Network Engagement Analysis
Lambda
Lambda
The Superintelligence Cloud · 56,494 followers
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Who’s engaging with
Lambda

487 AI builders, founders, and capital-markets operators engaged with Lambda’s LinkedIn feed across 20 posts in the last 30 days. This is who they are — names, titles, and the companies they work for.

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Data collected September 2, 2026 · 487 engagers from 20 posts · 30-day window (Aug 3 – Sep 2, 2026)
👥
📊
📝
⚡
Engagers
487
Posts
20
Reactions
789
TOP ENGAGERS
BKBruce K Lee
Bruce K Lee
BKBaizak K.
Baizak K.
TFTom Ferrara, AIF, FPS, CRPS, MBA
Tom Ferrara, AIF, FPS, CRPS, MBA, Varsity Financial Coaching
JJJason Johnson
Jason Johnson, Velvet Ventures
KAKsenia Anske
Ksenia Anske
0
Unique Engagers
0
Posts Analyzed
0
Reactions Captured
The Network

487 people who showed up

Real names. Real titles. Real companies. Click any card to open their LinkedIn profile. Search by name, title, or company — filter by reaction type.

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487 people match
The Inner Circle

55 people engage with almost everything Lambda posts

These engagers show up across 3+ posts in the window — a 30-day snapshot. They’re not casual scrollers: they’re wealth managers treating GPUs as an asset class, AI-infra operators, founders, and researchers who track the company closely. Highest-trust relationships in the dataset.

Most consistent engagers — ranked by posts engaged
BKBruce K Lee
Bruce K Lee
Founder and CEO, Keebeck Wealth Management · 12 posts
BKBaizak K.
Baizak K.
AI Hardware & RMA | NVIDIA HGX | H100 | H200 | B200 | B300 | GPU Servers | Linux | Hardware Diagnostics · 11 posts
TFTom Ferrara, AIF, FPS, CRPS, MBA
Tom Ferrara, AIF, FPS, CRPS, MBA
Varsity Financial Coaching · Chief Education Officer at Varsity Financial Coaching Financial Literacy and Wellness Advocate · 11 posts
JJJason Johnson
Jason Johnson
Velvet Ventures · Managing Partner at Velvet Ventures and Fermi 42 Ventures · 11 posts
KAKsenia Anske
Ksenia Anske
Superintelligence Technical Content Marketer · 10 posts
A(Andrzej (AJ) Ejsmont
Andrzej (AJ) Ejsmont
Executive | Investor | Advisor | Strategy | Growth | Brand | AI/Tech | Space | Life Sciences | Robotics | Agentic | Quantum Computing | Superintelligence | Sports | Ex-McKinsey | Harvard | Cambridge | Cornell · 10 posts
QKQuinn K.
Quinn K.
AI/ML Cloud Infrastructure - Capital Markets, Systematic & Algorithmic Trading · 10 posts
WLWilliam L.
William L.
Cal. State University · Statistics, Bachelor’s of Science: Data Science Concentration @ Cal. State University, East Bay · 10 posts
RARyan A. Raji
Ryan A. Raji
Investor | Venture Capital | Real Estate · 9 posts
MFMichael Falcon
Michael Falcon
Advisory Board, Board Member and Partner · 9 posts
JMJonathan Michels
Jonathan Michels
White & Case · Partner at White & Case LLP · 8 posts
MMMao Molly Yu
Mao Molly Yu
Corporate Controller AppZen, CPA (active), D&T Alumni · 8 posts
JSJohn Sullivan
John Sullivan
Managing Director, Business Development - Central and Western Regions · 8 posts
SOSanghwa Oh
Sanghwa Oh
GPUaaS Sales · 7 posts
JWJohn Warta
John Warta
Founder, NextNet Investments, Inc. · 7 posts
JEJon Eckhard
Jon Eckhard
Accomplished sales director with a history of success and experience leading business development efforts. · 7 posts
DHDoug Hamelberg
Doug Hamelberg
Senior Executive in Management Consulting | Corporate Finance | Enterprise Technology | Performance Management and Customer Success · 7 posts
MBMichael Brown
Michael Brown
Colocation, Telecommunications (Optical Networking, Dark Fiber) · 7 posts
Where They Work

The companies showing up most

Engagement clusters by employer — when multiple people from one company engage, that’s an account-level signal, not a bunch of unrelated likes.

🏢
Top companies by engager count
Thomson Reuters ↗
11 engagers · 2 senior
Aws ↗
4 engagers · 2 senior · 1 repeat
University ↗
3 engagers
Cmu ↗
3 engagers
Supermicro ↗
2 engagers · 1 repeat
Gradient ↗
2 engagers · 1 senior
Sbs Comms ↗
2 engagers · 1 senior
Nvidia ↗
2 engagers
Thomson Reuters, Morgan Stanley, and a long tail of wealth managers and VCs are engaging Lambda’s feed in numbers no other neocloud is pulling — the capital markets are watching compute become an asset class.
Target Accounts

The account-level opportunities

When multiple people — especially senior people — from one company engage, that’s an account signal, not a stray like. Ranked by engagers, seniority, and repeat engagement.

