Skip to content
FORKOFF

Per our own X pipeline, 50 AI founders were composite-ranked on 3 first-party inputs over a 30-day window.

Statistics hub · Updated 2026-07-23· n=50 · 30-day window

The 50 Most Active AI Founders on X,Composite-Ranked Q3 2026

FORKOFF ranks 50 AI founders on 3 first-party X-engagement inputs with 1000-iteration bootstrap CI per rank, framed by 45 cited data points from 23 named authorities. Authored by Kartik Chugh (Simba), reviewed by Kshitij JK.

Quick answer

As of 2026-07-23, the top 5 most active AI founders on X by composite score are Andrew Curran (AI Curator, 0.97), Pietro Schirano (EverArt, 0.82), Jason Liu (Instructor, 0.74), Nick Dobos (indie, 0.73), and Logan Kilpatrick (Google DeepMind, 0.73). Composite score under PRIMARY equal-weight scheme on a 0-1 scale. The composite rewards quality-adjusted activity (cadence, engagement rate, and reply rate), so high-follower broadcasters can rank below smaller, more active operators. Recomputed quarterly. Full 50-founder ranking + 95% bootstrap CI below.

50Verified handles
3Composite inputs
1000Bootstrap iterations
2026-07-23Last updated
Editor's Choice

The 20 numbers that frame this ranking.

Twenty externally cited statistics, ranked by how much each one frames an active-founder ranking on X. Every row carries a figure, a named source, and the year it was published, so the claim behind the ranking stays checkable at a glance rather than asserted. The full set of 45 cited data points, each with an inline link to its source, sits in the data appendix lower on this page.

#FigureStatisticSource
127x / 150xOn X's open-sourced ranking model a reply is weighted 27x a like, and a reply the author engages back on 150x a like (like 0.5, reply 13.5, reply-with-author-engagement 75.0).Corrects the live page and anchors why the composite weights replies so heavily.X Engineering, 2023Verified at primary source
252% / 54%52 percent of decision-makers and 54 percent of C-suite executives spend an hour or more per week reading thought leadership.Buyers actually read founder and executive content, and read a lot of it.Edelman and LinkedIn, 2024Verified at primary source
3586MX reported an advertising reach of 586 million users in January 2025.Sizes the platform the ranking covers at just under 600 million reachable users.DataReportal, 2025Verified at primary source
475%75 percent of decision-makers say a piece of thought leadership led them to research a product they were not considering.The pipeline mechanism: thought leadership creates net-new product demand.Edelman and LinkedIn, 2024Verified at primary source
5~90%9 in 10 decision-makers are more receptive to sales outreach from a firm that consistently produces quality thought leadership.The founder-funnel thesis in one number.Edelman and LinkedIn, 2024Verified at primary source
6250B to 480BThe creator economy is projected to roughly double from 250 billion dollars to 480 billion dollars by 2027.The macro backdrop the ranking sits inside.Goldman Sachs, 2023As reported by source
75xPersonal LinkedIn profiles generate roughly 5x more engagement than company pages.The founder-versus-brand core: personal beats the company page.Refine Labs, 2025As reported by source
8-33%Twitter posting frequency fell 33 percent year-on-year, the sharpest drop of any major platform.Why an active-founder ranking is scarce and valuable.Rival IQ, 2025As reported by source
92.16 vs 3.3The median X account posts 2.16 times per week, down from 3.3 the prior year.Context that makes the cohort's 8 to 142 posts-per-week range remarkable.Digital Web Solutions, 2025As reported by source
1051%Companies with high social-selling adoption post 51 percent higher revenue attainment.Ties activity to revenue, not vanity metrics.LinkedIn, 2025As reported by source
1170%70 percent of C-suite leaders say thought leadership at least occasionally made them question staying with an existing supplier.Competitive-displacement stakes for incumbents.Edelman and LinkedIn, 2024Verified at primary source
12-5.3% (-33M)X ad reach fell 5.3 percent year-on-year, a loss of 33 million reachable users.The platform-decline counter-narrative the active founders defy.DataReportal, 2025Verified at primary source
1315%Only 15 percent of decision-makers rate the thought leadership they consume as very good, a quality gap.The quality gap the ranking's methodology is built to address.Edelman and LinkedIn, 2024Verified at primary source
14220.2MElon Musk is the most-followed X account at 220.2 million followers.Anchors the number-one slot and the celebrity-versus-operator distinction.Brandwatch and Global Statistics, 2025As reported by source
1514.6% vs 1.7%Inbound where a prospect messages a founder after reading their content converts to a discovery call at 14.6 percent versus 1.7 percent outbound.The sharpest single ROI contrast in the dossier.Grow with Ghost, 2026As reported by source
16104MThe United States is X's largest country audience at 104 million users.The United States is the single largest market the ranking covers.DataReportal, 2025Verified at primary source
1741.5M / 30.9 minThe US has about 41.5 million monetizable daily active X users spending 30.9 minutes per day.US daily active users and time-on-platform for the founder audience.Statista (cited), 2025As reported by source
1873%73 percent of consumers will switch to a competitor if a brand does not respond on social.Responsiveness stakes: silence costs the switch.Sprout Social, 2025As reported by source
1993%93 percent of consumers say it matters that brands stay connected to online culture.Audiences expect brands and founders to stay culturally connected.Sprout Social, 2025As reported by source
20561% / 2.75x / 7xEmployee-advocacy reshares reach 561 percent further than company-page posts, with 2.75x impressions and 7x lead conversion.Advocacy reshares travel far past the company page.LinkedIn (cited), 2025As reported by source

Figures marked verified at primary source were confirmed on the publisher's own page. Figures marked as reported by source are widely converged and attributed to the named authority but were not fetched from a single primary filing, so they are presented as that source reports them, not as hard primary claims. Full method in the sources-consulted block.

Top 10 above the fold

The top 10 most active AI founders right now.

Ten cards, one per founder, ordered by the PRIMARY composite score. Each card shows the handle, display name, and company, the composite score under PRIMARY equal-weight, the secondary rank under platform-aware weights, the 95% bootstrap confidence bracket on the rank, and a one-sentence receipt that explains in plain terms why that founder ranks where they do.

FORKOFF composite-ranks 50 AI founders on X by 3 first-party X engagement inputs over a 30-day window with 95% bootstrap CI per rank. PRIMARY composite uses equal weights to avoid reviewer-collapse. The SECONDARY column shows where each founder ranks under platform-aware weights that lean on engagement rate (the highest-signal X metric per X's 2023 open-sourced ranking algorithm).

#1Andrew Curran
@AndrewCurran_ AI Curator

Highest cadence in the cohort at 132 posts per week, with a 1.0% engagement rate and a 56% reply rate over the 30-day window.

PRIMARY composite
0.973
SECONDARY rank
#1
95% CI on rank
#1 to #1
Posts / week
132
Engagement rate
1.0%
Reply rate
56%
Followers
74,790
#2Pietro Schirano
@skirano EverArt

A 1.0% engagement rate, with 11 posts per week and a 41% reply rate over the 30-day window.

PRIMARY composite
0.823
SECONDARY rank
#2
95% CI on rank
#2 to #5
Posts / week
11
Engagement rate
1.0%
Reply rate
41%
Followers
108,707
#3Jason Liu
@jxnlco Instructor

83 posts per week, with a 0.3% engagement rate and a 16% reply rate over the 30-day window.

PRIMARY composite
0.741
SECONDARY rank
#6
95% CI on rank
#2 to #9
Posts / week
83
Engagement rate
0.3%
Reply rate
16%
Followers
118,560
#4Nick Dobos
@NickADobos indie

28 posts per week, with a 0.4% engagement rate and a 14% reply rate over the 30-day window.

PRIMARY composite
0.735
SECONDARY rank
#4
95% CI on rank
#2 to #10
Posts / week
28
Engagement rate
0.4%
Reply rate
14%
Followers
53,265
#5Logan Kilpatrick
@OfficialLoganK Google DeepMind

A 0.7% engagement rate, with 7 posts per week and a 30% reply rate over the 30-day window.

PRIMARY composite
0.728
SECONDARY rank
#3
95% CI on rank
#3 to #10
Posts / week
7
Engagement rate
0.7%
Reply rate
30%
Followers
342,253
#6Sebastian Raschka
@rasbt Lightning AI

A 44% reply rate, with 3.7 posts per week and a 0.6% engagement rate over the 30-day window.

PRIMARY composite
0.728
SECONDARY rank
#5
95% CI on rank
#3 to #12
Posts / week
3.7
Engagement rate
0.6%
Reply rate
44%
Followers
481,291
#7Scott Stevenson
@scottastevenson Spellbook

35 posts per week, with a 0.4% engagement rate and a 13% reply rate over the 30-day window.

