily on repetitive design patterns. To help you experiment with video editing on it, we just launched a collection of 100 ready-to-use skills that show what’s possible and help you get started with video editing using GPT-5.6. These skills can create anything from motion graphics launch videos for your product to a 3B1B-style science explainer video. You can also use them to edit existing videos: add captions, generate motion graphics, create voiceovers, redesign visual styles, translate into new languages, and much more. If you want access to the full library, comment “VIDEO SKILLS” and I’ll share it with you. (You'll have to follow me so I can DM you.)

@AlfieJCarter CONTENT

The LinkedIn Content Generator is the most reliable way to produce consistent LinkedIn content in 2026 without starting from scratch every week. Usually, I'd charge $199 for this guide, but today you can get it for free. 7 commands that write your posts, build your carousels, draft your newsletters, plan your 30-day calendar, and get better at your voice the more you use them. Works in Claude Code, Cursor, or any SKILL.md harness. Like + comment "CONTENT" & I'll send you my proven guide for FREE. Must follow me to get the guide in DM. FREE for next 48 hours.

@BLRxZo @PHKxZo I’ll take 3 rooms.

Who wants to spend a month in Phuket at our Hacker Hostel? @PHKxZo 🌴💻 Who’s interested? Comment!

There's a GitHub repo that gives you AI for free. Forever. It's called "free-llm-api-resources." It lists every free AI provider in one place: → OpenRouter (dozens of free models behind 1 API key) → Google AI Studio → Nvidia + Mistral free tiers → Free local models that run offline Plug them into your agents and coding tools. Pay $0. There's even a router that auto-switches between 90 free providers. So you never hit rate limits. Most people pay $200/month for AI. Smart people bookmark this repo.

Anthropic just dropped 5 workshops on building self-improving agentic systems from scratch: 00:00 - Ship your first Claude agent 36:44 - Build memory for Claude agents 1:05:06 - Make your agent autonomous 1:26:46 - Set up a proactive agent 2:03:35 - self-improving agents (tools,skills) These 3-hours of free Claude workshops will replace 10 paid agentic courses. Watch today, then read article below on how to build a self-improving agentic system with Fable 5.

BRO this is the laziest possible way to get an AI employee. Don't set up anything yourself. Paste this article into your Hermes session and say: "Read this end to end, then set up background agents, connect iMessage, and build whichever profiles fit my workflow." That's it. You spend 5 minutes reading, the agent spends 30 building, and by tonight you're texting it like a team member. Articles aren't content anymore. They are playbooks your agent runs for you.

Hermes Agent by just crossed 200K GitHub stars in just a few months. I tested every claim in the @NousResearch project: memory, skills, cron, sub agents, all from Hermes Desktop App and WhatsApp. The whole system is one loop: message in → agent run → tools fire → loop ends → memory saved → skills grow What surprised me: No embeddings anywhere. Skills and user facts are plain text files. Chat history is one local database. And it still compounds: the longer it runs, the harder it is to leave. The moat is memory, not the model. I caught two gaps too: it never saved a non-complicated skill without being asked, and a cron bug. Details in the video. Watch it, then save the harness diagram below. 🔖 You Can Build Anything. You Can Learn Anything. 💪

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

YOUR HERMES AGENT IS FLYING BLIND WITHOUT A MAP THAT LOOKS LIKE THIS hundreds of nodes, every connection visible, spectral data mapped in real time so nothing gets lost your vault has the same complexity under the hood, your agent just can’t see it I learned this the hard way, one task took 2 minutes opening wrong files for a brief from 3 months ago one index file per major folder fixed it, dropped to 10 seconds build the map, the agent finds everything full breakdown in the article below ↓

@AlfieJCarter Agents

R.I.P. rebuilding your GTM stack from scratch every session. A complete Claude Skill Library can replace a $15,000/month agency retainer. It is not as easy as hiring someone else to do it. But if you start today, you can have 56 skills loaded into Claude covering SEO, content, outbound, sales, growth, analytics, strategy, ads, social, and CRM by end of this week. I usually charge $299 for access to this library but today, it's free. Like this post + comment 'Agents' and I'll DM you the entire skill library for free. (Must be following, or I can't message.) Taking this down in 48 hours.

Anthropic's internal loop engineering playbook just got leaked. And it's the most valuable AI guide I've read all year. This guide is packed with info, and there are five things you need to know if you want to maximize your AI productivity with loops (save this): 1. You should structure every loop around these 5 principles: • Discovery → Let the agent find its own work (CI fails, issues, commits) • Handoff → Give every task its own isolated git worktree • Verification → Never let the generator grade its own work • Persistence → Always write state to disk (markdown or board) • Scheduling → Run it on a timer so it works while you sleep 2. Separate Generator from Evaluator (most important rule) Use two agents: one writes, the other is a skeptical judge who assumes the code is broken. Make the evaluator act (run tests, click buttons, take screenshots) - this is what actually stops bad output. 3. Build with these 6 parts: • Automations (the timer) • Worktrees (safe parallelism) • Skills (permanent project knowledge) • Connectors (talk to GitHub, Linear, etc.) • Sub-agents (generator + evaluator) • Memory (state files that survive between runs) 4. Things you must watch out for with loop engineering: • Verification debt (use verification agents) • Losing understanding of your own codebase (start fresh if needed) • Token costs exploding (solution below) • Cognitive surrender (don't stop thinking because “the loop handles it”) 5. Solving token costs Loop engineering can be crazy expensive. I recommend you use an 80/20 "barbell" approach to loop engineering. For your most complex tasks that require the best intelligence, use expensive models (Opus). For the remaining 80% of your tasks (the gruntwork), use cheap, open-source models within the Claude Code harness (GLM-5.2 is great for code execution). Save these 5 rules so you don't forget them.