⚙ Hi {{first_name_tally|Operator}},

Confession: your inbox probably sucks. Mine too. It runs your day, interrupts your focus, and still somehow lets the important stuff slip through. Well… I wanna learn more.

This week I’ve been hopping on short discovery calls with people from the waitlist. We’ve already got a few lined up this week, and I just want one more person to round it out.

It’s 30 minutes, we’ll talk about how you handle email today, and I’ll show you what we’re building to see if it actually helps.

We’re only running these calls this week. First come, first served.

Book a time here: Calendly Link

- Rameel

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My wife is designing a custom home, and she's obsessed. (I don’t know why cause we aren’t buying a new home anytime soon).

She sends me YouTube videos constantly—mostly about finishes and layouts I'll never remember. But one video stuck.

It was about staircase design mistakes. 

The guy rattled off five blunders: ignoring building codes, inconsistent riser heights, poor lighting, slippery materials, wasted space underneath. I was halfway tuned out until he said this:

I didn't realize how many guidelines went into stairs—riser height, tread depth, handrail strength, ballister spacing. But it makes sense. By baking rules into the system, you encourage safe behavior without thinking about it.

The geometry does the work. You don't need signs that say "walk carefully." You design stairs people can't fall down.

Remote companies assume people will fail without constant watching.

Instead of building systems that force good behavior, they built systems that watch for failure. Seventy-eight percent now monitor keystrokes, screenshots, and activity logs—spending $240 per employee per year to prove they don't trust their own teams. 

Building better stairs starts with better hiring. 

Matt Mullenweg doesn't interview candidates. He tests them.

Automattic (the company behind WordPress.com) runs every hire through a 30-day paid trial where you're assigned real work—production code, actual projects, live collaboration—and judged on one metric: did you ship?

No one checks your hours or monitors activity. Most don't make it through. Some can't handle async communication. Others freeze without direct supervision. A few realize they need an office. But the ones who make it through? They stay. Automattic's regretted attrition sits under 5%, a third of the industry average.

The trial is the forcing function. This process filters for self-management before the first paycheck clears, which means the people who survive don't need surveillance—they've already proven they can handle autonomy.

The result for Matt is 2,000 people across 95 countries, no offices, no surveillance software, and attrition rates that make traditional HR departments question their entire retention playbook.

The hiring filter is the first forcing function. Get this wrong and everything downstream breaks. Get it right and surveillance becomes unnecessary.

The resistance comes from inertia and fear dressed up as pragmatism.

All three objections miss the point.

A bad hire costs 1–2x their annual salary when you account for recruiting, onboarding, lost productivity, and team disruption. At $180K comp, one bad hire runs you $180K–$360K. The trial costs $15K—less than a tenth of the downside. And if cash flow is the concern, structure it as deferred compensation.

Pay a reduced rate during the trial, then true-up to full salary once they convert. The best candidates don't blink at this because they know they'll ship.

The IP concern is even easier to solve. Scope the trial carefully. Give candidates real work, but not your most sensitive codebase or strategic roadmap. Automattic assigns production work to trial candidates without handing them the keys to everything.

A sandbox environment or lower-risk project still tests their core skills. And here's the thing: if you can't trust someone with real work for 30 days, you can't trust them full-time. The trial surfaces this risk early instead of six months in when they've already seen everything.

The speed objection reveals the real problem. Your hiring process is slow because you're doing 4–6 interview rounds trying to predict performance through conversation. The trial replaces prediction with observation.

You'll know in 30 days whether someone can ship, collaborate async, and self-manage—information that no amount of behavioral interviews can give you.

Automattic's trial might add calendar time, but it collapses decision time. Did they ship or didn't they? The answer is yes or no.

The companies that avoid the trial aren't protecting their business. They're protecting a broken hiring process that optimizes for credential signaling over actual performance. The trial exposes that.

Step 1: Pick One Role (Maybe Engineering?)

Choose a role where output is measurable and the work can be scoped into a 30-day project. Engineering, design, and writing roles work well. Sales or customer success roles are trickier but not impossible—you can have candidates shadow calls, draft proposals, or run mock demos.

Step 2: Design a Real Project, Not a Test

The project needs to be:

Bad example: "Help us build a new feature." Good example: "Fix these three bugs in our codebase and ship one small UI improvement."

The project should require collaboration with the team (Slack, standups, code reviews) so you can assess async communication and cultural fit alongside technical ability.

Step 3: Set Expectations Up Front

Be clear: this isn't an extended interview where you're looking for reasons to say no. It's a mutual test—they're evaluating you as much as you're evaluating them.

Set expectations:

Automattic is explicit: if you ship, you're in. If you don't, you're paid for your time. Move on.

Step 4: Track Conversion and Retention

Track two metrics:

If your conversion rate is above 80%, you're not filtering hard enough. If it's below 50%, your trial project might be poorly scoped or you're screening the wrong candidates upfront.

If your 12-month retention rate for trial hires is significantly higher than your retention rate for traditional hires, the trial is working.

Surveillance doesn't just cost money, but trust.

The best people leave first. They're the ones with options, and they won't stay at a company that treats them like children. The ones who stay learn to game the metrics like: 

You end up measuring activity instead of output. And activity is the wrong proxy.

The 30-day trial solves this at the root. If someone can't self-manage for 30 days, they won't self-manage for 30 months. If they need surveillance to stay productive, they shouldn't be hired. The trial surfaces this before you've invested in onboarding, benefits, and team integration.

Automattic doesn't need surveillance software because they filtered for people who don't need it. That's the forcing function. That's the architecture.

The companies that stopped watching their teams didn't stop caring. They started hiring better. They built systems that made surveillance unnecessary—not by monitoring harder, but by testing smarter.

Surveillance doesn't scale. Hiring does.

Design better stairs. Start with who gets to climb them.