PRIMARY composite
0.728
SECONDARY rank
#7
95% CI on rank
#3 to #8
Posts / week
35
Engagement rate
0.4%
Reply rate
13%
Followers
21,599
#8Pieter Levels
@levelsio indie

80 posts per week, with a 0.2% engagement rate and an 18% reply rate over the 30-day window.

PRIMARY composite
0.714
SECONDARY rank
#11
95% CI on rank
#3 to #10
Posts / week
80
Engagement rate
0.2%
Reply rate
18%
Followers
918,252
#9Georgi Gerganov
@ggerganov llama.cpp

A 43% reply rate, with 1.6 posts per week and a 0.7% engagement rate over the 30-day window.

PRIMARY composite
0.697
SECONDARY rank
#8
95% CI on rank
#4 to #19
Posts / week
1.6
Engagement rate
0.7%
Reply rate
43%
Followers
62,836
#10Jeremy Howard
@jeremyphoward Answer.ai

A 38% reply rate, with 1.9 posts per week and a 0.6% engagement rate over the 30-day window.

PRIMARY composite
0.667
SECONDARY rank
#12
95% CI on rank
#4 to #36
Posts / week
1.9
Engagement rate
0.6%
Reply rate
38%
Followers
322,859

See the ASVC discovery gap research for the parallel composite-rank methodology applied to AI-search visibility, and the FORKOFF about page for operator transparency on the editorial self-exclusion firewall.

3 charts

The cohort in three pictures.

Three charts built entirely from the first-party cohort data, not lifted from a third-party aggregator. The first plots cadence distribution against the platform norm, the second maps follower reach against reply rate to separate operators from broadcasters, and the third ranks the highest-cadence founders against the median X account so the scarcity the ranking measures is visible at a glance.

Chart 1 · Cadence distribution

Most ranked founders post well above the platform norm.

01631310-10911-20421-30231-4041-60261-1002100+Posts per week (bucketed)Platform median 2.16/wk; 31 of 50 founders post above it

The median X account posts 2.16 times per week, down from 3.3 a year earlier (Digital Web Solutions, 2025). 31 of the 50 ranked founders sit in a higher bucket, which is the scarcity the ranking measures while platform-wide posting fell 33 percent year-on-year (Rival IQ, 2025).

Chart 2 · Reach vs conversation

Follower reach does not equal operator behavior.

10%20%30%40%50%60%10K100K1M10M100MOperator floor, 30% reply rateFollower count (log scale) · dot size = engagement rate

The horizontal line is the 30 percent reply-rate floor that separates operator-mode founders (bright, above the line) from broadcast-mode founders (muted, below). Dot size is engagement rate. A founder can have a huge audience on the x-axis and still sit below the operator floor, which is exactly why the composite does not collapse to raw follower count. X's own model weights a reply 27x a like, up to 150x with author engagement (X Engineering, 2023).

Chart 3 · Movers baseline

The 12 highest-cadence founders against the median account.

Andrew Curran132Elon Musk108Jason Liu83Pieter Levels80Scott Stevenson35Pedro Domingos33Nick Dobos28Harrison Chase26Bindu Reddy25Garry Tan24Paul Graham19Greg Brockman182.16/wk platform medianPosts per week · Q3 2026 baseline, year-on-year rank movers ship at the Q3 refresh

This snapshot is an early baseline, so this chart shows absolute cadence against the 2.16-per-week platform median rather than a quarter-on-quarter delta. The movers-and-losers chart, showing each founder's rank change against the prior snapshot, ships at the Q3 refresh once two snapshots exist.

Rate your handle

How does your handle rank against the top 50?

Paste your handle. The widget calls the same composite-score logic FORKOFF runs against the cohort and returns your percentile rank plus a per-input breakdown. The unlocked view shows your score against the top 10 and a downloadable PDF placement card.

fk_widget rate_my_handle.tsx

FORKOFF ranks any X handle on the same 3-input composite the top 50 cohort uses with 1000-iteration bootstrap. Audit-grade. Same logic the cohort sees. The free version returns percentile and headline composite. The unlocked PDF returns the per-axis breakdown plus comparison against the top 10.

Widget routes through the ASVC visibility checker for now, same composite logic, AEO-focused output. The dedicated rate-my-handle widget ships in a future update once the public composite-scoring endpoint is wired.

Composite axis 1
Cadence (posts / week)
Composite axis 2
Engagement rate
Composite axis 3
Reply rate
Ranks 11-50 denser format

The remaining 40 founders, ranked 11 to 50.

Forty cohort rows in a denser layout. Each row carries rank, handle, display name, company, category, PRIMARY composite, SECONDARY rank, 95% CI bracket, and the per-input trio.

FORKOFF publishes 40 additional cohort rows ranked 11 to 50 with identical methodology and full per-input transparency. Compare against the FORKOFF cold-email open-rates benchmark and the ASVC discovery gap research for sister composite-rank benchmarks.

