How to Choose AI Tools Without Regret: The 2 Methods I Use to Decide Whether to Pay

TL;DR: There is no best AI tool, only the tool that fits where you are right now. When a new tool comes out, wait a bit and compare what people say. When you do want to use one, test it on your own real work, giving several tools the same prompt. If you pay, pay monthly, then look at how many times you actually used it this month and whether it produced real value before you renew or cancel. I do not pay annually.

At talks I am often asked: "Which AI tools do you use? Any recommendations? Should I pay for them?"

I have been asked these questions so many times that I decided to write this up: how I choose AI tools, and how I decide whether to pay.

The short answer: there is no "best" AI tool, only the AI tool that fits you best. And the way to find it is to test it yourself.

My mistake: the same $200 plan, wasted once and worth it once

Let me start with my own story. In 2025 I subscribed to Claude's $200-a-month plan (Max 20x). I had read lots of engineers saying how strong Claude was and how good it was at coding, so I signed up.

Then I realized I did not know how to use it or what to use it for. If you only ask it questions, the experience is not that impressive, and the models back then were not as smart as they are now. Most importantly, I have no engineering background, so using it felt clumsy. I used it a few times and then left it alone. That $200 was wasted.

In March 2026, while writing my newsletter, I was on the same $200 plan again, and this time it felt cheap and well worth it. In less than a year, both Claude and I had changed:

1. Claude could do much more. It could use Skills (fixed instructions written for the AI to follow), operate a computer, and connect to MCP (the standard way to link AI to outside services) and APIs (interfaces that let different software talk to each other). It was no longer just about writing code.
2. The ecosystem had matured. Lots of people were sharing how they used it, and there were tutorials everywhere.
3. I had grown too. I had kept doing vibe coding (asking AI to write code through conversation) and exploring different AI uses, so I knew a lot more and knew how to get good results from AI.

Sometimes it really is a question of timing. Either I was not ready for the tool, or the tool was not right for me, and that is why it felt like a waste.

If you are new to AI, I do not recommend jumping straight to a $200-a-month plan. Unless you already have relevant background, or you have decided to put serious time into learning, you will probably end up as frustrated as I was, wondering why it is not as good as everyone says. That is because a lot of the basics are not in place yet:

• You want Claude Code (Anthropic's AI coding tool) to run a complex workflow, but you have never heard of MCP, APIs, or Skills.
• You want the AI to write in your voice, but you have never collected your own writing for it to learn from, so of course the output reads like AI.

You get the most out of a tool when your own experience and growth meet the right tool.

This section is adapted from my CreatorHome newsletter issue #043, published on 2026-03-31.

What I have learned: heavy users can test early, most people should wait and watch

I have a few takeaways from using AI tools, and they depend on who you are.

I am a heavy user and I am willing to spend money, so I am comfortable testing tools as soon as they come out. If that is not you, I suggest waiting a little first.

AI changes very fast right now, and so does the information about it. Waiting gives you time to see two things:

• What the tool is good at. When a tool first launches, people are still figuring out where it is strong and where it is weak.
• What people actually get out of it. Give it a while, and people will use it on real work and share what they made.

While you wait, keep two things in mind:

1. Look at several sources and compare. Some people exaggerate, and if you only follow one person's review it is easy to get carried along.
2. Do not buy a tool for one small feature. It may only be good at that one thing, and you may never use the rest.

Once you have watched for a while and you really have a need, test it yourself with the process below.

The big picture: how I choose AI tools

Think of it as a series of gates. A tool has to pass each one before moving on, and fewer tools make it through each round:

1. I can name the specific job I want the tool for.
2. It did the best job when I tested the same task on several tools.
3. The free version is not enough, so I pay monthly for one month.
4. I used it 4 or more times in that month, so I renew.
5. It keeps producing value, so I keep paying monthly, and I can switch at any time.

The whole process follows one rule: judge every step with your own real work, not other people's results. Here is each step in detail.

Before you start

• Write down the one job that hurts most. Figure out what eats up most of your day, then look for a tool for it. Do not pick a tool because it is popular and then go looking for a use.
• Prepare one or two real tasks. Choose work you actually have coming up, such as a blog cover image or a meeting recording you need to clean up.
• Open the official pricing page. Check what the free version can do, whether there is a trial, what the paid plan adds (models, usage limits, features), and whether you can pay monthly.
• Prepare test material with nothing confidential in it. Do not test with client data or unreleased projects yet. I explain why under "Limits and cautions."

Take Typeless's pricing page as an example. Look at three things: how much the free version is limited, what Pro adds, and what the monthly price really is (I checked typeless.com/pricing on 2026-10-12).

Method one: test several tools with the same real task

This is the most important part. You have to try different tools to find out which ones are actually good and right for you.

You can of course look at other people's recommendations, but I strongly suggest testing them yourself before you decide. A tool someone else loves may suit their workflow or use case, not yours. Or you see someone getting great results, but you have no need for it at all. If you pay anyway, you may not even know how to use it, and that is a waste.

Step 1: Pick a job you actually need to do

This works the same for text AI like ChatGPT and for image generators. For image generation, I use a task I really need done, for example:

Make a cover image for a blog post in a flat illustration style.

