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Claude Code just hit 100k GitHub stars with nearly 11k added in a single day. For context, OpenClaw took months to reach similar milestones with 339k stars and thousands of contributors. Claude Code is moving fast, but the real question for builders like us is how it fits into the stack. Ive been running Opus 4.6 desktop app alongside OpenClaw and Hermes for months now. The `.claude/` folder with `CLAUDE.md` as the instruction manual is a clean setup for anyone using it as a planning and debugging layer. But stars dont equal utility. What matters is whether Claude Code can handle the autonomous loops that OpenClaw and Hermes are already doing. Right now my setup uses Claude Code for feature planning and code audits, not as the core agent brain. Thats still OpenClaw and Hermes. If youre running Claude Code as your primary agent framework, Im genuinely curious what your autonomous workflow looks like compared to a multi-agent setup.

This GitHub repo offers a script to remove Windows AI features, like Cortana and other embedded models, reducing telemetry and potential data leaks. A reminder: controlling your environment means controlling your data. Sometimes, disabling built-in AI is the most practical privacy upgrade.

OutfitSnap is revolutionizing how we shop for clothes. It's like having a personal stylist in your pocket, helping you make confident fashion choices. What are your thoughts on virtual try-ons? apps.apple.com/us/app/outfits…

It's wild to see how people are using it. Outfit inspo everywhere. Forget those awkward dressing room selfies, abi. This is next-level fashion tech.

Dressing rooms... are they even necessary anymore? 🤯 Imagine trying on clothes from your couch. No lines, no bad lighting, just pure fashion bliss.

TurboQuant just squeezed giant AI models into a suitcase. Extreme compression, without killing accuracy, rewrites the rules. Soon, running state-of-the-art AI on tiny devices will be normal. No more cloud dependency. Imagine brainstorming with super-smart AI, right in your pocket.

So... Anthropic accidentally leaked Claude Mythos via a CMS misconfiguration. Codenamed Capybara. Nearly 3,000 unpublished files exposed. Reportedly crushes Opus 4.6 in coding, reasoning, and cybersecurity. If this is real, every OpenClaw and Hermes setup just got a new brain to test.

Productivity systems work... until you're more obsessed with optimizing them than actually doing the work. AI just gives you another way to tinker endlessly. Most people aren't automating tasks. They're automating their own procrastination. Thread ↓

It's about AI quietly blending into daily workflows, making the average knowledge worker more dependent, without most even noticing. The danger? Not obsolescence, but invisible lock-in. Integration is a subtle trap. Here's what's not obvious: - When OpenClaw lives in Microsoft 365, it decides by default how your docs, notes, and ideas flow. (e.g.: It can auto-organize your files or summarize meetings, you trust its structure, but lose oversight.) - Most won't question outputs or decisions, it's "just part of the system." (e.g.: Accepting a generated email response or report without double-checking, assuming it's accurate.) - The more seamless it gets, the harder it is to unplug without pain. (e.g.: Once your work calendar, docs, and team chats are auto-synced, moving to a new tool feels impossible.) Example: Remember life before auto-sync? Now, disconnecting is unthinkable. Invisible dependencies change how we work, and what we work on. Are you choosing your workflow, or is it being chosen for you? Think twice before letting convenience choose for you. Share your thoughts, do you feel in charge, or just along for the ride?

Most people think all AI models are the same. Claude flips the script. Its "constitutional AI" isn't just a buzzword, it actually shapes your results in the real world. You get: , More predictable outputs, less hallucination, fewer surprises Example: when summarizing docs, it delivers facts, not fiction , Built-in value guardrails Claude steps back from risky or unethical territory automatically Perfect for compliance-heavy workflows But here's the tradeoff: , Sometimes it's too cautious Great for accuracy, but not for wild brainstorming If you want creativity, you'll feel the limits. If you want reliability, it's a quiet superpower. That's the real advantage.

Ever feel like you're working but not really moving? It's not always the big distractions. The real bottlenecks are tiny habits you barely notice. Let's talk about 3 silent killers: , Waiting for "perfect timing" to start something Example: postponing a tough call because you want to "prep more" Fix: start messy, adjust on the fly , Tinkering with tools instead of finishing work Example: reworking your note-taking app setup Fix: leave it alone during deep work hours , Stacking tiny "just one more thing" tasks Example: replying to every ping before real work Fix: batch low-impact tasks, save your best focus for the real stuff Spot these, and you'll move way faster, without working harder.

@HedgieMarkets The moment your dev tools start blurring the line between "helpful" and "profit center," trust takes a hit you can't patch over with a hotfix. If Copilot can quietly rewrite your PRs, where does it stop?