Rank
Founder
PRIMARY
SECONDARY
95% CI
  • #11
    Shawn Wang
    @swyx Smol AI ai devtools
    A 39% reply rate, with 6.5 posts per week and a 0.3% engagement rate over the 30-day window.
    0.650
    #15
    #8 to #20
  • #12
    Captain Nemo
    @thecaptain_nemo indie ai voice_creator
    A 2.2% engagement rate, with 2.1 posts per week and an 11% reply rate over the 30-day window.
    0.643
    #9
    #6 to #41
  • #13
    Aidan Gomez
    @aidangomez Cohere ai product
    A 1.6% engagement rate, with 1.6 posts per week and a 14% reply rate over the 30-day window.
    0.639
    #10
    #8 to #39
  • #14
    Thang Luong
    @lmthang Google DeepMind ai research
    A 50% reply rate, with 0.5 posts per week and a 0.5% engagement rate over the 30-day window.
    0.633
    #14
    #11 to #40
  • #15
    Sam Altman
    @sama OpenAI foundation labs
    13 posts per week, with a 0.3% engagement rate and an 11% reply rate over the 30-day window.
    0.622
    #16
    #9 to #22
Show ranks 16 to 50 (35 founders) →expand
  • #16
    François Chollet
    @fchollet Google ai research
    14 posts per week, with a 0.2% engagement rate and a 20% reply rate over the 30-day window.
    0.612
    #20
    #10 to #20
  • #17
    Paul Graham
    @paulg Y Combinator ai devtools
    19 posts per week, with a 0.1% engagement rate and a 23% reply rate over the 30-day window.
    0.599
    #23
    #11 to #21
  • #18
    Soumith Chintala
    @soumithchintala Meta ai open_source
    A 0.6% engagement rate, with 1.4 posts per week and a 17% reply rate over the 30-day window.
    0.578
    #17
    #10 to #40
  • #19
    Alexandr Wang
    @alexandr_wang Meta Superintelligence Labs foundation labs
    14 posts per week, with a 0.2% engagement rate and an 8% reply rate over the 30-day window.
    0.578
    #19
    #10 to #25
  • #20
    Jim Fan
    @drjimfan NVIDIA ai research
    A 43% reply rate, with 1.6 posts per week and a 0.2% engagement rate over the 30-day window.
    0.568
    #22
    #11 to #35
  • #21
    CTO Junior
    @cto_junior indie ai product
    Highest engagement rate in the cohort at a 2.5% engagement rate, with 6.8 posts per week and a 0% reply rate over the 30-day window.
    0.561
    #13
    #17 to #24
  • #22
    Anjney Midha
    @AnjneyMidha a16z ai devtools
    A 0.4% engagement rate, with 9.1 posts per week and a 3% reply rate over the 30-day window.
    0.561
    #18
    #13 to #32
  • #23
    Mira Murati
    @miramurati Thinking Machines Lab foundation labs
    A 33% reply rate, with 0.7 posts per week and a 0.4% engagement rate over the 30-day window.
    0.561
    #21
    #10 to #42
  • #24
    David Ha
    @hardmaru Sakana AI ai product
    A 39% reply rate, with 4.2 posts per week and a 0.2% engagement rate over the 30-day window.
    0.558
    #26
    #10 to #31
  • #25
    Garry Tan
    @garrytan Y Combinator ai devtools
    24 posts per week, with a 0.1% engagement rate and a 10% reply rate over the 30-day window.
    0.527
    #28
    #15 to #28
  • #26
    Bindu Reddy
    @bindureddy Abacus.AI ai product
    25 posts per week, with a 0.2% engagement rate and a 1% reply rate over the 30-day window.
    0.524
    #25
    #15 to #33
  • #27
    Jonathan Frankle
    @jefrankle Databricks ai research
    A 0.3% engagement rate, with 2.3 posts per week and a 10% reply rate over the 30-day window.
    0.514
    #24
    #14 to #42
  • #28
    Aravind Srinivas
    @AravSrinivas Perplexity foundation labs
    14 posts per week, with a 0.1% engagement rate and a 10% reply rate over the 30-day window.
    0.514
    #30
    #18 to #32
  • #29
    Elon Musk
    @elonmusk xAI foundation labs
    108 posts per week, with a 0.0% engagement rate and a 4% reply rate over the 30-day window.
    0.510
    #36
    #22 to #31
  • #30
    Harrison Chase
    @hwchase17 LangChain ai devtools
    26 posts per week, with a 0.1% engagement rate and a 2% reply rate over the 30-day window.
    0.497
    #33
    #21 to #35
  • #31
    Pedro Domingos
    @pmddomingos U Washington ai voice_creator
    33 posts per week, with a 0.2% engagement rate and a 0% reply rate over the 30-day window.
    0.493
    #27
    #21 to #32
  • #32
    Greg Brockman
    @gdb OpenAI foundation labs
    18 posts per week, with a 0.2% engagement rate and a 1% reply rate over the 30-day window.
    0.483
    #34
    #21 to #36
  • #33
    Clem Delangue
    @ClementDelangue HuggingFace ai open_source
    14 posts per week, with a 0.1% engagement rate and a 5% reply rate over the 30-day window.
    0.459
    #38
    #24 to #39
  • #34
    Martin Casado
    @martin_casado a16z ai devtools
    6.5 posts per week, with a 0.2% engagement rate and a 4% reply rate over the 30-day window.
    0.452
    #35
    #22 to #40
  • #35
    Mustafa Suleyman
    @mustafasuleyman Microsoft AI foundation labs
    A 23% reply rate, with 3 posts per week and a 0.0% engagement rate over the 30-day window.
    0.449
    #40
    #28 to #43
  • #36
    Amjad Masad
    @amasad Replit foundation labs
    10 posts per week, with a 0.3% engagement rate and a 0% reply rate over the 30-day window.
    0.439
    #32
    #27 to #39
  • #37
    Julien Chaumond
    @julien_c HuggingFace ai open_source
    9.1 posts per week, with a 0.2% engagement rate and a 0% reply rate over the 30-day window.
    0.422
    #37
    #30 to #40
  • #38
    Bill Gurley
    @bgurley Benchmark ai devtools
    6.3 posts per week, with a 0.1% engagement rate and a 4% reply rate over the 30-day window.
    0.401
    #41
    #30 to #43
  • #39
    Ilya Sutskever
    @ilyasut Safe Superintelligence foundation labs
    A 0.9% engagement rate, with 0.2 posts per week and a 0% reply rate over the 30-day window.
    0.391
    #29
    #34 to #39
  • #40
    Andrej Karpathy
    @karpathy Eureka Labs ai research
    A 0.8% engagement rate, with 0.2 posts per week and a 0% reply rate over the 30-day window.
    0.384
    #31
    #35 to #40
  • #41
    Demis Hassabis
    @demishassabis Google DeepMind foundation labs
    A 0.5% engagement rate, with 0.2 posts per week and a 0% reply rate over the 30-day window.
    0.337
    #39
    #38 to #42
  • #42
    Aaron Levie
    @levie Box ai voice_creator
    11 posts per week, with a 0.0% engagement rate and a 0% reply rate over the 30-day window.
    0.310
    #42
    #41 to #43
  • #43
    Andrew Ng
    @AndrewYNg DeepLearning.AI ai research
    A 0.2% engagement rate, with 1.2 posts per week and a 0% reply rate over the 30-day window.
    0.262
    #43
    #39 to #44
  • #44
    HuggingFace
    @huggingface HuggingFace ai open_source
    A 0% reply rate, with 0.9 posts per week and a 0.0% engagement rate over the 30-day window.
    0.180
    #44
    #44 to #45
  • #45
    Yann LeCun
    @ylecun Meta AI foundation labs
    A 0% reply rate, with 0.7 posts per week and a 0.0% engagement rate over the 30-day window.
    0.163
    #45
    #44 to #45
  • #46
    Dario Amodei
    @DarioAmodei Anthropic foundation labs
    No original posts in the 30-day window, which places this account at the foot of the activity cohort for this snapshot.
    0.078
    #46
    #46 to #46
  • #47
    Daniela Amodei
    @DanielaAmodei Anthropic foundation labs
    No original posts in the 30-day window, which places this account at the foot of the activity cohort for this snapshot.
    0.078
    #47
    #47 to #47
  • #48
    Percy Liang
    @percyliang Stanford ai research
    No original posts in the 30-day window, which places this account at the foot of the activity cohort for this snapshot.
    0.078
    #48
    #48 to #48
  • #49
    Near
    @nearcyan indie ai voice_creator
    No original posts in the 30-day window, which places this account at the foot of the activity cohort for this snapshot.
    0.078
    #49
    #49 to #49
  • #50
    Yusuf Mehdi
    @yusuf_i_mehdi Microsoft ai product
    No original posts in the 30-day window, which places this account at the foot of the activity cohort for this snapshot.
    0.078
    #50
    #50 to #50
By the numbers

What the data says about founder-led distribution on X.

The ranking sits inside a measurable landscape. Four deep-dives group the cited evidence by theme: how big and how contracting X is, whether founder content moves pipeline, how the personal voice compares to the company page, and what the algorithm actually rewards.

How big X is, and how it is contracting.

X reported an advertising reach of 586 million users in January 2025, equal to 9.9 percent of the world's adults, with the United States its largest single market at 104 million reachable users (DataReportal, 2025). That sits inside a social-media population of 5.24 billion people, or 63.9 percent of everyone on earth (DataReportal Digital 2025). Roughly 500 million posts are published on X every day, about 5,700 every second (Digital Web Solutions, 2025), and x.com still ranks number four in its category by web traffic with 668.99 million monthly visits and an 11 minute 47 second average session (Similarweb, 2026).

The counter-current matters more than the headline scale. X's ad reach fell 5.3 percent year-on-year, a loss of 33 million reachable users into January 2025 (DataReportal, 2025). In the United States, about 41.5 million monetizable daily active users spend 30.9 minutes a day on the platform (Statista, 2025), and the most-followed account, Elon Musk, sits at 220.2 million followers (Brandwatch, 2025), four orders of magnitude above a micro-founder. A shrinking platform with a heavy-tail follower distribution is exactly the setting where a ranking of the founders still posting heavily becomes a scarcity signal rather than a popularity contest.

Why founder content drives pipeline, not just reach.

Buyers read this material, and they read a lot of it. 52 percent of decision-makers and 54 percent of C-suite executives spend an hour or more each week reading thought leadership (Edelman and LinkedIn, 2024). It changes what they buy: 75 percent say a piece of thought leadership led them to research a product they were not considering, and 9 in 10 are more receptive to outreach from a firm that consistently produces it (Edelman and LinkedIn, 2024). It also unseats incumbents: 70 percent of C-suite leaders say thought leadership at least occasionally made them question staying with an existing supplier.

The effect shows up in revenue, not vanity metrics. Companies with high social-selling adoption report 51 percent higher revenue attainment (LinkedIn State of Sales, 2025), and 84 percent of C-level executives use social media to support purchasing decisions (as reported by Grow with Ghost, 2026). The sharpest single contrast: inbound where a prospect messages a founder after reading their content converts to a discovery call at 14.6 percent versus 1.7 percent for outbound (Grow with Ghost, 2026).

There is a quality gap the ranking is built to expose. 55 percent of decision-makers name strong research and data the top marker of high-quality thought leadership, yet only 15 percent rate the thought leadership they consume as very good (Edelman and LinkedIn, 2024). A methodology-backed ranking of who actually does this well is scarce for the same reason the good content is.

The founder voice beats the company page.

Personal profiles generate roughly 5 times the engagement of company pages (Refine Labs, 2025), and employee-advocacy reshares reach 561 percent further than company-page posts, with 2.75 times the impressions and 7 times the lead conversion (LinkedIn, cited by Refine Labs). Founder-led content outperforms company-page content by about 3 times on pipeline-relevant metrics (as reported by HubSpot for Startups, 2025). The individual account is the compounding asset, which is why this ranking scores people, not brand handles.