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Ranked by opportunity score
Thomson Reuters ↗11 engagers · 2 senior · 0 repeat
Gary Bisbee, CFA, Rick Dauk
Aws ↗4 engagers · 2 senior · 1 repeat
Fiachra Groarke, Alex Mirarchi
Morgan Stanley ↗2 engagers · 2 senior · 0 repeat
Cody Gunsch, Lauren Garcia Belmonte
Varsity Financial Coaching ↗1 engagers · 1 senior · 1 repeat
Tom Ferrara, AIF, FPS, CRPS, MBA
Velvet Ventures ↗1 engagers · 1 senior · 1 repeat
Jason Johnson
Vast Data ↗1 engagers · 1 senior · 1 repeat
John Farcich
Crescent Cove Advisors ↗1 engagers · 1 senior · 1 repeat
Jun Hong Heng
Leblanc Financial Alliance ↗1 engagers · 1 senior · 1 repeat
Scott Beaty
These aren’t individual leads — they’re accounts with multiple senior people already paying attention. That’s where outreach stops being cold.
Content Appetite

Research & ideas vs. business news

Do people engage with Lambda’s technical work, or with its business momentum? Research notes and financing news pull different crowds — here’s who shows up for each.

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Who engages with what
525
Research / ideas only — 251 (48%)
Business news only — 203 (39%)
Both — 71 (13%)

13 of 20 posts is research or technical point-of-view (AgentFlow, world models, orchestration) — the volume play that keeps builders in the feed. Business news is the reach play: the $926M term loan and Jensen Huang’s AI-factories post pulled more likes than the research posts combined. The two audiences barely overlap — a content mix that widens the net but doesn’t deepen it.

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Likes per post, by type

Blue = research / ideas · Purple = business news. Research pulled 1,430 likes — business news pulled 19,452.

44
08-03
E
52
08-05
E
63
08-11
E
18653
08-12
C
325
08-12
C
793
08-13
E
43
08-13
E
83
08-14
E
38
08-17
E
39
08-19
E
24
08-21
C
14
08-21
E
45
08-24
E
159
08-24
E
24
08-25
E
20
08-26
C
33
08-27
E
270
08-27
C
106
08-28
C
54
08-31
C
What They’re Saying

The comments reveal the relationship

53 comments captured from 48 people in the window. A comment is a name in public — the strongest engagement signal of all.

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Most active voices
Jonathan Richard Schwarz
3 comments
Muntazir Abidi, PhD
2 comments
Chin Kwee Koh
1 comments
John Sines, MBA, PE
1 comments
Emmanuel Oluwole
1 comments
Samuel Holbură
1 comments
🗣
Four ways people comment
Buying intent“Need 128 nodes by Nov 26 — DM” — direct capacity demand stated in a public comment. Every one of these is a hand raised.
Substance“that $40k/month AWS bill is a familiar starting point. Lambda’s $926M GPU loan shows how compute is now treated as long-term infrastructure” — practitioners debating the financing model in public.
Technical peer review“Under half a million in compute to get frontier competitive is the number that should force a buy versus build conversation” — engineers and researchers stress-testing Lambda’s open-model findings, with real opinions.
Community“This was a good one!” — Hamel Husain on the build-vs-buy post. Recognizable operators amplifying Lambda content to their own networks.
The commenters aren’t a random crowd — they’re capacity buyers, AI-infra finance people, and respected builders. Every comment is a warm conversation waiting to happen.
Network Composition

Who is this network — and does it fit your ICP?

Lambda sells AI infrastructure to builders, enterprises, and the capital markets that fund AI factories. Its content pulls a specific crowd: AI/ML engineers and researchers, founders, GTM operators — and an unusually heavy finance contingent watching GPUs become an investable asset class. Here’s how its 487 engagers break down.

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Seniority Breakdown
Manager / IC
77%
Founder / CEO
9%
VP / Director
8%
C-Suite / GP
6%
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Role Focus
AI/ML Engineering
20%
Founders & Executives
12%
Finance & Capital Markets
10%
GTM & Marketing
9%
Research & Academia
7%
IT & Infrastructure
6%
Product & Design
3%
Executives & Leaders
4%
Other
29%
🏢
Where They Work
Thomson Reuters
100
Aws
36
University
27
Cmu
27
Supermicro
18
Gradient
18
Engagement Depth

How the network engages

Reaction mix tells you the *type* of attention Lambda’s content gets. The repeat rate tells you who’s actually paying attention vs. passively scrolling.

👍
LIKE
687
87.1% of reactions
👏
PRAISE
71
9.0% of reactions
❤
EMPATHY
16
2.0% of reactions
💡
INTEREST
15
1.9% of reactions
Engagement pattern — depth of relationship
Single post
80%
2–3 posts
12%
4+ posts
8%
What Drew Them In

The content that built this network

20 posts on Lambda’s page feed analyzed (Aug 3 – Sep 2, 2026). Research and engineering notes are the volume play; the $926M term loan and the AI-factories-as-asset-class moment pulled the biggest engagement of the window.

