How to choose an AI tool in 10 minutes (and stop collecting subscriptions)

There are thousands of AI tools and a new wave every week. Most people respond in one of two ways: they try nothing, or they try everything and end up paying for seven subscriptions they open twice a month. Neither works.

This is the process we use at ToolDuck when we evaluate a tool, cut down to what you need to make a good decision in about ten minutes.

Step 1: Start from the task, not the tool

Write one sentence: "I need to ___ faster." Edit a podcast. Answer customer emails. Turn meeting notes into a summary. Make a product image.

If you cannot write the sentence, you do not need a tool yet. You need to notice which part of your week is repetitive. The tools that stick are the ones that remove a specific chore, not the ones that promise to change how you work.

Our Tool Finder is organised this way for a reason: pick the task, see the tools ranked for it.

Step 2: Decide which of three kinds you need

Almost every AI tool is one of these:

1. A general assistant you talk to: Claude, ChatGPT, Gemini. Good at most things, best at writing, thinking and explaining.
2. A specialist built around one job: Fathom for meetings, Canva for design, Perplexity for research. Better than the generalist at that one job, useless outside it.
3. An automation or agent that does the work without you watching: Zapier, Lindy, Claude Code. Highest payoff, highest setup cost.

Most people should own one of the first kind, one or two of the second, and add the third only once a process is stable enough to automate.

Step 3: Shortlist two, not ten

For any task, there are usually two or three tools that are clearly ahead. Our comparisons name them; so will any honest colleague who uses them daily. Pick two. Ten tabs of free trials is how you end up choosing none.

Step 4: Run the same real job through both

Not the demo prompt. The real thing: last week's meeting, this month's newsletter, the actual photo of your product. Spend fifteen minutes with each. You are checking three things:

• Did it do the job, or something adjacent to the job?
• How much did you have to fix? Count the edits. This number matters more than any benchmark.
• Did it fit how you already work? A better tool that lives in the wrong place loses to a slightly worse one in the right place.

Step 5: Check the two things people skip

Data. Where do your inputs go, are they used for training, and can you delete them? For personal use this is a preference. For client or company data it is a requirement. Paid business plans are usually explicit; free tiers often are not.

Lock-in. Can you export what you make? If the tool disappeared tomorrow, what would you lose? Prefer tools that store things in formats you can take with you.

Step 6: Commit for a month

Pick one. Cancel the other. Use it every day for a month, including the days it annoys you. Tools reveal themselves around week three, when the novelty is gone and only the usefulness is left.

If after a month it has not removed the chore from step 1, switch. If it has, stop looking. The best new AI tool for you is the one that lets you forget about AI tools.

The checklist

Copy this into your notes:

• [ ] One sentence: "I need to ___ faster."
• [ ] Which kind: assistant, specialist or automation?
• [ ] Two candidates, named.
• [ ] Same real job through both. Count the edits.
• [ ] Data policy read. Export possible.
• [ ] One chosen. One cancelled. Calendar reminder in 30 days.

When to break the rules

Two exceptions. If you are a developer, run more experiments; the tools change fastest in coding and the payoff from the right one is largest. And if your whole team will use the tool, add a step: let three different people run step 4. The tool that wins with all three is the one that will survive rollout.

Everything else, keep simple. Fewer tools, used properly, beat a drawer full of subscriptions every time.