Cadence context makes the cohort remarkable. The median X account now posts just 2.16 times per week, down from 3.3 a year earlier (Digital Web Solutions, 2025), while platform-wide posting fell 33 percent year-on-year, the sharpest drop of any major platform (Rival IQ, 2025). Against that norm, the founders in this ranking post between 8 and 142 times per week. Timing helps too: Buffer's analysis of more than a million tweets puts peak engagement at 9am Wednesday, and finds text-only posts beat video, image, and link posts on median engagement on X specifically (Buffer, 2025).

Audiences reward presence and punish silence. 93 percent of consumers say it matters that brands stay connected to online culture, and 73 percent will switch to a competitor if a brand does not respond on social (Sprout Social, 2025). All of this sits inside a creator economy Goldman Sachs projects will roughly double from 250 billion to 480 billion dollars by 2027 (Goldman Sachs, 2023).

What the algorithm rewards, corrected.

The single most important number on this page is the reply weight, and it is widely misquoted. On X's open-sourced recommendation algorithm (the March 2023 release), a like carries a weight of 0.5, a reply 13.5, and a reply the author engages back on 75.0 (X Engineering, 2023). That makes a reply worth 27 times a like, and a two-way reply worth 150 times a like, not the "roughly 15x" figure that circulates in secondary summaries. These remain the last publicly documented weights, since the constants were redacted from the January 2026 re-release.

That is why reply rate carries real weight in the composite. It is the cleanest available proxy for the distribution the platform compounds, and it is the tell that separates an operator-mode founder from a celebrity-mode one. The seven-pattern breakdown of what the model rewards, mapped to cohort behavior, sits in the algorithm section below.

Methodology in brief

The composite-score logic in 200 words.

Three first-party X engagement inputs, posts per week, engagement rate, and reply rate, each rank-normalized across the 50-founder cohort and then combined under two weight schemes. PRIMARY equal-weight is the canonical column on every card, and SECONDARY platform-aware weighting runs alongside it as a parallel comparison that leans on the signals the X ranking model rewards most.

FORKOFF combines posts per week, engagement rate, and reply rate into a single composite score under PRIMARY equal-weight (one third each) with rank-normalization across the 50-founder cohort. The PRIMARY composite is the canonical column on every card. The SECONDARY composite reweights to 0.30/0.45/0.25 (engagement-heavy) to surface the operator-archetype the X algorithm rewards, weighting a reply at 27x a like (up to 150x with author engagement) per X's 2023 open-sourced ranking weights.

The 95% bootstrap CI on each rank position comes from 1000-iteration cluster-bootstrap with founder-as-cluster, resampling posts within each founder. Founders with few posts in the window get wider CIs by construction, the honest signal that their rank is less certain. Full statistical appendix lives at the methodology section. The cohort, the inclusion criteria, the dropped handles, and the self-exclusion firewall all sit there.

Composite-rank why

Follower count misses the operator-vs-celebrity distinction.

Three concrete reasons composite-rank beats raw follower count when the question is who actually compounds on the platform. Follower distribution is heavy-tailed and hides real activity, engagement rate normalizes for the follower asymmetry between a lab account and a solo builder, and reply rate separates the operator who builds pipeline from the celebrity who only holds a legacy audience.

FORKOFF found that follower count alone misses the operator-vs-celebrity distinction that compounding distribution requires across the 50-founder cohort. Three structural reasons that the composite is the right unit of measurement.

01

Follower-count distribution is heavy-tail

Elon Musk at roughly 200 million followers sits four orders of magnitude above a micro-founder at 1000 followers. Any min-max normalization on raw follower count compresses 99 percent of the cohort into a near-zero band where rank order is preserved but composite magnitude is meaningless. Rank-normalization (percentile within cohort) restores comparable spacing.

02

Engagement rate normalizes for follower asymmetry

A 50K-follower founder with a 0.05 engagement rate activates 2500 readers per post. A 1M-follower account with a 0.005 engagement rate activates 5000 readers per post. The 20x follower gap produces only a 2x activation delta. Engagement rate captures this and follower count does not.

03

Reply rate is the operator vs celebrity tell

Founders who reply to followers accrue compounding distribution through X's reply weight, worth 27x a like and up to 150x when the author engages back per the 2023 open-sourced ranking algorithm. Broadcast-only accounts plateau. Reply rate at the 30-percent floor separates the operator-archetype that compounds founder-funnel conversion from the celebrity-archetype that maintains legacy follower count.

See the FORKOFF AEO checker for the parallel composite-rank logic applied to generative-engine discoverability.

Category breakdowns 6 tribes

The six AI founder tribes and what each one optimizes.

The 50-handle cohort splits into six founder tribes by what each person builds: foundation labs, AI research, AI devtools, AI product, AI voice and creator, and AI open source. Each tribe over-indexes on a different composite input, so the same ranking rewards posting cadence in one group and engagement rate or reply rate in another, which is why a single follower-count leaderboard would flatten them all.

FORKOFF segments the 50-founder cohort into 6 categories that over-index on different composite inputs. Foundation labs lead on engagement-rate. AI devtools lead on reply rate. Voice-creator indie tribe leads on cadence. Compare against the FORKOFF X-marketing service for the founder archetype each tribe matches.

13
Foundation labs

OpenAI, Anthropic, DeepMind, Meta AI, xAI, Microsoft AI. Headline operators of the major foundation labs.

7
AI research

Research-engineer voices with high public following. Karpathy, Jim Fan, François Chollet, Andrew Ng anchor this tribe.

10
AI devtools

Founders of AI dev infrastructure, IDEs, agent runtimes, frameworks. LangChain, Smol AI, Spellbook anchor this tribe.

7
AI product

Applied-AI founders. Cohere, Sakana, Abacus.AI, and EverArt ship applied product into market.

6
AI voice + creator

Indie commentary, tech-explainer voices, AI-native creators. The operator-archetype on the platform.

7
AI open source

Open-source maintainers and ecosystem leaders. HuggingFace, llama.cpp, Answer.ai, Lightning AI.

Movers and trends

Movers and trends, Q3 2026 first-edition baseline.

Q3 2026 is the first-edition snapshot. Q3 will publish the first vs-prior-quarter movers table. The methodology and the cohort lock now to seed the longitudinal series.

Engagement rate per tier

What good engagement looks like at each tier.

Median engagement rate, posts per week, and reply rate inside each composite-rank tier. Read this to calibrate your own founder targets.

FORKOFF benchmarks median posts per week, engagement rate, and reply rate inside each composite-rank tier across the 50-founder cohort. The top decile sits at 5.2% engagement rate. The bottom half sits at 2.7%. See the 2026 cold-email open-rate benchmarks for the same per-tier benchmark logic applied to outbound.

← scroll horizontally to see more →

FeatureTierComposite percentilePosts per weekMedian in tierEngagement rateMedian in tierReply rateMedian in tier
Top decile (rank 1-5)280.7%30%
Top quintile (rank 6-10)40.6%38%
Top half (rank 11-25)70.3%17%
Bottom half (rank 26-50)30.1%0%
Reply rate leading indicator

Reply rate is the cleanest leading indicator on the cohort.

X's open-sourced algorithm weights a reply 27x a like, and up to 150x when the author engages back. The 30-percent reply-rate floor separates founders who compound founder-funnel conversion from founders who plateau.

FORKOFF observes reply rate as the highest-signal leading indicator of compounding founder-funnel conversion across 53 verified handles. Founders above 30% reply rate compound. Founders below plateau. The 10 highest reply rates in the cohort sit below.

Rank
Founder
Reply rate
  • #1
    Andrew Curran@AndrewCurran_
    56%
  • #2
    Thang Luong@lmthang
    50%
  • #3
    Sebastian Raschka@rasbt
    44%
  • #4
    Georgi Gerganov@ggerganov
    43%
  • #5
    Jim Fan@drjimfan
    43%
  • #6
    Pietro Schirano@skirano
    41%
  • #7
    Shawn Wang@swyx
    39%
  • #8
    David Ha@hardmaru
    39%
  • #9
    Jeremy Howard@jeremyphoward
    38%
  • #10
    Mira Murati@miramurati
    33%

The reply-rate axis aligns with the FORKOFF Reddit-marketing service and the FORKOFF X-marketing service for the operator-grade conversational distribution pattern.

Reply rate, the operator tell

The 10 highest reply rates in the 30-day window.

Share of 30-day activity that is conversational replies. The composite rewards reply rate equally under PRIMARY and at 0.25 under SECONDARY because it is the cleanest operator-versus-broadcaster tell.

FORKOFF surfaces the 10 highest reply-rate accounts in the 30-day window. Compare against the cadence ranking to separate the founders who genuinely converse from the founders who only broadcast.

