442 named people engaged with Lambda's feed in 30 days — 112 senior decision-makers, 30 from finance and capital markets, with names, titles and companies attached. The real audience — and the real openings — are in the list below.
All 21 posts in the window were published on Lambda's own page. Here is how the content performed, and who it reached.
The read. On Lambda’s posts the gap is 101 vs 52 likes per post: business and product news outperform research, but by roughly 2×. Research is doing its job — bringing in engineers and researchers, who are the hardest segment to buy attention from. Lambda’s reach this window was 1,580 likes across 21 posts.
Ranked by an opportunity score that weights seniority and repeat engagement above raw headcount — two partners who show up every week beat eleven one-time likes. These are the accounts where attention is forming around Lambda — visible, public, and not yet committed to anyone.
Read this the right way. An account cluster is public attention, not a contract — nobody on this list has signed anything with Lambda. Interest without exclusivity is the whole ballgame: these are companies a competitor can open a conversation with before Lambda ever routes the signal.
Three or more posts inside a 30-day window — people repeatedly choosing to engage with Lambda’s content. For a competitor this is the short list: the exact people giving Lambda sustained attention, ranked by how often they show up. %d people from %d companies — %d of them senior. Across the full %d, %d engagers work at hyperscalers and vendors, led by NVIDIA (13), Amazon Web Services (6), Equinix (3), NetApp (2), Meta (2), and Supermicro.
Real names, real titles, real companies — every one verified against a live LinkedIn profile. Search, filter by seniority, and open any profile. This is the market Lambda is building, row by row.
All 442 rows — name, title, company, seniority, posts engaged, profile URL — as a CSV that imports straight into Salesforce, HubSpot, or Airtable. Free. One email.
No sequence, no drip. One email with one file attached. Want this treatment for a competitor instead? See the offer →
Reactions are cheap. Comments cost something — and they are public. Four patterns in what people wrote, ranked by how close each one sits to a purchase.
Most active voices: Jonathan Richard Schwarz (3), Muntazir Abidi, PhD (2), then Chin Kwee Koh, John Sines, Emmanuel Oluwole and Samuel Holbură with one each. The people who comment repeatedly are already in a public relationship with Lambda — the first names worth studying before you pitch the same account.
The audience isn’t only engineers. 331 of the 427 engagers (78%) sit in roles that build on, fund, buy, or sell AI infrastructure — and the finance contingent is the most distinctive pattern in the data.
Gaps in the public record — places where attention is thin or absent. Not weaknesses Lambda can't fix; openings a competitor can move into first.
17 engagers work at AI-infra vendors and hyperscalers — AWS (4), NVIDIA (2), Supermicro (2), VAST Data, Equinix, Lumen, Quanta, QTS, Microsoft Research, Meta, OpenAI. The same ICPs every other provider is chasing are already in this feed.
Lambda's own page averages 75 likes per post (~1,580 a month). Every like in the window came from Lambda's own posts, and original narrative that earns its own reach still has room to win this audience.
Research posts average 52 likes vs 101 for business and product news. Nobody is currently winning Lambda's audience with engineering depth — the hardest segment is under-served.
The audience is 77% managers and ICs, 6% C-suite/GP. Enterprise decision-makers are thin on the ground — the people who sign large contracts are reachable before Lambda builds the habit.
No visible employer clusters at most enterprise accounts, and the largest cluster (Thomson Reuters, 11) shows zero repeat engagement. Attention has not converted to commitment anywhere in this dataset.
Commercial topics Lambda touched lightly — build-vs-buy economics, enterprise infrastructure decisions — drew little visible response. Conversations a competitor could own before Lambda invests in them.
None of this means Lambda is weak. It means the market is still forming — and the attention is public. First mover on the gaps wins the conversation.
The same five motions, aimed at the account you're actually selling against.
The data is public. The edge comes from reading it first.
Every number on this page is countable. Where a figure needed a judgment call, the call is stated here.
Paste the LinkedIn page of the competitor whose audience you want to win. You get the same read back: who's paying attention, which accounts cluster, where their engagement is thin, and where they leave the door open.
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