Why not X search directly. X's search and profile pages block automated fetching, so nothing here came from browsing X's timeline. Instead, individual profiles were read through a public mirror of X's profile API (api.fxtwitter.com/<handle>), which returns the live bio and follower count for a known handle. That means the research could verify a candidate but could not discover one from X alone; discovery came from the sources below.
Step 1 - build the candidate pool (≈45 names). Sources, in order of weight: Indie Hackers "milestone" interviews from Jul 2025-Jun 2026 (the single best feed for rising names, because founders self-report a number and a date); the TrustMRR leaderboard and founder pages (Stripe-verified MRR, lifetime revenue, plus a live X follower count with a 30-day delta); Starter Story revenue breakdowns; Product Hunt "top indie hackers" and Maker of the Year lists; arrfounder.com growth reports; and a handful of "indie hackers to follow on X in 2026" listicles used only for names, never for numbers (their follower counts were about 2x stale). Searches were phrased around outcomes rather than labels: "hit $10k MRR build in public 2026", "solo founder $1M ARR 2026", "vibe coding indie hacker MRR", "$0 to $50k MRR in months".
Step 2 - verify each candidate on four axes.
- Handle and audience. Live X bio and follower count, dated. Old handles were checked and three had changed (@marc_louvion, @dannypostmaa, @damengchen no longer resolve). Candidates with no findable X presence were kept only if the revenue evidence was strong, and marked "unverified".
- Revenue. Preference order: Stripe-verified page (TrustMRR, open dashboards like levels.io/stats) → founder's own post with a screenshot → Indie Hackers interview → third-party article. Every figure carries its source and date. Where a tweeted figure and a verified figure disagreed, both are shown and the disagreement is flagged rather than resolved - same rule as the paper's editorial policy.
- Track record. Verified exits, years of public updates, and whether they report bad months and failed products, not just wins. Reporting the downside was weighted heavily; it is the cheapest honesty signal available.
- Business model. Who pays them? If the majority of revenue is courses, communities or boilerplates sold to other indie hackers, that was flagged ("picks and shovels") or, in the pure-creator case, excluded.
Step 3 - split established vs rising. Established = public track record of 4+ years, six-figure-plus following, and revenue verifiable across multiple years. Rising = the breakout (revenue or audience, ideally both) happened within the last 12-24 months; a business can be older (Zigpoll, 2019) if the public presence is new. Names that had already exited or become well-known before 2025 (Nico Jeannen, Alexander Isora, Dan Kulkov) were pushed out of "rising".
Step 4 - rank. Established list ordered by follower count, then trust. Rising list ordered by strength of verification first (verified MRR + dated follower growth at the top), then by size of the number. That is why Jack Friks outranks Jason Zigelbaum despite a smaller revenue figure: one is Stripe-verified with a follower trend, the other is self-reported.
Exclusion rules applied. VC-funded (Sahil Lavingia, Riley Brown, and Romàn is on the edge after YC); pure creator/media (Justin Welsh, Greg Isenberg, Ben Tossell); community host rather than builder (Courtland Allen, KP); no 2025-26 revenue evidence (Hasan Toor, Cindy Zhou, Ryan Carson); big audience but declining business (Dagobert Renouf). Anonymised IH case studies with no product or handle were dropped.
Known limits. Follower counts are a single-day snapshot (24 Aug 2026) and two TrustMRR pages disagreed by ~4K on the same person the same day. The only third-party verification layer is TrustMRR, owned by Marc Lou. LinkedIn-native and YouTube-native builders are under-represented, because this list was compiled from X. It is rebuilt from scratch every quarter, and the rising half turns over fastest.