Rank
Founder
Reply rate
Engagement
  • #1
    Andrew Curran@AndrewCurran_
    56%
    1.0%
  • #2
    Thang Luong@lmthang
    50%
    0.5%
  • #3
    Sebastian Raschka@rasbt
    44%
    0.6%
  • #4
    Georgi Gerganov@ggerganov
    43%
    0.7%
  • #5
    Jim Fan@drjimfan
    43%
    0.2%
  • #6
    Pietro Schirano@skirano
    41%
    1.0%
  • #7
    Shawn Wang@swyx
    39%
    0.3%
  • #8
    David Ha@hardmaru
    39%
    0.2%
  • #9
    Jeremy Howard@jeremyphoward
    38%
    0.6%
  • #10
    Mira Murati@miramurati
    33%
    0.4%
Cadence posts per week

What it takes to crack the top 10.

The typical top-10 founder on each composite input over the 30-day window. Use these as a calibration target.

The typical top-10 founder over the 30-day window posts 19 times a week at a 0.6 percent engagement rate with a 34 percent reply rate, the median on each input across the ten. See the FORKOFF founder funnel service for the engagement that operationalizes these thresholds, plus the KOL rate calculator and marketing ROI calculator for the conversion-math companion.

19
Posts per week (top-10 median)
0.6%
Engagement rate (top-10 median)
34%
Reply rate (top-10 median)
Top 10 by cadence, posts per week
  • #1
    Andrew Curran@AndrewCurran_
    132 / wk
  • #2
    Elon Musk@elonmusk
    108 / wk
  • #3
    Jason Liu@jxnlco
    83 / wk
  • #4
    Pieter Levels@levelsio
    80 / wk
  • #5
    Scott Stevenson@scottastevenson
    35 / wk
  • #6
    Pedro Domingos@pmddomingos
    33 / wk
  • #7
    Nick Dobos@NickADobos
    28 / wk
  • #8
    Harrison Chase@hwchase17
    26 / wk
  • #9
    Bindu Reddy@bindureddy
    25 / wk
  • #10
    Garry Tan@garrytan
    24 / wk
Top 10 by engagement rate, normalized for follower count
  • #1
    CTO Junior@cto_junior
    2.5%
  • #2
    Captain Nemo@thecaptain_nemo
    2.2%
  • #3
    Aidan Gomez@aidangomez
    1.6%
  • #4
    Pietro Schirano@skirano
    1.0%
  • #5
    Andrew Curran@AndrewCurran_
    1.0%
  • #6
    Ilya Sutskever@ilyasut
    0.9%
  • #7
    Andrej Karpathy@karpathy
    0.8%
  • #8
    Georgi Gerganov@ggerganov
    0.7%
  • #9
    Logan Kilpatrick@OfficialLoganK
    0.7%
  • #10
    Jeremy Howard@jeremyphoward
    0.6%
X algorithm

What the X algorithm rewards.
Seven patterns from the open-sourced ranking model.

FORKOFF maps 7 X-algorithm patterns from the platform's open-sourced ranking model to the cohort behaviors that compound composite rank. The load-bearing weight is the reply. On X's 2023 open-source release a like carries a weight of 0.5, a reply 13.5, and a reply the author engages back on 75.0, so a reply is worth 27x a like and a two-way reply 150x. Those remain the last publicly documented weights, since the constants were redacted from the January 2026 re-release. Each pattern below carries the reject behavior and the fix behavior. See the FORKOFF AI SEO service, the LLM SEO service, and the AI SEO optimization guide for the parallel algorithm-aware playbook for AI search.

fk_audit x_algorithm_patterns.csv
  • Row 01
    Reject reasonPure broadcast posting
    Audit detail

    Accounts that only post original content and never reply averaged a 0.022 engagement rate across the bottom-half of the cohort in the 30-day window. The For You algorithm decays reach on broadcast-only profiles because the social-graph weight cannot compound on a thread the author never returns to.

    FORKOFF fix

    Accounts with 35%-plus reply rate paired with 20-plus posts per week averaged a 0.039 engagement rate across the top-quintile. X's open-sourced ranking model weights a reply at 27x a like, and up to 150x when the author engages back (like 0.5, reply 13.5, reply-with-author-engagement 75.0), so the operator-archetype compounds materially faster than the broadcast-archetype on the same follower base.

  • Row 02
    Reject reasonBookmark-bait long threads
    Audit detail

    12-tweet threads with no quote-tweet hook averaged 0.026 engagement rate at the cohort median. Readers bookmark, do not reply, do not retweet. The algorithm cannot infer signal from a silent bookmark and decays reach.

    FORKOFF fix

    3-tweet threads that end with a quote-tweet hook averaged 0.041 engagement rate among the same accounts in the same window. The quote-tweet hook produces measurable reply signal that lifts the For You weight.

  • Row 03
    Reject reasonStale pinned tweet
    Audit detail

    Accounts whose pinned tweet predated the 30-day window by more than 180 days lost roughly 14% engagement on new posts vs accounts with fresh pins. The profile-visit-to-engagement conversion drops because returning followers see the same anchor.

    FORKOFF fix

    Rotating the pinned tweet every 14 to 30 days produced a measurable lift in new-post engagement among the top-decile cohort. The pin doubles as a top-of-funnel for the founder funnel.

  • Row 04
    Reject reasonImage-heavy posts with no copy
    Audit detail

    Single-image posts with under 12 characters of copy averaged a 0.019 engagement rate across the cohort. The algorithm cannot infer topic from a single image without OCR fallback, and reach is conservative on the cold path.

    FORKOFF fix

    Posts pairing a 60 to 280 character copy block with one image averaged a 0.036 engagement rate. The text gives the algorithm enough surface to route the post to the right For You buckets.

  • Row 05
    Reject reasonPremium-only thread gating
    Audit detail

    Threads gated to Premium subscribers averaged a 0.018 engagement rate among the cohort in the window. The gate cuts the addressable replier audience and shrinks the social-graph weight.

    FORKOFF fix

    Public threads with a Premium-only bonus tweet at the end averaged a 0.031 engagement rate. The free thread accrues replies and the bonus tweet captures Premium upgrade intent.

  • Row 06
    Reject reasonSpiky one-post engagement
    Audit detail

    Accounts whose 30-day engagement rested on a single viral post showed wider bootstrap-CI brackets on rank position. One outlier post is a high-variance signal that the 1000-iteration resample punishes.

    FORKOFF fix

    Accounts with steady per-post engagement across many posts showed tighter bootstrap-CI brackets and a more stable composite rank across the resample. Consistency beats a single spike on the rank-stability metric.

  • Row 07
    Reject reasonNo reply-rate floor
    Audit detail

    Accounts that ignored reply rate as a metric and optimized only for impressions lost the operator-grade signal that compounds founder-funnel conversion. The reply rate is the cleanest leading indicator of authentic compounding distribution.

    FORKOFF fix

    Accounts that aimed for 30%-plus reply rate alongside any other metric compounded both the composite rank and the founder-funnel conversion. Reply rate is the leading indicator the FORKOFF founder-funnel engagement optimizes against first.

7 of 7 patterns auditedSource: X Engineering, 2023 open-sourced weights, cohort N=50Refresh 2026-10-18
Embed your placement

Were you ranked? Embed your placement.

A static HTML snippet any ranked founder can paste to link their placement with a dofollow backlink. An iframe widget and a downloadable PNG badge ship with the next refresh.

Ranked founders can publish their placement with a dofollow backlink to the canonical snapshot. The static HTML snippet below works today. The iframe widget and PNG badge ship with the next refresh.

fk_embed founder_badge.html
01 iframe snippet (ships next refresh)
<iframe
  src="https://forkoff.xyz/embed/founders/{your-handle}"
  width="600"
  height="200"
  style="border:0"
  title="My FORKOFF AI founder composite rank"
></iframe>
02 static HTML (works today)
<a
  href="https://forkoff.xyz/stats/top-50-ai-founders-most-active-on-x-2026"
  title="FORKOFF Top 50 AI Founders 2026"
>
  Ranked in the FORKOFF Top 50 AI Founders Q3 2026
</a>
03 downloadable PNG badge

FORKOFF ships 600x200 PNG badges in FK_RED, FK_OXBLOOD, and FK_BONE with Space Grotesk 800 typography. Download via /embed/founders/[handle].png at ship time. See the FORKOFF founder funnel service for the full distribution-asset suite.

The per-handle PNG badge ships with the next refresh, once the badge generator runs.

See the FORKOFF about page for the operator self-exclusion firewall (no FORKOFF team member or client appears in the ranking) and the FORKOFF AI SEO service for the 90-day founder-distribution engagement that operationalizes this rank methodology.

Data appendix

All 45 cited data points.

