Automate your research with AI: stay informed without drowning

Image: Wendelin Jacober — Openverse (cc0)

In short — Automating your research with AI means stopping the information flood from running you, and shrinking it to a 10-minute daily digest. A simple system — RSS aggregator + LLM + a fixed ritual — is enough to stay informed without sacrificing your deep work time.

---

Eighteen months ago, I easily spent forty-five minutes every morning opening tabs. Twitter/X, Hacker News, a few newsletters, a diagonal skim of LinkedIn. I told myself it was research. It was scrolling dressed up as work.

The problem isn’t information. The problem is the lack of a system to process it. And for a solopreneur who ships alone, every hour lost in the noise is an hour stolen from code, distribution, and clients.

What’s the real cost of unstructured research for a solo?

Unstructured research costs a typical independent between 1 and 2 hours a day — without producing proportional value. That’s not an opinion: a RescueTime study on knowledge workers estimates that interruptions and context switching destroy up to 40% of daily productivity.

For a solo, it’s even harsher. You don’t have a colleague who filters for you, no research meeting where someone synthesizes. Either you do it all, or you miss it all. And because you don’t want to miss anything, you scroll.

The real cost isn’t just reading time. It’s the cognitive cost of sorting: deciding in real time whether each article deserves your attention. That cost piles up in the background and wears you out before you’ve even opened your code editor.

AI doesn’t read for you. It does the sorting upstream, so you no longer have to.

How do you build an AI research system in under an hour?

An automated research system comes down to three blocks: a source aggregator, an LLM that summarizes and filters, and a place to read the result. Nothing more.

Block 1 — The aggregator (15 min of setup)

Feedly is still the go-to. Free plan to start, Pro at ~$8/month if you want the built-in AI features (Leo, their filtering engine). You plug in your RSS feeds: blogs, industry publications, GitHub feeds of projects you follow.

No-subscription alternative: an OPML file imported into n8n or Make, which pulls the feeds directly. More technical, but zero recurring cost.

Block 2 — The LLM that filters (20 min of setup)

Two approaches depending on how comfortable you are:

1. Perplexity Spaces (the simplest): you create a themed space, you define your priority topics, Perplexity generates a daily digest with verifiable sources. Pro plan at $20/month, zero code.

2. Make or n8n + Claude or GPT-4o (the most flexible): a scenario that pulls today’s articles from Feedly, sends the titles + excerpts to an LLM with a filtering prompt, and pushes the summary into Notion, a private Slack channel, or a simple email. Setup in 30 to 45 min if you already know Make.

The filtering prompt is the key. Minimal example: “Here’s a list of articles. Select only those that relate to [your 3 topics]. For each selected article, write a 2-sentence summary and say why it matters for a solopreneur developer.” The more precise your prompt, the cleaner the signal.

Block 3 — The receptacle (5 min)

A dedicated Notion page, a Slack #research channel, or even an email folder. What matters: one place. Not three.

Realistic total budget for a solid system: $20 to $30/month. Less than a coffee a day.

Which sources should you plug in — and which should you cut without regret?

The quality of a research system is measured first by what you take from it, but above all by what you cut. Most of the sources you follow today have probably given you nothing concrete in the last six months.

Sources to plug in (strong signal)

• The technical blogs of the tools you actually use (Anthropic, OpenAI, Vercel, Supabase — their changelogs are worth more than 90% of roundup articles)
• 2 to 3 newsletters from practitioners who publish lived experience, not commentary (Lenny’s Newsletter, Indie Hackers digest, The Pragmatic Engineer depending on your field)
• The GitHub feeds of open source projects critical to your stack — issues and releases are pure research
• 1 to 2 feeds from researchers or practitioners on X/Bluesky, imported via RSS (Nitter or RSS bridges exist for that)

Sources to cut without guilt

• Generalist aggregators (TechCrunch, The Verge): 95% of the content doesn’t concern you, and what matters will end up in your filtered research anyway
• Newsletters that summarize other newsletters: you pay in attention for third-hand content
• LinkedIn in free-scroll mode: if you want to follow someone specific, subscribe to their RSS feed or their direct newsletter

The simple rule: if you can’t name a concrete takeaway from that source in the last 30 days, cut it.

To go further on the numbers that show why information volume is exploding and how solos are responding, check out our roundup solopreneur & AI statistics 2026.

When and how should you consume the AI summary so it actually pays off?

An automated research system running in the background is useless if you check it whenever, however. The consumption ritual matters as much as the technical setup.

The timing: never first, never last

Don’t start your day with your research. The first hours are for deep work — code, writing, decisions. Research first thing in the morning is opening the window on the world’s noise before you’ve produced anything. Bad idea.

The slot that works: after lunch, for 10 to 15 minutes. Your brain is in a lower-intensity mode — the right time to absorb information without a high cognitive cost.

The format: read the digest, not the articles

Your LLM produced a summary. Read it. If a point really grabs you, open the source article. Otherwise, move on. The goal isn’t to read everything — it’s to know what matters and to go deeper when it’s strategically useful.

Concretely: 10 minutes reading the digest, 0 to 20 minutes of deep-dive on 1 or 2 topics max. Total: 30 minutes a day, not one more.

The capture: one place, one sentence

If something in the digest deserves an action or a future thought, note it immediately in your system (Notion, Obsidian, whatever). One sentence is enough: “Look at X’s API for project Y” or “Potential angle for an article”. Without capture, research stays passive consumption.

---

AI carries the volume. You keep the judgment. That’s exactly the division of labor that lets a solo stay competitive without burning out — AI filters the noise, you read the 10% that matters, and you spend the rest of the time building.

If you want someone to look at your current stack and identify where you’re wasting time, Sébastien de Bollivier does that as a freelance dev.

Got an idea to ship? A website, a SaaS, an AI automation — built with you.

Talk about your project