My Playbook for Building a Recruiting Machine

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.

Match Selling with Anti-Selling

Every engineer at Tenex 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 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

Find Undervalued Talent

We intentionally avoid recruiting from the obvious suspects like FAANG and high-growth startups known for their engineering talent.

Instead, we identify undervalued hubs of talent. Examples: founding engineer, failing startups, non-FAANG combined with side hustles, product hunt, indie hackers, claude code community.

Optimize Interview Time

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?

Here’s our process if helpful:

• Intake interview
• First round interview
• Technical take home
• Systems design interview
• Final round interview

Open-Source Recruiting

We invite every single person on earth to recruit for us. If you refer a candidate and they get hired plus 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.

Invest in Talent

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.

AI-Native Approach

We take an AI-native approach to recruiting. This is one of the high ROI AI use cases I’ve found in building our business.

• We use Juicebox for sourcing talent
• We use Lovable to build a talent FAQ site
• We use Anthropic to build up a list of talent prospects across hubs like product hunt, indie hackers, etc.
• We use Anthropic to help us more effectively filter tons of apps through our ATS (Ashby)

These tools have changed what I have learned building in AI and how we approach scaling our team.

Key Takeaways

Building a recruiting machine comes down to six principles: match selling with anti-selling, identify undervalued talent hubs, optimize your interview process for time, open-source your recruiting, invest in worldclass recruiting talent, and take an AI-native approach.

If you want to hyperscale while keeping talent density high, you need a systematic playbook that covers as much ground as possible.

If you have any questions about our recruiting strategy, reply below. If you want to be an engineer at Tenex, make sure to apply. And if you want to refer a candidate, tell them to apply and mention you in their first round interview.