CJ Hess

I’m saying fuck it. There’s not enough time to scale my recruiting team so I’m making everyone on earth a recruiter. I have to hire 120+ people at @tenex_labs by year-end. - 70 AI engineers - 35 AI strategists - 15 other roles If you have a strong network, what I’m offering you the opportunity to make $100,000 as a side hustle. If: - You refer a candidate (form below) - Candidate applies for role - We hire them - They stay 90 days We pay you $10,000…per hire. I want to make this huge. Plans for the future: Referrer website with any info you need about Tenex/our roles. Leaderboard of our referrers. Top referrer gets sent on a baller vacation. Time to roll out the red carpet. All the info you need below…

We truly have the most cracked AI engineers in the world. They are all VERY opinionated about their tech stacks, which change constantly. Here's the current stack for one of our engineers: 1) Typescript - everything eventually becomes JavaScript, and you can basically build everything with typescript. Types are good for agents. 2) Ruby on Rails - RoR curious because it's very structured, which is really good for agents (@dhh) 3) Ghostty - nice terminal, native pane splitting, big context copy and pasting (cc: @mitchellh) 4) @cursor_ai - agnostic harness to switch between models 5) Codex CLI - daily driver / the Mac app was cool for a week but CLI is more functional (cc: @OpenAI) / pro: high quality code / con: trips over its own feet, too literal 6) Claude Code - use when need something to just happen. pro: will get you a result quick / con: sometimes it’s messy (cc: @AnthropicAI) 7) @WisprFlow - work way faster yapping to text, especially when WFH 8) @raycast - better spotlight with 9) @openclaw - place to keep structured data, stay organized, handle certain tasks 10) @vercel - super smooth for hosting, prototypes 11) @neondatabase - really easy to integrate with a vercel project + preview deployments are great for agent to raise a PR & test in-browser P.S. if you think you're a cracked AI engineer & want to surround yourself with the best & brightest, we're hiring at @tenex_labs.

I'm having one of my big brained engineers show me how to set up @openclaw safely & securely tomorrow. What burning questions do you want answered? Will post as a video next week.

I'm having one of my big brained engineers show me how to set up @openclaw safely & securely tomorrow. What burning questions do you want answered? Will post as a video next week.

Recruiting is painful. It's especially painful when you need to hyperscale your business. I'm currently feeling this pain big time. I have to hire 15 engineers in the next 37 days, while keeping talent density high. Not sure if it will be possible, but here's my playbook for building a recruiting machine: 1) We match selling with anti-selling Every engineer at @tenex_labs gets two spiels: Why you should work here: - You get paid like a salesperson (uncapped variable upside) - You are forced to operate on the frontier of AI - You get immense diversity in the software you build from deep ML systems to vertical-specific agents to full-stack applications Why you shouldn't work here: - You will work a lot (not because we care about facetime, but because there's a shit ton to do) - You have to be willing to bet on yourself, because that's how your comp is structured - You have to be okay working on a portfolio of projects vs. all your energy on one product 2) We identify undervalued hubs of talent We intentionally avoid recruiting from the obvious suspects like FAANG + high-growth startups known for their engineering talent. We focus all of our energy recruiting from underrated talent pools that match the ideal candidate (entrepreneurial, end-to-end systems experience, AI-pilled) profile. Examples: founding engineer, failing startups, non-FAANG combined w/ side hustles, product hunt, indie hackers, claude code community 3) We optimize the interview process for return-on-time-spent Many interview processes are unnecessarily long. We build our process around one question: how can we know whether you're the right fit in as close to 0 minutes as possible? This is arguably the most important step in the system to make sure we're maintaining insane recruiting velocity. Here's our process if helpful: 1) Intake interview 2) First round interview 3) Technical take home 4) Systems design interview 5) Final round interview 4) We open-sourcing recruiting We invite every single person on earth to recruit for us. If you refer a candidate & they get hired + stay for 90 days, you make $5,000. I've watched people make a living off of this arrangement. Turning our recruiting engine into a social network is how we cover as much ground as humanly possible. 5) We put our money where our mouth is We only have 1 executive in our business right now. And that person ran talent acquisition at a company that was hiring 1,000 engineers per year. If you want to build a worldclass recruiting engine, you need to be willing to pay up for worldclass recruiting talent. 6) We take an AI-native approach to recruiting We use @juicebox_work for sourcing talent. We use @Lovable to build a talent FAQ site. We use @claudeai to build up a list of talent prospects across hubs like product hunt, indie hackers, etc. We use @claudeai to help us more effectively filter tons of apps through our ATS (@ashbyhq) P.S. if you have any questions about our recruiting strategy, reply below. happy to help. P.P.S. if you want to be an engineer at @tenex_labs make sure to apply. P.P.P.S if you want to refer a candidate make sure to tell them to apply and then mention you in their first round interview.

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I can’t hire fast enough. There is virtually unlimited demand to help midsized and enterprise businesses execute AI transformation successfully. And @tenex_labs is becoming the McKinsey of AI, leading the charge. We need killer engineers: full-stack, AI-pilled coding workflows, uncapped cash upside based on output And we need killer strategists: technically dangerous (at minimum), exceptional at strategic relationship building, strong product sense. Link to learn more below…