Expand, Filter, Absorb: How I Actually Use AI

Source: Dev.to

I wanted to understand how sleep actually affects productivity—not the usual “get 8 hours” advice, but the real picture.
Normally I’d open a browser, skim a few articles, and end up with the same recycled tips. Instead, I told my AI agent:

“Research everything about sleep and cognitive performance. Include recent studies, what scientists actually disagree on, how naps compare to full cycles, the effect of screen time before bed, and what shift workers do differently.”

It returned a synthesis of dozens of sources: PubMed studies I’d never find on my own, Reddit threads from night‑shift nurses, and contradictions between sleep coaches and neuroscience researchers. I read the summary in five minutes and had a clearer picture than after an evening of Googling.

The pattern

Every time I use AI well, I follow the same three steps. I didn’t plan it; the pattern just showed up.

Expand

Ask the AI to go wide. Not “find me an answer” but “explore this whole space.” I want angles I wouldn’t think of, sources I’d skip. The AI doesn’t get tired after page three; it just keeps going.

Filter

Now there’s too much. I ask the AI to reduce it: summarize, compare, rank by relevance, strip the noise, and give me the signal. Most people stop too early, trying to process raw results themselves. Let the machine, which reads faster than you, do the heavy lifting.

Absorb

I read (or listen to) the filtered output and connect it to what I already know. I decide which parts matter for my specific situation. The AI can tell me what experts think, but only I can determine which insight changes my next project.

It’s like asking AI to write the prompt

When you want a good AI prompt, the smartest move is to ask the AI to write it for you: “Write me the best prompt for X.” The AI knows its own format better than you do. The same applies to research—tell the AI what you want to understand and let it figure out where to look. You focus on judging the results. In both cases you use AI for the mechanical part so you can focus on the judgment part.

Fun fact from my CS background

If you’ve worked with distributed systems, this pattern may ring a bell. Google’s MapReduce framework (2004) did something similar: spread work across many machines (map), then combine results (reduce).

Expand, Filter, Absorb is basically MapReduce for your brain—except it adds an “expand” step that goes out and finds data you didn’t know existed. Small difference, big practical impact.

Try it once

Pick something you’re curious about. Don’t search for it yourself. Tell your AI to go wide, then ask it to compress, then read what survives. The specific AI you use will change, but the framework stays: expand what you can see, filter what you don’t need, absorb what matters.

Call to Action

Send this prompt to your AI:

Research everything about [your topic]. Cover at least 10 sources. Include expert opinions, common misconceptions, recent changes, and practical next steps. Then summarize the top 5 insights ranked by how actionable they are.

One prompt. Five minutes of reading. You’ll know more than most people who spent a weekend on it.