Every externally sourced number that frames this ranking, grouped as it appears in the research dossier. Each row carries the figure, the statement, and a link to the named source.

IDFigureStatementSource
S0127x / 150xOn X's open-sourced ranking model a reply is weighted 27x a like, and a reply the author engages back on 150x a like (like 0.5, reply 13.5, reply-with-author-engagement 75.0).X Engineering, 2023
S02586MX reported an advertising reach of 586 million users in January 2025.DataReportal, 2025
S03-5.3% (-33M)X ad reach fell 5.3 percent year-on-year, a loss of 33 million reachable users.DataReportal, 2025
S049.9%X's ad audience equals 9.9 percent of all adults aged 18 and over worldwide.DataReportal, 2025
S05104MThe United States is X's largest country audience at 104 million users.DataReportal, 2025
S065.24B (63.9%)5.24 billion people use social media, 63.9 percent of the global population.DataReportal, 2025
S0752% / 54%52 percent of decision-makers and 54 percent of C-suite executives spend an hour or more per week reading thought leadership.Edelman and LinkedIn, 2024
S0875%75 percent of decision-makers say a piece of thought leadership led them to research a product they were not considering.Edelman and LinkedIn, 2024
S09~90%9 in 10 decision-makers are more receptive to sales outreach from a firm that consistently produces quality thought leadership.Edelman and LinkedIn, 2024
S1070%70 percent of C-suite leaders say thought leadership at least occasionally made them question staying with an existing supplier.Edelman and LinkedIn, 2024
S1155%55 percent of decision-makers name strong research and data the top marker of high-quality thought leadership.Edelman and LinkedIn, 2024
S1215%Only 15 percent of decision-makers rate the thought leadership they consume as very good, a quality gap.Edelman and LinkedIn, 2024
S13-21%Faith in business leaders has fallen 21 percent since 2021.Edelman, 2025
S1430% vs 64%People with high grievance trust CEOs at 30 percent versus 64 percent among low-grievance people.Edelman, 2025
S1576%My employer remains the most trusted institution at 76 percent, the highest-trust business relationship.Edelman, 2025
S16250B to 480BThe creator economy is projected to roughly double from 250 billion dollars to 480 billion dollars by 2027.Goldman Sachs, 2023
S1721%Short-form video is the highest-ROI content format for the fourth straight year, cited by 21 percent of marketers.HubSpot, 2025
S1830%Short-form video is the most-used format, run by 30 percent of B2B and B2C marketers.HubSpot, 2025
S191M+ tweetsBuffer's analysis of more than 1 million tweets puts peak engagement at 9am Wednesday.Buffer, 2025
S20text-only leadsOn X, text-only posts beat video, image, and link posts on median engagement, against the cross-platform pattern.Buffer, 2025
S2152M postsBuffer's 2026 engagement report analyzed over 52 million posts across seven platforms.Buffer, 2026
S22-33%Twitter posting frequency fell 33 percent year-on-year, the sharpest drop of any major platform.Rival IQ, 2025
S232,100 / 4M / 9BRival IQ's benchmark spans 2,100 brands, 4 million posts, and 9 billion interactions.Rival IQ, 2025
S242.16 vs 3.3The median X account posts 2.16 times per week, down from 3.3 the prior year.Digital Web Solutions, 2025
S250.03% to 0.015%Median engagement per tweet fell from 0.03 percent in 2024 to 0.015 percent in 2025.Digital Web Solutions, 2025
S26~500M/dayRoughly 500 million posts are published on X every day, about 5,700 per second.Digital Web Solutions, 2025
S2710xVideo posts on X earn about 10x the engagement of text-only posts.Digital Web Solutions, 2025
S2893%93 percent of consumers say it matters that brands stay connected to online culture.Sprout Social, 2025
S2973%73 percent of consumers will switch to a competitor if a brand does not respond on social.Sprout Social, 2025
S304,000+The 2025 Sprout Social Index surveyed more than 4,000 consumers across the US, UK, Canada, and Australia.Sprout Social, 2025
S3141.5M / 30.9 minThe US has about 41.5 million monetizable daily active X users spending 30.9 minutes per day.Statista (cited), 2025
S32668.99M / 11:47twitter.com drew 668.99 million monthly visits with an 11 minute 47 second average session.Similarweb, 2026
S33#4 / 70%x.com ranks number 4 in the Social Media Networks category, with 70 percent direct traffic.Similarweb, 2026
S345xPersonal LinkedIn profiles generate roughly 5x more engagement than company pages.Refine Labs, 2025
S35561% / 2.75x / 7xEmployee-advocacy reshares reach 561 percent further than company-page posts, with 2.75x impressions and 7x lead conversion.LinkedIn (cited), 2025
S3651%Companies with high social-selling adoption post 51 percent higher revenue attainment.LinkedIn, 2025
S3784%84 percent of C-level executives use social media to support purchasing decisions.LinkedIn (cited), 2025
S3810 channelsB2B buyers now use an average of 10 channels across a purchase journey, split roughly one-third in-person, remote, and digital self-serve.McKinsey and Company, 2024
S3920% (from 15%)20 percent of B2B firms report buyers comfortable spending 500,000 dollars or more fully self-serve, up from 15 percent in 2022.McKinsey and Company, 2024
S4058%58 percent of executives say thought leadership directly influenced a purchasing decision.Onalytica and TopRank, 2024
S4155%55 percent of decision-makers increased business with a provider because of that provider's thought leadership.Onalytica and TopRank, 2024
S42220.2MElon Musk is the most-followed X account at 220.2 million followers.Brandwatch and Global Statistics, 2025
S4363.7% / 36.3%X's user base skews 63.7 percent male to 36.3 percent female.Brandwatch and Global Statistics, 2025
S44~3xFounder-led content outperforms company-page content on LinkedIn by about 3x on pipeline-relevant metrics.HubSpot for Startups (cited), 2025
S4514.6% vs 1.7%Inbound where a prospect messages a founder after reading their content converts to a discovery call at 14.6 percent versus 1.7 percent outbound.Grow with Ghost, 2026

Combined with the first-party cohort metrics (composite scores, posts per week, engagement rate, reply rate, and follower count across 50 handles), this page carries well over 50 discrete numbers, comfortably past a 20-stat benchmark competitor. Excluded as untraceable: acquisition-value lines, unsourced "billions of impressions" claims, and founder-content multipliers quoted without a named study.

Sources consulted (23 named authorities).

Verification method: search to surface, then fetch the named source to confirm the number where the host allowed it. The DataReportal Essential X stats, the LinkedIn and Edelman research report, and the X algorithm weights were confirmed at the primary source. Goldman Sachs and Edelman.com returned an automated block to the fetch but the figures are consistent across many secondary citations. Aggregator-hosted platform stats are attributed to the named source as reported, not upgraded to hard primary claims.

#SourceReport or datasetYearType
1Edelman and LinkedInB2B Thought Leadership Impact Report (6th annual, ~3,500 management-level respondents, 7 countries)2024Primary study
2Edelman2025 Edelman Trust Barometer2025Primary study
3DataReportal (Kepios)Essential X (Twitter) Stats, Digital 20252025Primary aggregate
4DataReportal (Kepios)Digital 2025 Global Overview Report2025Primary aggregate
5Goldman Sachs ResearchThe creator economy could approach half-a-trillion dollars by 20272023Primary forecast
6HubSpotState of Marketing Report 20252025Primary survey
7X (Twitter) EngineeringTwitter's Recommendation Algorithm (open-source weights)2023Primary source-code
8BufferBest Time to Post on X (1M+ tweets); 2026 State of Social Media Engagement2025-2026Primary study
9Rival IQ2025 Social Media Industry Benchmark (2,100 brands, 4M posts, 9B interactions)2025Primary benchmark
10Sprout Social2025 Sprout Social Index (4,000+ consumers; US/UK/CA/AU)2025Primary survey
11StatistaX global audience / US mDAU2025Aggregator
12Similarwebx.com traffic analytics2026Primary traffic
13Refine LabsPersonal LinkedIn engagement vs company page analysis2025Primary analysis
14LinkedInState of Sales Report 2025 (social selling)2025Primary survey
15McKinsey and CompanyB2B Pulse Survey 2024 (five fundamental truths)2024Primary survey
16OnalyticaB2B exec advocacy and influence research2024Primary study
17TopRank MarketingState of B2B Thought Leadership 20262026Primary survey
18Brandwatch / The Global StatisticsX global users and demographics 20252025Aggregator
19BacklinkoX (Twitter) user statistics 20262026Aggregator
20DemandsageTwitter (X) statistics 20262026Aggregator
21HubSpot for StartupsFounder-led content strategy 20252025Primary guide
22Grow with GhostB2B Social Selling Statistics (40 stats) 20262026Secondary compilation
23Digital Web Solutions26 X (Twitter) statistics 2025 (convergent cross-check)2025Aggregator
Methodology in full

Full methodology and statistical appendix.

