jer

5 of 10 teams at demo day broke $10M annualized HF0 is not just for early stage companies Interviews started yesterday.

Anthropic is building a secure OpenClaw. Four features in 30 days, each one reverse-engineered from the open-source agent that hit 250K GitHub stars and 40,000 exposed machines. The feature mapping is surgical: OpenClaw: text agent from WhatsApp, it works on your desktop. Anthropic: Dispatch (March 17). Persistent thread from phone to desktop. OpenClaw: Discord and Telegram as control surfaces. Anthropic: Claude Code Channels (March 20). MCP bridge to both. OpenClaw: full OS access, browser control, app manipulation. Anthropic: computer use in Cowork and Claude Code (today). OpenClaw: 100+ community skills, no review process. Anthropic: curated plugin marketplace with enterprise admin controls. OpenClaw: heartbeat daemon, always-on 24/7. Anthropic: desktop must stay open. Intentional friction. Runaway prevention. The strategy is legible: let open source take the arrows, ship the enterprise-safe version before anyone else can. OpenClaw proved 250K developers want to text an AI that controls their computer. OpenClaw also proved that desire produces one-click RCEs, CrowdStrike threat advisories, agents creating dating profiles nobody asked for, inbox deletions during “automated cleanup,” and 20% malware rates in skill ecosystems. Anthropic studied every failure mode and built the inverse. Connectors before computer use. Permission prompts before every action. Sandboxed execution. Every constraint maps to a compliance checkbox. Gaps remain. Dispatch requires Anthropic’s own mobile app. OpenClaw works in WhatsApp and iMessage, apps 3 billion people already use. No native messaging integration yet. Cowork needs your Mac awake with Claude Desktop running. No headless mode, no background daemon, no proactive monitoring where the agent messages you first. The “always-on coworker” positioning still requires you to be mostly-on yourself. Here’s where it gets interesting. Steinberger built OpenClaw entirely on OpenAI’s Codex. Said his productivity doubled. Publicly called Claude Opus the best general-purpose agent while building the biggest agent project in history on a competitor’s coding tool. Joined OpenAI February 14. Altman posted he’d “drive the next generation of personal agents” and it would “quickly become core to our product offerings.” Five weeks of “quickly”: GPT-5.4 with strong benchmarks. ChatGPT agent mode in a cloud sandbox. And a March 20 “code red” meeting where leadership concluded product fragmentation was losing them the race to Anthropic’s unified tools. The plan: merge ChatGPT, Codex, and Atlas into one superapp. The core loop Steinberger proved, text from phone, agent works on your machine, you return to finished output, doesn’t exist in any OpenAI product. Their agent runs in an isolated cloud browser. No local files. No persistent desktop control. No async handoff. The person who built the most successful personal agent in history is inside OpenAI. The product that reflects his insight isn’t. Anthropic sent trademark lawyers, then shipped the product. OpenAI sent an offer letter, then called a reorg. The agent race rewards shipping velocity over hiring velocity. One company is converting the OpenClaw demand signal into product. The other is converting it into org charts.

i can't believe nobody caught this. Anthropic's entire growth marketing team was just ONE PERSON (for 10 months, confirmed) a single non-technical person ran paid search, paid social, app stores, email marketing, and SEO for the $380B company behind claude here's exactly how one human is doing the job of a full marketing team: it starts with a CSV. 1. he exports all his existing ads from his ad platforms along with their performance metrics (click-through rates, conversions, spend, etc) 2. feeds the whole file into claude code 3. and tells it to find what's underperforming. claude analyzes the data, flags the weak ads, and generates new copy variations on the spot this is where he gets clever: he then splits the work into 2 specialized sub-agents: 1. one that only writes headlines (capped at 30 characters) 2. and one that only writes descriptions (capped at 90 characters). each agent is tuned to its specific constraint so the quality is way higher than cramming both into a single prompt so now he's got hundreds of fresh headlines and descriptions. but that's just the text. he still needs the actual visual ad creative, the images and banners that go on facebook, google, etc. so he built a figma plugin that: 1. takes all those new headlines and descriptions 2. finds the ad templates in his figma files 3. and automatically swaps the copy into each one. up to 100 ready-to-publish ad variations generated at half a second per batch. what used to take hours of duplicating frames and copy-pasting text by hand so now the ads are live. the next question is which ones are actually working. for that he built an MCP server (basically a custom integration that lets claude talk directly to external tools) connected to the meta ads API. so he can ask claude things like: • "which ads had the best conversion rate this week" • or "where am i wasting spend" and get real answers from live campaign data without ever opening the meta ads dashboard and the part that ties it all together and closes the loop: he set up a memory system that logs every hypothesis and experiment result across ad iterations. so when he goes back to step one and generates the next batch of variations... claude automatically pulls in what worked and what didn't from all previous rounds. the system literally gets smarter every cycle. that kind of systematic experimentation across hundreds of ads would normally need a dedicated analytics person just to track the numbers from the doc: ad creation went from 2 hours to 15 minutes. 10x more creative output. and he's now testing more variations across more channels than most full marketing teams a $380 billion company. and their entire growth marketing operation (not GTM) = just one person and claude code lol truly unbelievable