The AI industry produces more decisions per week than any person can make well. That is not a bug — it is the business model. Attention and evaluation cycles are the product. Every new model announcement, every tool launch, every comparison thread is a decision request dressed up as information.
The cure is not better decision-making. The cure is defaults.
What decision fatigue looks like in AI
Sunday: you read about a new model. Monday: you evaluate a new tool. Tuesday: you watch a demo. Wednesday: you sign up for a trial. Thursday: you are back to your old workflow because the new tool did not integrate easily. Friday: you read about another new model.
Net output: zero.
You spent a full week in evaluation mode and shipped nothing. The tools changed. The work did not move. This is not a time management problem. It is a structural one — you are making the same category of decision on repeat, with no mechanism to stop.
Defaults are the cure
A default is a pre-made decision. One model for content. One tool for automation. One workflow for each function. Decided once, revisited quarterly.
When a default is set, the decision is closed. You do not re-evaluate every time a new option appears. The new model launches — noted, filed, not acted on until the next review. The new tool gets a demo request — declined. The question is already answered.
Defaults do not mean you are locked in. They mean you are not perpetually unlocked.
How to set your AI defaults
For each function you use AI for, pick the best current option and commit to it for 90 days. Write it down explicitly.
For content drafting, I use Claude. For automation, I use Make. For support, I use Tidio.
That is your default stack. It is not permanent. It is a 90-day commitment — long enough to get real output, short enough to course-correct if something is genuinely broken.
The act of writing it down matters. An unwritten default is just a preference. A written default is a policy. Policies do not require re-litigation every Monday morning.
The decision moratorium
Declare a 60-day moratorium on new AI tool evaluations. No new trials. No new demos. No new newsletters about tools.
Use what you have. Ship with what you have.
At the end of 60 days, evaluate one new thing — but only if a specific, measured gap has emerged. Not because something looked interesting. Not because a competitor mentioned it. A gap: a task you cannot do, a cost you cannot justify, a workflow that is visibly broken.
If no gap exists, the moratorium extends by default.
Defaults compound
Every decision you make once and encode as a default is a decision you never have to make again. That is the mechanism.
After 12 months of defaults, you have a stable stack, a prompt library, and a set of workflows that run without you thinking about them. The cognitive overhead of the stack approaches zero. The output does not.
That is the compounding effect of decided-once. The first 90 days feel slow. Month 10 feels like leverage.
We send a quarterly AI stack review template to Field Notes subscribers — a structured way to evaluate your defaults without falling into the evaluation trap. Get it at avakata.agency/contact.html.
What we do at Avakata
We review the stack quarterly. We add a new tool only when a specific, measured gap exists — not when something is new, not when a vendor pitches us, not when a benchmark looks good.
We have not added a net-new tool category in six months.
The stack is boring. The output is not.
If you want to audit your current AI stack and set defaults that hold, book a discovery call. We will tell you what to cut, what to keep, and what to stop evaluating.