Why Fyxer Refused to Launch Until Their AI Could Beat 10 Human Assistants

The Insight

Most AI products launch when the technology is "good enough." Fyxer AI launched when their AI could beat 10 human executive assistants at inbox organization in a head-to-head accuracy test.

Richard Hollingsworth didn't guess whether the product was ready. He set a measurable bar: the AI had to outperform the humans who'd been doing this work for years. Only then did it ship.

This matters because "good enough" AI products struggle with retention. If your AI is worse than what a human can do, customers try it, get disappointed, and leave. Fyxer's approach meant customers experienced a product that was better than the alternative from day one. The result: 90% of paying customers still active after three months.

The decision rule: don't launch your AI product until you can prove it beats the human alternative at the specific workflow you're targeting.

How They Did It

1. Started with one workflow, not a platform. Their first feature was organizing inboxes into folders. A single, logic-based task that people were already paying $60 an hour for through their agency. They didn't try to build a general-purpose AI assistant. They picked the workflow with the clearest demand signal.

1. Documented the human process first. They asked their agency's assistants exactly how they organized inboxes for clients. Step by step. Then they built the AI to mimic that exact workflow. No guessing about what the process should be. They had hundreds of assistants who'd been doing it for years.

1. Used humans to train the AI. The assistants didn't just demonstrate the workflow. They actively trained the AI by correcting its outputs and feeding accuracy data back into the model. The humans became the quality control layer.

1. Set a clear launch threshold. They pitted 10 assistants against the AI on the same inbox organization tasks. The product only shipped when the AI consistently beat the humans in accuracy. Not matched them. Beat them.

What Trips Up Founders

Launching on vibes. Most founders launch when it "feels ready" or when they run out of patience. Without a measurable benchmark, you're guessing. And if the product isn't better than the alternative, you'll spend months trying to fix retention instead of growing.

Testing against the wrong benchmark. Comparing your AI to no solution at all is misleading. Customers aren't choosing between your product and nothing. They're choosing between your product and however they currently solve the problem (a human, a spreadsheet, doing it manually). Beat that specific alternative.

Trying to launch everything at once. Fyxer could have built AI for scheduling, email drafting, and inbox management all at launch. Instead they picked one workflow and made it undeniably better. Breadth kills accuracy in early-stage AI products.

When This Doesn't Work

If you're in a market where no human equivalent exists, you can't benchmark against humans. In that case, you need a different quality bar (maybe user satisfaction scores or task completion rates).

This also doesn't work if speed to market genuinely matters more than accuracy. Some AI products win by being first, not best. But if your product replaces expensive human work, accuracy is everything.

The Question

Before you launch, ask yourself: can I put my AI in a blind test against the current solution and prove it wins? If you can't run that test, you probably don't understand the workflow well enough yet. Go spend more time watching humans do it.