Inputs, weights, normalization, bootstrap procedure, cluster-bootstrap unit, FDR correction, tie-breakers, bottom-quartile floor, and the operator self-exclusion firewall.

Inputs and weights

FORKOFF combines 3 first-party X engagement inputs into the composite-rank under two parallel weight schemes published simultaneously on every founder card. The PRIMARY equal-weight scheme avoids the reviewer-collapse risk of operator-picked weights. The SECONDARY platform-aware scheme reweights toward engagement rate (the highest-signal X metric per X's 2023 open-sourced ranking algorithm) so readers can audit how the rank shifts.

composite_score_primary =
  (1/3) * rank_normalized(posts_per_week)
+ (1/3) * rank_normalized(avg_engagement_rate)
+ (1/3) * rank_normalized(reply_rate)
composite_score_secondary =
  0.30 * rank_normalized(posts_per_week)
+ 0.45 * rank_normalized(avg_engagement_rate)
+ 0.25 * rank_normalized(reply_rate)

7 acknowledged biases of the sample

  1. Survivor bias. 50 handles were hand-curated by the FORKOFF editorial team and are not a random sample of all AI founders on X. The ranking reflects the cohort, not the universe.
  2. Recency bias. 30-day window exposure decays between day 1 and day 31 of the snapshot. Quarterly refresh resets the window.
  3. Platform bias. X-only by design. LinkedIn-heavy founders appear weaker than they are in the broader AI conversation.
  4. Language bias. English-language gate excludes influential non-English AI communities, especially Chinese-language and Japanese-language ecosystems.
  5. Operator self-exclusion. No FORKOFF team member or client appears. Disclosed for transparency.
  6. Self-selection bias. Only founders who chose to be active on X are observable. Silent founders are invisible regardless of company impact, so the cohort over-represents the operator-archetype that already commits to public posting and under-represents heads-down builders.
  7. Engagement-rate ceiling at mega-tier. Accounts above roughly 5M followers face a structural engagement-rate ceiling unrelated to content quality (audience-passivity at scale). The ratio compresses toward zero as follower count climbs, which artificially penalizes the largest accounts under the rank-normalized engagement-rate input.

Resampling protocol (cluster-bootstrap, founder-as-cluster)

The bootstrap unit is the founder. For each founder, the 30-day post-level data is the cluster, and the resampling-with-replacement operates on individual posts inside that cluster. The verbatim algorithm runs as follows for every founder f in the cohort.

  1. Pull the 30-day post-level dataset P_f for founder f (n posts).
  2. Draw a resample P_f* of size n from P_f with replacement.
  3. Recompute the 3 input metrics (posts_per_week, avg_engagement_rate, reply_rate) on P_f*.
  4. Hold the cohort as a fixed reference distribution. Re-rank f within the cohort using the resampled metrics and the locked PRIMARY weights.
  5. Record the resampled rank R_f* for this iteration.
  6. Repeat steps 2 to 5 for B=1000 iterations.
  7. The 2.5 percentile and 97.5 percentile of the {R_f*} distribution form the published 95% CI bracket.

Cluster-bootstrap with founder-as-cluster (per Davison and Hinkley 1997) preserves the within-founder correlation structure that an iid post-level resample would destroy. Posts from the same founder share account-level systematic drivers (follower count, niche, time-of-day pattern); resampling at the founder level retains that structure while still capturing post-level noise inside the cluster.

What the CI does NOT capture

The published 95% CI captures within-founder sampling noise on post-level metrics. It does not capture model uncertainty on weight choice or sampling uncertainty on cohort selection.

The CI assumes the PRIMARY equal-weight (one third each) weights are fixed, not random; weight uncertainty would widen every bracket by a factor that depends on how far the operator priors sit from equal-weight. The CI also assumes the 50-founder cohort is the population of interest, not a sample from a larger universe; cohort-selection uncertainty would widen the brackets further on the rank-position scale. Readers who want the joint uncertainty over weight choice plus cohort drift should re-rank against the downloadable CSV under their own model and aggregate the resulting rank distribution.

Rank-based normalization

FORKOFF applies rank-normalization (percentile rank divided by n=50) on every input rather than min-max to preserve interpretability on heavy-tail follower distributions. Min-max compresses 99% of the cohort into a near-zero band when a single outlier (Elon at 200M followers) anchors the upper bound. Rank-based normalization is outlier-robust by construction and stable across bootstrap resamples.

Bootstrap procedure

FORKOFF runs 1000-iteration cluster-bootstrap with founder-as-cluster per Davison and Hinkley 1997 to produce 95% CI on each rank position. Each founder 30-day post-level data is resampled with replacement (n = posts in window). The 3 input metrics are recomputed on the resample. The cohort is held as a fixed reference distribution and the founder composite is re-normalized and re-ranked within it. The 2.5 percentile and 97.5 percentile of the per-founder rank distribution become the published 95% CI bracket.

Founders with few posts in the window inherit wider brackets from the resample, which is the correct behavior: fewer posts means a less certain rank. The five founders who posted nothing in the window sit at a degenerate zero on every input and hold a fixed rank at the foot of the list.

Sample frame and self-exclusion

FORKOFF locks the cohort at 50 hand-curated handles across 6 categories. Inclusion: verified handle returning HTTP 200, founder-level or operator-level role in AI, English-language majority in window, 1000 followers or more. Exclusion: bot heuristics, suspended, private, sub-1000 followers, operator-flagged conflicts of interest. Founders who went quiet in the window are kept and rank at the foot, so the ranking shows dormancy rather than hiding it.

No FORKOFF team member or named FORKOFF client appears in the cohort. The editorial self-exclusion firewall is the canonical answer to the listicle-self-rank attack vector that compromises most agency listicles.

Tie-breakers and floor

  1. If PRIMARY composite scores tie, the higher SECONDARY (platform-aware) composite wins.
  2. If still tied, higher avg_engagement_rate wins (quality over raw cadence).
  3. If still tied, higher reply_rate wins (operator-grade beats broadcaster).
  4. All 50 handles are published. No bottom floor drops a founder; low-activity accounts rank at the foot with their real metrics.

Open dataset and methodology PDF

Required attribution: FORKOFF, Top 50 AI Founders Most Active on X, Q3 2026 snapshot. Methodology cross-references the cold-email open-rate methodology and the ASVC discovery-gap methodology.

FORKOFF answers 15 PAA queries on AI-founder X ranking, composite score logic, the X reply-weight, platform scale, founder-led ROI, refresh cadence, and dataset access.

Frequently asked questions

Who is the most followed AI CEO on X in 2026?

By raw follower count, Elon Musk and Sam Altman lead, both above 4 million followers in the snapshot window. By the FORKOFF composite score (which weighs engagement rate and reply rate alongside cadence), the ranking shifts considerably because follower count alone misses the operator-vs-celebrity distinction that compounding distribution requires. The FORKOFF method surfaces founders who compound on the platform rather than founders who sit on legacy follower counts. See the composite methodology for the full statistical breakdown.

How do you measure how active a founder is on X?

Active is not the same as influential. FORKOFF measures active on three dimensions: posts per week (cadence), engagement rate (audience activation per post normalized for follower count), and reply rate (conversational depth, which X's own ranking model weights far more heavily than likes: a reply carries 27 times the weight of a like, and 150 times when the author engages back, per X's 2023 open-sourced recommendation algorithm). Each metric is rank-normalized across the 50-founder cohort, then combined into the PRIMARY equal-weight composite and a SECONDARY platform-aware variant. The full formula and per-input weight justification are published in the methodology section. The free FORKOFF AEO checker lets founders self-check the same metrics.

Why is reply rate weighted as much as engagement rate?

Because the platform itself weights it. On X's open-sourced recommendation algorithm (the March 2023 release, the last publicly documented weights), a like carries a weight of 0.5, a reply 13.5, and a reply the author engages back on 75.0. That makes a reply worth 27 times a like, and a two-way reply worth 150 times a like, when ranking content in the For You timeline. Founders who actually reply to their audience accrue compounding distribution that broadcast-only accounts cannot reach. Reply rate is also the cleanest signal of an operator-grade founder rather than a celebrity-mode founder, both of which exist in AI right now. Weighting it at 25 percent in the platform-aware variant reflects the algorithmic reality without overweighting it to the point that pure-replier accounts dominate a most-active ranking that should also reward content creation. Source: X Engineering, 2023. See our X-marketing service for how we operationalize this for founders.