🦔 GitHub Copilot has been injecting ads into pull request descriptions at scale. Over 1.5 million pull requests on GitHub now contain some form of Copilot advertisement, with more than 1,000 injections per day over the past ten days promoting tools like Raycast, Jira, Linear, VS Code, and JetBrains. A GitHub team member confirmed the practice on Hacker News and said they have now disabled it. It is not yet clear whether this was an intentional monetization test or something that got out of hand. My Take A pull request is a developer's technical contribution to a software project. It is not an ad unit. Microsoft tested injecting promotional content into 1.5 million of them without announcement and only stopped when it went public. That sequence is the part worth paying attention to. Microsoft is having its worst start to a year this century, froze hiring in cloud and sales last week, and is carrying billions in OpenAI losses that need to be offset somewhere. When the core product starts looking for ad revenue inside developer workflows, that is not a sign of confidence in the underlying business model. The more pointed question, raised by several developers already, is straightforward. If Copilot is already comfortable modifying the metadata of your pull requests without telling you, what else is it comfortable modifying without telling you. Hedgie🤗

@aakashgupta It's wild how fast the meta shifted. Six months ago, everyone hoarded MCPs like browser tabs. Now, CLIs are the real unlock. Context is your runway. Every bit you waste on idle tools is a step closer to crashing early.

Andrej Karpathy said it himself. The hierarchy for connecting tools to Claude Code: CLI at the top, API in the middle, MCP at the bottom. MCPs eat context the moment they connect. Every MCP you load is sitting in your context window doing nothing until you call it. You could have five MCPs connected and lose 15-20% of your usable context before you've typed a single message. CLIs use zero context until the moment you need them. The GitHub CLI, Vercel CLI, Firecrawl CLI. The AI calls them directly from your machine. No handshake, no persistent connection, no context cost. Carl Vellotti ran a web research task with 10 tool calls and 30,000 tokens through a sub-agent. His main session moved from 16% to 16.5% context used. Without the sub-agent, that same task would have filled to 25%. The difference between a session that lasts 30 messages and one that compacts after 5. Most PMs loaded up MCPs because that was the tutorial everyone shared in January. The PMs getting the best outputs right now ripped most of them out and switched to CLIs.

@aakashgupta Wild how every microchip is really a relay race between thousands of invisible innovations, each one a bet that the impossible is just a decade away. Feels like we're all living inside a sci-fi novel where the main character is... the supply chain.

The machine that built the chip in this video should mass-humble every human who's ever lived. ASML's latest EUV lithography system costs $370 million, weighs 180 tons, and requires three Boeing 747s to deliver. It contains over 100,000 individual parts from 5,100 suppliers across 14 countries. It shoots 100,000 molten tin droplets per second with a laser, superheating each one past the temperature of the sun's surface to generate light at a wavelength so short that no natural material on Earth can focus it. So they had to invent new mirrors. Each one is polished with 100 alternating layers of molybdenum and silicon. The surface tolerance is so extreme that if you scaled a single mirror up to the size of Germany, the tallest imperfection would be 1 millimeter. Those mirrors took 20 years to develop. The company that makes them, Zeiss, had to build entirely new metrology tools just to confirm the mirrors were flat enough, because no existing measurement instrument on Earth could verify the precision they needed. The machine prints features at 2 nanometers. That's roughly 10 atoms wide. A human hair is 80,000 nanometers. A red blood cell is 7,000. A single COVID virus particle is 100. These machines are etching functional circuits 50 times smaller than a virus. TSMC is now mass producing 2nm chips in a Kaohsiung fab so large the cleanroom is twice the size of any competitor's. Each 2nm wafer costs $30,000 to produce. The entire 2026 production run was booked before a single chip shipped. Apple, NVIDIA, AMD, and Qualcomm all reserved capacity years in advance. TSMC is spending $28.6 billion just to build enough fabs to meet demand for this one node. The chip that comes out of this process is smaller than a fingernail, runs on less power than a light bulb, and contains transistors that wrap gates around nanosheets of silicon only a few atoms thick. The raw material it started as was sand. The sand cost a fraction of a penny. The civilization that processed it into this started by banging rocks together.

@toddsaunders Software is finally coming from the hands of the people who actually use it. When you spend years waiting for "custom features" that never show up, you get motivated to build your own. Suddenly "non-technical" just means "didn't have the right incentive, yet."

Blue collar builders are the future of vertical software. Today I had 2 conversations that changed how I see software. 1/ A pool service operator built a chemical dosing calculator and route planner. He asked his software company for these features for years... they kept saying no. So he built it himself. 2/ A scaffolding rental company owner built an inventory and scheduling platform tracking every piece of equipment across every job site. He was losing $40K/year in missing frames, and nobody could tell him where anything was. Now he knows where every piece is, who has it, and when it's coming back... and it's all integrated into his CRM. The blue collar builder era is here. 👷

The most productive people I know don't have fancy workflows. They have a bias for action.

Want to make AI useful? Force it to do ONE thing that saves you time, then move on. Resist the urge to keep optimizing.