Hope everyone's Easter weekend was smooth! With our first 100 members growing steadily, I've put extra gears into getting this community to be stronger than an ever-growing part time construction site. Expect over the next few weeks to see a lot more video and classroom content produced by yours truly. There's a whole field adjacent to the OpenClaw world that amplifies with new frontier AI novelties. For instance, cross-LLM accuracy. What if that was an automatic, 24/7 engine that you didn't even to battle across your agentic setups? So you’ve talked to Perplexity to fact check what GPT told you, and then you had Claude prep a presentation mimicking Gemini's format, you slap assets across LLMs thinking it's improving. This accuracy feels like a band-aid on a bigger hole, Cognee.ai bridges all of that with 3 core API requests for free: Ingesting, chunking, and organizing. Footnote: I'm not affiliated with Cognee.ai , it's an open source project available for free By wiring this simple string of automated knowledge work, capabilities are night and day. With a few commands, you can unify your knowledge base across multiple LLMs, and get the 80/20 benefits of RAG when that body of work grows substantially. At what point does a speck of sand become a hill? Join us this Saturday as we dive deeper into the business angles of this, along with another video on how to use OpenClaw for a strangers business (hint, it's not too different from industry-grade AI scoping!)

Becoming a compendium around OpenClaw has a few realities around it. 1) It allows this community to function as the gateway into how to use AI more meaningfully in your business and day to day life. Subconsciously, dissecting the preambles of specialists that have been in this space for years, you see what's distilled and worked. 2) The wiki and docs are good for technical people, not the mass public of people that are picking it up for the first time. There's a continued wave of people that have tried and failed, through no fault or complete ignorance of their own. It takes a community, a village, to introduce real time problem solving approaches that allow for innovation. OpenClaw's architecture isn't going away, this isn't just another project. It's the basis for the future of AI engaging with humanity through living markdown files, which is the new standard of juice squeezed from AI to realize what's possible. It's what Codex does so well, it's what GPT 5.4 crushes at, it understands you relative to the context of the problem you're trying to solve. Your persistence won't just reward you in these coming 6 months, but for the years ahead. You will become familiar with practices around AI implementation that are missing from the mass commons, that without, we see continued repetition of failure for over 95% enterprise projects. Working in enterprise sales and AI implementation 9-9 myself, I see the sycophantic worries and anti-AI sentiment clouding with doubt day by day, yet, played out over time, AI that understands what's encompassing you will grow in dimension. AI that knows what "healthy" looks like for you. What "happy" looks like for you. Which will fundamentally change our relationship with any tech that follows! Join us Saturday 12-2PM EST for live Q&A's

Let’s be honest: the default job hunt turns smart people into ticket-writers. It feels like a hamster wheel, and depending your CV-to-market fit, it might be. You sit there feeding the machine: copy-paste your resume, tweak the same cover letter for the 43rd time, fill in the same “What excites you about this role?” box until your brain is soup. Two hours disappear and you’ve applied to… maybe three roles. And worse? You have no real system. Just tabs, vibes, and a vague hope that “something hits.” What I want you to do is flip that. Instead of being the cog, you treat the job hunt itself as your first live automation project. A citizen-developer project. A workforce-readiness asset. Recognize that by not doing this, you leave it to your competitors to do so. You’re not just “looking for a job.” You’re building a Job Search Agent that works with you (Template below) Step 1: Build a Job Search Recipe (So You Stop Spraying and Praying) Most people start with “Indeed… search… scroll.” You’re going to start with a recipe: Role keywords: e.g., “junior data analyst,” “coordinator,” “implementation specialist,” “Salesforce admin,” “learning designer.” Locations: remote, hybrid, specific cities, visa-friendly locations if that matters for you. Salary ranges: your realistic floor + your stretch. Filters: visa sponsorship, early-career roles, specific tools (Salesforce, HubSpot, Figma, Python, n8n, etc.). Nothing fancy yet. This can literally live in a Google Doc or Notion page called: Job Search Recipe – v1 The point: you’re telling your future agent exactly what “good” looks like. You’re thinking like a system designer, not a desperate applicant. If you're struggling with creating this, feed your CV into GPT and ask it to. Step 2: Build a Simple Tracker (Your Pipeline, Not Just “Applied”) If your job search lives in your inbox, you’ve already lost. Make a very dumb, very powerful tracker. Sheet, Notion, Airtable – doesn’t matter. Columns like: Job title

https://www.perplexity.ai/join/p/paypal-subscription Enjoy!

https://www.notion.so/The-Ultimate-GTM-Automation-Setup-Guide-28d1b3ef40be80a4879cfc9ade400047 Product of https://gtmengineer.dev/ Takes you from zero to 80% of the way of using Claude Code, bypassing a lot n8n and actual troubleshooting stresses Enjoy!