❓ Problem

Keeping up with AI tools has quietly become a part-time job nobody applied for. There's An AI For That now tracks roughly 47,400 publicly listed tools, and the number goes up every day. You find one that works, spend a weekend learning it, and by Tuesday someone on X is calling your whole workflow prehistoric.

Even the people who live in this stuff are lost. When Ole Lehmann asked which tool is best for creating animations through MCP, it wasn't a beginner's question. It was a very online AI power user admitting that nobody really knows.

And the advice out there is compromised. Most AI tool affiliate programs pay 20-40% recurring commission, so the average "Top 10 AI Tools" listicle is often a ranking of payouts, not performance. Was the tool actually tested? On what task? Would it still be number one without the commission?

Guessing wrong is expensive. 58% of US buyers regret at least one software purchase from the previous 12-18 months, and among regretful retail buyers, 88% were likely to buy based on vendor information alone. The problem isn't a lack of options. It's a lack of anyone doing honest homework.

✅ Solution

An independent testing lab for AI tools. Think Wirecutter for your AI stack, with receipts.

• Same brief, every tool. Competing products get identical real-world tasks: animate a product launch, clean and analyse a messy spreadsheet, build a landing page, summarise a 90-minute sales call.
• Receipts, not vibes. Every test publishes the actual outputs side by side, plus the cost, time taken, and how many human fixes it needed before it was usable.
• Winners by task, budget and experience level. "Best for a solo marketer on $50 a month" is a very different answer from "best for a 20-person design team", and the rankings reflect that.
• Every result is dated. A March test is labelled as a March test, and re-run when a major version ships.
• Save your stack, get switching alerts. Tell it what you use today and it stays quiet until a rival beats your tool by enough to justify the pain of switching.

The rule that makes the whole thing work: buyers fund the research, vendors can't buy a better ranking.

📊 Key Numbers

Market size

• AI is now a line item for most businesses. Business AI adoption on Ramp passed 50% for the first time in March 2026, up from 35% a year earlier.
• The heavy spenders are spending properly. In July, the top 1% of businesses spent a median $7,400 per employeeon AI, with the top 10% at $650. Those are the teams who will pay for a proper bake-off.
• Demand for discovery is already proven, with TAAFT used by more than 5 million people every month.