1
“A new asset class is being born. AI factories are becoming investable infrastructure. The capital markets are …”
Jensen Huang2026-08-12
18653 likes · 781 comments · 865 shares
18653
likes
2
“We've just made a major finding for SovereignAI 🚨: Take any open-weight model (here: Qwen3.5-397B), apply our …”
Jonathan Richard Schwarz2026-08-13
793 likes · 26 comments · 74 shares
793
likes
3
“Lambda has priced a $926 million senior secured term loan B facility, the first investment-grade-rated term lo…”
2026-08-12
325 likes · 10 comments · 30 shares
325
likes
4
“🎙️ Full tech report on how to actually achieve SovereignAI, from data to model training, values, infrastructur…”
Jonathan Richard Schwarz2026-08-24
159 likes · 11 comments · 30 shares
159
likes
5
“An AI learning Tetris taught us more about agent infrastructure than its score did. At the Agentic AI Summit, …”
2026-08-14
83 likes · 1 comments · 2 shares
83
likes
6
“How much power does the AI buildout actually take? Lambda co-founder and CTO Stephen Balaban put a number on i…”
2026-08-31
54 likes · 3 comments · 1 shares
54
likes
7
“AI teams are about to relearn a basic infrastructure lesson: not every workload needs your most expensive comp…”
2026-08-24
45 likes · 0 comments · 4 shares
45
likes
8
“A humanoid policy has to work beyond the environment where it was trained. Testing one can require thousands o…”
2026-08-21
24 likes · 0 comments · 0 shares
24
likes
9
“Lambda has closed a $926 million senior secured term loan B facility, the first broadly syndicated, investment…”
2026-08-27
270 likes · 1 comments · 10 shares
270
likes
10
“Lambda’s biggest pivot started with a $40K/month AWS bill. Stephen Balaban joins Ollie Forsyth on New Economie…”
2026-08-28
106 likes · 2 comments · 4 shares
106
likes
What This Data Tells You

Four angles worth acting on

This isn’t a list of likes. It’s a map of commercially relevant relationships forming in public — and most of them aren’t being worked.

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The network is real and it’s big
487 verified engagers · 789 reactions · 20 posts in 30 days — and 20,882 likes, 842 comments, 1031 shares across the feed. No bots, no bought followers — every name here checked against a real profile with a real headline.
🎯
71% of engagers match a Lambda-relevant profile
342 of 479 people are AI/ML builders, founders, capital-markets operators, or GTM leaders — the people who buy compute, fund AI factories, or sell into them. The feed is a weekly meeting with Lambda’s own market, and most of those people are just names on a like list.
🎖
Decision-makers are already in the room
109 senior engagers — 41 founders/CEOs, 29 C-suite/GPs, 39 VPs/Directors — plus 46 finance & capital-markets people. The people who write checks for compute are engaging weekly — and they’re not being captured.
🔁
55 people never miss a post
95 people engage 2+ times and 55 engage 3+ times in 30 days. That’s not traffic, that’s relationship formation — high-trust, high-frequency attention from people who track Lambda closely. These are conversations waiting to happen.

The question isn’t whether people engage with Lambda’s content. It’s who’s engaging that nobody’s working.

So What

What you’d actually do with this

Data is only as good as the decision it changes. Here’s the same analysis, read two ways.

🧭
If you’re Lambda’s revenue or GTM team

This is a live map of who your LinkedIn feed actually reaches: 487 named people, including 41 founders/CEOs, 29 C-suite, 39 VPs/Directors, and 46 finance & capital-markets operators. Every one of them is a warm account signal — none of it is in your CRM.

Thomson Reuters is the account to watch — 11 engagers, 2 senior. And 71% of the audience matches Lambda’s own market, yet that attention isn’t being scored, routed, or converted. Whoever works these relationships first, wins them.

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If you’re selling to Lambda — or into its orbit

Lambda’s feed is a public roster of the AI-infra ecosystem: 98 engineers and researchers, 41 founders, and a finance contingent (Morgan Stanley, Thomson Reuters, wealth managers) that no other neocloud attracts. The people who build on, fund, and cover Lambda’s infrastructure are commenting weekly with names and titles.

55 people engage with 3+ posts in 30 days — the committed core tracking the company. And comments show real demand signals (“Need 128 nodes by Nov 26 — DM”). The relationship layer already exists; the missing piece is a system that turns public engagement into routed pipeline.

Who’s engaging with your posts that you’re missing opportunities with?

SignalScout turns any LinkedIn profile’s engagement into a ranked, filterable map of the people who actually show up — with names, titles, companies, seniority, and one-click LinkedIn links. The data is already in your feed. This is what it looks like analyzed.

Get Your Own Network Analysis → View Lambda on LinkedIn ↗