After this step you have one fixed prompt (the text instruction you give the AI), and you will use it for every tool.

Step 2: Give the same prompt to every tool

Paste the exact same prompt into each tool, and do not rewrite it for any one of them along the way. Generative AI gives different results each time, so run each tool at least twice. Judging from a single run is easy to get wrong.

For that cover image, I tested Midjourney, DALL-E, and Google Gemini at the time. That list is now out of date; see case two below.

After this step you have at least two results from each tool, side by side.

Step 3: Compare with the same yardstick

My rule is simple: whichever result is closest to the style I want, that is the tool I use. When comparing, note three things:

• How close the result is to what you wanted.
• How many rounds of edits it takes before you can use it.
• How much time it takes in total, including waiting and editing.

After this step you know which tool fits this job best. If they all look about the same, test again with a harder task.

Do not fully trust demo videos

This one matters a lot. Many demo videos are curated. Weak results are left out, or the example happens to be one the tool handles especially well. That makes you think it will work just as well on your own work, and it may not. So test it yourself, with tasks you will actually do.

A mistake I made: I saw an impressive demo of an AI photo retouching tool and paid for it. Then I found that the demo showed exactly the kind of image it was best at, and the photos I actually needed to fix came out much worse.

Be extra careful with newly launched tools. Some demos look great, but in reality:

• There are few useful, real examples, and no tutorials.
• Neither users nor the company share any resources.
• It looks impressive but is not that good in actual use.

If you are new, start with mature tools

So I suggest starting with tools you can understand and that are already mature, such as Claude Code. Lots of people use it, and there are plenty of resources and shared use cases, which makes it friendlier for beginners.

You do not need to chase the newest thing. Learning a tool with a mature ecosystem and plenty of resources is the better choice.

Method two: before you commit, pay for one month

Many AI tools only show what they can really do once you subscribe.

If you stay on the free version, you often hit limits or feel it is not that good. That may not be the tool's fault; you just have not let it work at full strength. So if you want to know whether an AI tool is really good, and whether it actually makes you more productive, it is worth subscribing for one month.

Before you pay, check the official pricing page and make sure the paid plan adds exactly what is holding you back, such as a stronger model, higher limits, or a specific feature. If the free version already does the job, do not pay yet.

Some tools have no free trial. For example, Midjourney's help center says its website does not currently offer one. In that case, pay monthly for the cheapest plan and test it for a month.

My two principles for deciding whether to buy

1. Production value. If it brings direct value to your work, or saves you a lot of time and makes a real difference, it is worth the money, because that is an investment with a return.
2. How you pay. I strongly recommend paying monthly. Never pay for a year up front. I explain why below.

How to measure production value: think in hourly wages

A subscription may not feel cheap, but look at it another way: if you hired someone to do this work for you, one day of their pay could cost more than a month of the subscription.

Taiwan's 2026 minimum wage is NT$196 an hour, so eight hours of help costs NT$1,568, already more than a plan around $20 a month. A $200-a-month plan is a different story. It only pays off if you really use it every day.

For a more accurate number, follow these four steps:

1. Estimate how much time it saves in a month. For example, 30 minutes a workday over 20 workdays is 10 hours.
2. Subtract the time spent on setup, checking, and retries.
3. Multiply the net hours saved by what you think an hour of your time is worth.
4. Compare that with the total of the subscription, add-ons, and API fees.

This is a way to calculate, not a guaranteed return.

Do not decide whether to use a tool based on whether it is cheap or free. Ask whether it solves a problem or creates more value for you. That is what matters most.

Why I only pay monthly, never annually

AI tools change too fast. I have seen too many tools get replaced within a few months, and I may need to switch at any time. If I paid for a year and a better tool came out, I would hesitate over whether to switch. If I only pay for a month, I can just switch next month with no guilt.

Monthly billing costs a bit more, but it means every month you are using the newest and strongest tool available.

Watch out on pricing pages, too. On some of them, the big number is the annual price divided by twelve. Typeless, mentioned above, is one example: Pro shows $12 a month, but that is the annual rate, and paying monthly costs $30. Before subscribing, check what the monthly price really is, then run the hourly-wage math above.

Is it a fit? Count how many times you used it this month

If you buy a tool, you should use it. If you rarely do, that is money wasted. Count how many times you used it in a month, and you will know whether to keep paying.

My rule: if I used it fewer than 4 times in a month (less than once a week), I cancel.

1. On the day you pay, set a calendar reminder a few days before the renewal date.
2. When the reminder pops up, count how many times you actually used the tool this month.
3. Fewer than 4 times, cancel. Four or more, run the hourly-wage math above to check that it is worth it.

You end up with a clear answer: renew or cancel. The 4-times threshold is my own personal standard.

