Addresses the growing problem of AI tool fatigue (the constant pressure to adopt new platforms) and proposes a triage framework: adopt (solves a current pain point), watch (interesting but no immediate need), and ignore (doesn't fit your stack or workflow).
A new AI tool launches every day. Product Hunt is overwhelming. Twitter is a firehose of “this changes everything” threads. The pressure to evaluate, test, and adopt is relentless.
Here’s the uncomfortable truth: most new tools don’t matter for your work. The ones that do are usually obvious within a week because they solve a problem you already have.
Our triage framework:
Adopt: Solves a pain point we have right now. We can describe the specific workflow it improves. We’ve tested it with real work (not just a demo). It integrates with our existing stack.
Watch: Interesting concept, but we don’t have the problem it solves yet. We bookmark it, check back in 3 months, and see if it’s still relevant (and still exists).
Ignore: Doesn’t fit our stack, our workflow, or our priorities. No matter how impressive the demo is. This is 90% of tools.
The other realization: depth beats breadth. Knowing one tool deeply (its shortcuts, its limitations, its integration options) is worth more than surface-level familiarity with ten tools. We’d rather master a handful of tools deeply (the ones our work actually runs on) than dabble in twenty alternatives.
This is exactly why we maintain detailed tool evaluations (hundreds of them) so you can make informed decisions without testing everything yourself.
- Tool Fatigue
- Tool Evaluation
- Adoption Framework
- Signal vs Noise


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