A new AI tool launches every day. Some are genuinely useful. Most are hype. And the difference between the two is hard to spot when everything promises to “change how you work.”
Here’s the framework I use to evaluate new tools without getting sucked into the endless cycle of switching, testing, and abandoning.
The Four-Question Filter
Before trying any new AI tool, run it through these four questions.
Question 1: What specific problem does this solve? Not “it’s cool” or “everyone’s talking about it.” What specific problem in your life or work does this address? If you can’t name the problem in one sentence, you don’t need the tool.
“This tool automates my weekly report generation.” That’s a problem. “This tool is an AI-powered everything platform.” That’s marketing.
Question 2: Can my current tools already do this? Before adding something new, check if your existing system covers it. Often, a new tool does something your current AI can already do with the right prompt or configuration.
“The new tool auto-summarizes meetings.” Can Claude or ChatGPT do that with a transcript? Yes. Do you need a separate tool? Probably not.
Question 3: What’s the real cost? Not just money. Time. Learning curve. Data migration. Integration overhead. Subscription commitment.
A “free” tool that takes 10 hours to set up and requires moving your data to a new platform isn’t free. It’s expensive in the only currency that matters: time.
Question 4: What happens if this tool disappears? Startups fold. Products get discontinued. Pricing changes. If this tool vanished tomorrow, would you lose your data? Your workflows? Your system?
The best tools either let you export your data easily or sit on top of platforms that aren’t going anywhere. If a tool locks your data behind a proprietary format with no export option, that’s a red flag.
Red Flags in AI Products
Watch for these warning signs.
“AI-powered” as the main selling point. If the primary feature is “we use AI,” that’s not a product. It’s a wrapper around someone else’s API. What matters is what the AI DOES, not that AI exists.
No clear pricing. “Contact us for pricing” usually means expensive or variable. Transparent pricing shows confidence. Hidden pricing suggests you might not like the number.
Requires all your data upfront. A tool that demands access to your email, calendar, contacts, and files before you can try it is collecting data, not serving you. Start with tools that work with minimal permissions and let you add more as trust builds.
No export option. If you can’t get your data out, you’re a hostage, not a customer.
Solves a problem you don’t have. The most seductive tools are the ones that create a need you didn’t know you had. “You need AI-powered dream analysis!” No, you don’t. Stay focused on your actual problems.
The 7-Day Test
If a tool passes the four-question filter, give it a 7-day test.
Day 1 to 2: Set it up. Follow the onboarding. Get it running with your real data for one specific task.
Day 3 to 5: Use it daily for that one task. Note what works and what doesn’t. Compare the output to your existing system.
Day 6: Ask yourself honestly: “Is this better than what I had? Enough to justify the switching cost?”
Day 7: Decide. Keep it or drop it. Don’t let it linger in “I’ll decide later” limbo. That’s how you end up with 12 subscriptions you barely use.
The Shiny Object Trap
This is the biggest danger for AI enthusiasts.
Every week, a new tool looks amazing. You try it. Spend hours configuring it. Start migrating your data. Then next week, another tool looks even better. And the cycle repeats.
Meanwhile, your actual system, the one that was working, sits neglected. Your morning routine breaks because you changed the tool it runs on. Your task board has three different versions across three different platforms.
The cure: commitment to your core system.
Pick your primary AI platform (Claude, ChatGPT, whatever works). Build your system on it. And only switch tools when the new option is dramatically, provably better. Not 10% better. Dramatically better.
A good system you use consistently beats a great system you’re always rebuilding.
When to Actually Switch
There are legitimate reasons to adopt a new tool.
Your current tool can’t do something critical. Not a nice-to-have. A critical capability gap that limits your system.
The new tool integrates natively with something important. If a new tool connects directly to your email or calendar in a way your current tool doesn’t, that’s a real advantage.
Significant cost savings. If a new tool does the same thing for substantially less money, that’s worth evaluating seriously.
Your current tool is declining. Less reliable. Worse updates. Slower development. If the trajectory is negative, start planning your migration.
For everything else, stick with what works.
Building an Evaluation Habit
Instead of reacting to every new launch, schedule a quarterly evaluation.
Every three months, spend 30 minutes with your AI reviewing the landscape.
“What are the most significant new AI tools released this quarter? For each one, tell me: what problem it solves, how it compares to my current setup, and whether it’s worth a 7-day test.”
Your AI compiles the overview. You read it. Maybe one tool per quarter is worth testing. Most quarters, zero.
This turns tool evaluation from a reactive, time-consuming habit into a structured, quarterly activity. You stay informed without being distracted.
The Minimalist AI Stack
After evaluating dozens of tools over the past year, here’s what I’ve landed on.
Primary AI: Claude. My daily assistant. Morning routines, task management, email drafting, planning, health tracking. Everything.
Secondary: Perplexity. For research that needs current information and sources.
Audio: OpenAI TTS. For text-to-speech when creating audio content.
That’s it. Three tools. Everything else I tried was either redundant, unreliable, or not worth the overhead.
Your stack might be different. But the principle is the same: as few tools as possible, each one earning its place by solving a real problem better than the alternatives.
Simplicity is a feature.
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