AI tool evaluation checklist

Here is the checklist I use when choosing AI tools. Go through it once before you pay and again after a month:

Criterion	Question to ask yourself	Pass condition
Real need	Do I actually need this capability?	You can describe a concrete use, and it is not just for one small feature
Compare sources	Have I seen other people's real results?	You checked more than one source, not a single recommendation
Available resources	Are people sharing real examples and tutorials?	You can find tutorials, examples, or official resources
Hands-on testing	Have I tested it on my own work?	Same prompt tested across different tools
Alternatives	Is there a free or cheaper option?	What the paid plan adds is worth it
Usage frequency	How many times did I use it this month?	At least 4 times a month (once a week or more); otherwise cancel
Production value	Does it bring direct value or save me a lot of time?	Net time saved, converted to money, is more than the total cost
How you pay	Will this tool be replaced soon?	Monthly only, never annual, so you can switch at any time

My real selection cases

Case one: voice dictation tools

I tested macOS built-in dictation, Google voice typing, Wispr Flow, and Typeless, one after another.

I used the same "work task briefing" passage with each one and compared recognition accuracy, how they handled filler words, and the quality of the final text.

I chose Typeless because its smart cleanup produces text I can use almost without editing.

Case two: AI image generation

At the time I tested Midjourney, DALL-E, Google Gemini, and Adobe Firefly on two real needs: blog cover images and social media post illustrations. Each tool performed very differently depending on the type of image, and none of them won across the board.

My conclusion: use different tools for different needs. You do not have to stick to one.

That list needs updating now. OpenAI removed DALL-E 2 and DALL-E 3 from its API on May 12, 2026, and recommends newer models such as gpt-image-2 instead. The image model inside the Gemini app is now called Nano Banana.

For image cards and design work, I currently use Claude Opus 5.5. It is not an image generation model, so I mean making image cards and designs, not generating illustrations or photos. This is where things stand right now; which tool leads in the next stage is still open.

Case three: AI writing assistants

I use ChatGPT, Claude, and Gemini. I used to split the work: Claude for long-form writing, ChatGPT for code, Gemini for search.

These days I do not pick a writing tool very carefully anymore, because today's agents are all strong enough. The real work is training the agent to write like me.

The way to do that is to give it enough material, and even to start producing more content for it, not just to teach it how to write. This ties back to what I said earlier: if you have not built up your own writing, of course what the AI writes sounds like AI.

The point: agents are strong enough already. The difference is how much of yourself you give them.

Common sticking points and what to do

Situation	What to do
Every tool seems about the same	Your test task is too easy. Try again with the hardest, most time-consuming job you do
The free version does not show any difference	Check the official pricing page to see whether the paid plan adds a model, higher limits, or a feature. Pay for a month only if that is exactly where you are stuck
The same tool gives different results each time	That is normal for generative AI. Run each tool at least twice before comparing, and do not judge by the best run alone
Online reviews are split	Look at real results from several sources, not just one. Some reviews may be exaggerated
There is no free trial	Pay monthly for the cheapest plan and test it for a month. Do not pay annually
You are paying monthly but not using it	Set a reminder before the renewal date and cancel if you used it fewer than 4 times that month
A better tool comes out halfway through	This is exactly why you pay monthly. Switch next month

Limits and cautions

• Test results only apply to your own tasks. My conclusions may not fit you, and neither may anyone else's recommendations. That is exactly why you should test yourself.
• Prices and features change quickly. The prices in this article were checked on 2026-10-12. Always confirm on the official pricing page before subscribing.
• Monthly plans also renew automatically. If you do not plan to keep using a tool, cancel before the renewal date.
• Do not test with confidential client material. Check the tool's data settings first. In ChatGPT you can turn off "Improve the model for everyone" under Data controls in settings, and on Claude's personal plans you can choose whether your chats are used to improve the models.
• In-app subscription prices may differ. For example, Claude's help center says the listed Max prices are for web subscriptions, and buying through the mobile app may cost a different amount.

Resources

Resource	What it covers
Claude plans and pricing	Prices and billing cycles for Pro and Max
Claude Max plan explained	Prices for Max 5x and Max 20x
Typeless pricing	Free versus Pro, monthly and annual prices
Wispr Flow pricing	Free versus Pro
Gemini image generation	Free and paid access to Nano Banana
OpenAI model deprecations	Removal dates and replacement models for DALL-E 2 and DALL-E 3
Claude data usage	Whether chats on personal plans are used for model training
Taiwan Ministry of Labor: 2026 minimum wage (Chinese)	NT$29,500 a month, NT$196 an hour

Summary

There is no shortcut to choosing AI tools. Test a lot, compare a lot, and watch your own habits. Keep these principles in mind:

1. If you are not a heavy user, wait and watch new tools first, compare several sources, and do not buy for one small feature.
2. Other people's recommendations may not fit you. Testing for yourself matters most.
3. Do not be fooled by marketing videos. Test with your real needs.
4. When starting out, pick mature tools with plenty of resources. There is no rush to chase the newest one.
5. Watch how often you use a tool, and cancel the ones you rarely use.
6. Pay monthly, never annually, so you can always switch to the strongest tool available.
7. Look at production value: only pay if it brings direct value or saves you a lot of time.

I hope this helps you avoid a few bad picks when choosing AI tools.

Related reading

• My AI Solo Work Routine: 2025 Experiences and 8 Use Cases
• Claude Design: The Complete Guide