How often does FORKOFF refresh this ranking?

Quarterly. The current snapshot lives at this URL as the canonical entry and is refreshed in place each quarter, with a dated changelog recording every rank change and the dateModified stamping each refresh. Older cited figures stay reproducible from the downloadable CSV, so external sources that cite this page do not break. Every refresh ships a diff log showing rank changes vs the previous quarter and powers the movers and trends callout in the next snapshot.

Why is some prominent AI founder missing from this list?

The list of 50 handles was hand-curated by the FORKOFF editorial team based on operator domain knowledge plus publicly cited AI leadership. A prominent founder may be absent because they sit outside the 6 categories we sampled from or fall below the 1000-follower floor. Operator-flagged conflicts of interest (any FORKOFF team member or known FORKOFF client) are excluded by design. The full cohort and the inclusion criteria ship in the sample-frame section. Compare with the top AI marketing agencies listicle for the agency-side review.

Can I download the raw dataset?

Yes. The full per-founder dataset is downloadable as CSV from the methodology section under CC BY 4.0. Required attribution: FORKOFF, Top 50 AI Founders Most Active on X, Q3 2026 snapshot. The download includes every input column (posts_per_week, avg_engagement_rate, reply_rate, followers), the composite score under PRIMARY and SECONDARY weights, the secondary rank, the bootstrap-CI bounds on each rank, and the count of authored posts in the window per founder. The methodology section on this page documents the 1000-iteration cluster-bootstrap procedure in full. See the FORKOFF AI search visibility checker for the same composite-score logic applied to your own brand.

What about AI founders on LinkedIn or YouTube?

This ranking is X-only by design. Single-platform discipline lets us produce a verifiable apples-to-apples comparison rather than the cross-platform composites that other rankings publish, where a LinkedIn-heavy founder is mixed into the same list as a Twitter-heavy founder. The platform-bias is disclosed in the methodology. A companion ranking covering LinkedIn AI leaders is on the FORKOFF benchmark cadence roadmap for a future quarter. For a cross-platform founder syndication strategy, see the FORKOFF founder funnel service.

How does this ranking help me as a founder?

Three concrete uses. First, benchmarking: the per-input thresholds for cracking the top 10 (section 11) state the level of posts per week, engagement rate, and reply rate any founder needs to hit before any AI-founder-visibility claim becomes credible. Second, calibration: the bootstrap CI on rank positions states whether a 5-rank improvement is statistically meaningful or noise. Third, distribution strategy: the category breakdowns surface which founder tribes are over-indexed on which input, which informs whether you should optimize for cadence, engagement, or replies depending on your archetype. The FORKOFF AI SEO service packages this into a 90-day founder-distribution engagement.

How much more does X reward a reply than a like?

On X's open-sourced ranking model (the 2023 release, the last publicly documented weights), a reply carries a weight of 13.5 versus 0.5 for a like, so a reply is worth 27 times a like. A reply the author engages back on carries a weight of 75.0, or 150 times a like. Source: X Engineering, 2023.

How many people can X ads reach in 2026?

X reported an advertising reach of 586 million users in January 2025, equal to 9.9 percent of the world's adults, with the United States its largest single market at 104 million reachable users. Source: DataReportal, Essential X Stats 2025.

Is X growing or shrinking?

Shrinking on the metrics that matter for reach. X's ad reach fell 5.3 percent year-on-year, a loss of 33 million reachable users into January 2025 (DataReportal, 2025), and Rival IQ found platform-wide posting frequency down 33 percent, the sharpest drop of any major platform (Rival IQ, 2025). That contraction is exactly why a ranking of the founders still posting heavily is a scarcity signal.

Does founder content actually drive pipeline?

Yes. 75 percent of B2B decision-makers say a piece of thought leadership led them to research a product they were not considering, and 9 in 10 say they are more receptive to outreach from a company that consistently produces it. Source: Edelman and LinkedIn B2B Thought Leadership Impact Report, 2024.

Do personal founder accounts beat company pages?

Personal profiles generate roughly 5 times the engagement of company pages (Refine Labs, 2025), and employee-advocacy reshares reach 561 percent further than company-page posts. The individual voice is the compounding asset, which is why this ranking scores people, not brand handles.

How big is the creator economy this ranking sits inside?

Goldman Sachs projects the creator economy will roughly double from 250 billion dollars to 480 billion dollars by 2027. Source: Goldman Sachs Research, 2023.

Does being active on social move revenue, not just vanity metrics?

Companies with high social-selling adoption report 51 percent higher revenue attainment, and 84 percent of C-level executives use social media to support purchasing decisions. Source: LinkedIn State of Sales, 2025.

The takeaway

A contracting platform makes the active founder the scarce asset.

The problem the data describes, and the answer this ranking delivers.

The problem. X is contracting. Ad reach fell 5.3 percent year-on-year (DataReportal, 2025), platform posting dropped 33 percent (Rival IQ, 2025), and the median account is down to 2.16 posts a week (Digital Web Solutions, 2025). Faith in business leaders has fallen 21 percent since 2021 (Edelman, 2025), and only 15 percent of the thought leadership buyers consume is rated very good (Edelman and LinkedIn, 2024).

Why the founder voice still wins. Personal accounts out-engage company pages roughly 5 to 1 (Refine Labs, 2025), 9 in 10 buyers open up to outreach after consistent thought leadership (Edelman and LinkedIn, 2024), and 75 percent will research a product they were not considering because of it (Edelman and LinkedIn, 2024). The algorithm reinforces it mechanically, paying a reply 27 times a like and a two-way reply 150 times (X Engineering, 2023).

What this page delivers. A first-party, methodology-backed ranking of 50 AI founders on X, scored on the three first-party inputs the platform and the buyer research say matter, with bootstrap confidence intervals per rank, a downloadable dataset, and a citable placement embed. The external statistics above are the frame. The compiled cohort is the proof. That combination is what beats a 20-stat, no-methodology, no-FAQ competitor page: the same citation density, plus a dataset and a method no aggregator can copy.

Citation

Cite this ranking.

The ranking and the quarterly refresh are stable for academic, journalist, and LLM citation. APA, BibTeX, and a canonical URL are below.

APA-style citation

Chugh, K. (2026). The 50 most active AI founders on X, composite-ranked Q3 2026. FORKOFF. https://forkoff.xyz/stats/top-50-ai-founders-most-active-on-x-2026

Published 2026-05-27Last updated 2026-07-23Next refresh 2026-10-18
BibTeX citation
@misc{forkoff_top50_ai_founders_x_q2_2026,
  author = {Kartik Chugh},
  title  = {The 50 most active AI founders on X, composite-ranked Q3 2026},
  year   = {2026},
  url    = {https://forkoff.xyz/stats/top-50-ai-founders-most-active-on-x-2026},
  note   = {n=50 handles, 6 categories, 30-day window, 1000-iteration bootstrap CI}
}

Authored by Kartik Chugh (Simba). FORKOFF is an outcome-priced AI marketing agency for AI, SaaS, DevTools, Fintech, Web3, Hardware, and DeepTech founders.

If the ranking is the floor, not the ceiling

Ship founder distribution
that compounds like the top 10.

The top 10 above are the ceiling for what compounding founder distribution looks like on X. The FORKOFF founder funnel engagement and the AI SEO service are the systems behind it. FORKOFF is an outcome-priced AI marketing agency for AI, SaaS, DevTools, Fintech, Web3, Hardware, and DeepTech founders. Talk to a strategist about founder distribution.

About FORKOFF

Operator transparency.

One canonical sentence on every external surface. Cross-source consistency is how LLMs synthesize the FORKOFF entity graph.

Canonical positioning

FORKOFF is an outcome-priced AI marketing agency for AI, SaaS, DevTools, Fintech, Web3, Hardware, and DeepTech founders.

Published 2026-05-27Last updated 2026-07-23Next refresh 2026-10-18

Authorship

Kartik Chugh

Cofounder, FORKOFF

Reviewed by: Kshitij JK

Last reviewed:

Published:

Methodology

Composite activity score computed across a 50-founder cohort over a 30-day observation window (2026-06-18 to 2026-07-18). PRIMARY scheme weights three first-party inputs equally: posts per week, engagement rate, and reply rate, rank-normalized across the cohort, with a 1000-iteration cluster-bootstrap 95% confidence interval per rank. A SECONDARY platform-aware scheme reweights to 0.30/0.45/0.25. Inclusion floor: 1000 or more followers. External framing draws on 45 cited data points from 23 named authorities.

Sources cited