How to Keep Up With AI Without Drowning (15 Minutes a Week)

Somewhere in the last two years, keeping up with AI became its own part-time job. A new model every month, a new tool every week, and a feed full of people announcing that everything changed again this morning. The honest secret: you do not need to keep up with AI. You need to keep up with the five percent of it that touches your work, and that takes about fifteen minutes a week.

Here is the low-effort system: one digest instead of twelve feeds, one weekly slot, one experiment a month, and a filter for deciding what actually deserves your attention.

The filter: what deserves your attention at all

Most AI news fails a simple test: does this change what I can do at my desk this month? Model benchmark drama does not. Funding rounds do not. A new feature inside a tool you already use does. A capability jump in something you do weekly (writing, research, images, meetings) does. Everything else is spectator sport, enjoyable but optional. When in doubt, our plain-English jargon glossary turns headline noise into a two-minute check of whether anything real happened.

One digest, not twelve feeds

Following AI news in real time is how you drown. Pick exactly one weekly digest (a newsletter or a podcast episode) whose job is to filter for you, and unfollow the rest with a clear conscience. Better still, make AI curate its own field:

I am a [role] who uses AI for [your main tasks]. Once a week I will paste in headlines or links I noticed. Your job: tell me 1) which items actually affect someone in my role, in one sentence each, 2) which are hype or irrelevant to me and why in five words, 3) the one thing, if any, worth 15 minutes of my time this week. Be ruthless.

An assistant with web search can even fetch the week's AI news itself before filtering it, which turns the whole ritual into one prompt.

The fifteen-minute Friday slot

Attention needs a container or it leaks all week. Book one recurring slot (Friday coffee works) and give it a fixed agenda: read the digest, run the filter prompt, and note at most one thing to try. Outside that slot, AI news is officially not your problem, and the fear of missing out dies the moment you know the catch-up is scheduled. It is the same trick that weekly status updates play on projects: a boring rhythm that quietly beats heroic bursts.

One experiment a month beats ten bookmarks

Reading about AI changes nothing; trying something does. Once a month, promote one item from your notes to a real experiment on a real task:

This month I want to try: [the thing]. Design me a 30-minute experiment on my real work: what task to test it on, what a fair success test looks like, and what I should compare it against (my current way of doing it). At the end, help me decide: adopt, drop, or revisit in three months.

Most experiments end in drop, and that is the system working: you now know, instead of wondering. The ones that stick, like voice mode or a first automation, each pay for a year of Fridays.

What you can safely ignore

Model release day coverage (wait for the weekly digest to tell you if it matters). Benchmark arguments. Anything predicting the world in 2035. Tool roundups listing forty options, when two or three free tools cover an office worker's actual needs. And doom-or-hype takes about your job, which the evidence answers more calmly.

Calm beats current

The colleagues who seem effortlessly up to date are not reading more than you; they are filtering harder and trying things sooner. Fifteen minutes on Friday, one experiment a month, and a shortlist of skills that compound: that is the whole practice. The skills part is what our free courses are for, and they change far more slowly than the news does.