The link-building playbook that worked in 2020 — buy a few DR 60 guest posts, throw exact-match anchors at your homepage — barely moves rankings in 2026. The reason isn't just Google. It's that half of your buyers are now asking ChatGPT, Perplexity or Google's AI Overviews, and those systems weight different signals. If your SEO strategy doesn't plan for both, you're leaving obvious wins on the table.
Start with keyword research — properly
Every founder skips this and every founder regrets it. Ahrefs' Keywords Explorer (or Semrush, or Google Keyword Planner in a pinch) is non-negotiable for a simple reason: it tells you which phrases have buyers versus which ones only have curiosity.
- Aim for keywords with KD under 20 and a genuine commercial intent ("best AI [X]", "[X] alternative", "[X] pricing").
- Ignore vanity volume. A KW with 200 searches and clear intent beats a 20k-volume keyword you have no realistic chance of ranking for.
- Cluster keywords into single pages. One page per intent, not per keyword.
Links still matter — and diversity matters more than DR
Ahrefs' own studies (see Do Links Still Matter for Rankings? and their 1M-SERP analysis) keep showing the same thing: referring-domain count correlates with organic traffic more strongly than almost any other off-page signal.
Where founders go wrong is chasing a single number (DR) and buying five links from the same PBN network. What actually moves the needle is a diverse mix:
- Directories — cheap, permanent, categorically relevant. See our free AI directories round-up.
- Listicles & niche edits — the highest-ROI link type for AI tools in 2026 (we'll come back to why).
- Press releases & syndication — one-time authority builder, good for brand SERP and Google News trust.
- Guest posts on real, trafficked blogs — not link farms.
- Organic mentions from Reddit, X and community forums — unlinked brand mentions are now a ranking signal on their own.
Why listicles influence both Google and LLMs
This is the biggest shift of the last 18 months. Analyses like Search Engine Land's 8,000-citation study and Discovered Labs' 2M-citation analysis both landed on the same pattern: LLMs disproportionately cite comparison and listicle pages ("top 10 AI X", "best X for Y") when generating recommendations.
Semrush's most-cited-domains study shows the same domains — TAAFT, G2, Reddit, YouTube, review aggregators — appearing over and over in AI answers. Getting your tool named inside those pages is now one of the most efficient marketing investments in the space.
How to actually do it
- Find listicles already ranking in Google's top 20 for your target keyword.
- Pitch the author or the site — a paid niche edit, an expert quote, or a genuinely improved data point.
- Make sure your inclusion is contextual (in the body of the list, not the footer). LLMs weight in-context mentions much higher.
- Use natural anchor text — brand name, or short descriptive phrase. Exact-match anchors are penalised now.
What a healthy 90-day plan looks like
- Weeks 1–2: Keyword research + 3 high-intent target pages on your own site.
- Weeks 2–4: Submit to 25–30 free AI directories for baseline link diversity.
- Weeks 4–8: Pitch or buy inclusion in 5–10 already-ranking listicles.
- Weeks 6–10: One press release wire, aimed at brand SERP + Google News.
- Ongoing: Reddit, X and Quora activity for unlinked brand mentions.
Bottom line
SEO for AI startups in 2026 is really two jobs: rank in Google and get cited by LLMs. Both reward the same underlying behaviour — diverse, contextual, brand-heavy mentions across real sites people actually read. Keyword research keeps you honest about what to rank for. Link diversity is what actually gets you there. For the LLM-citation half of this equation specifically, see our deep dive on how to get your AI tool recommended by ChatGPT and Gemini.