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Sabri Eyuboglu (CTO/co‑founder of EngramLab) tweeted on 2026-06-24 that scaling…

2026-06-24 · 17:19 UTC ·@EyubogluSabri ·1 min read

Brief

EngramLab argues that scaling compute on user-specific context reduces token spend and builds persistent expertise that lowers energy per problem, enabling solving harder problems; Kleiner Perkins says its memory matches frontier systems on 1–10% of tokens, with Microsoft, Notion, and Harvey testing and founders danbiderman and Sabri Eyuboglu speaking with LMBraswell (video, 2026-06-24).

Why it matters

Sabri Eyuboglu (CTO/co‑founder of EngramLab) tweeted on 2026-06-24 that scaling compute on user context reduces token spend and builds expertise that lowers the energy required to solve problems, freeing capacity to tackle harder problems.

Key details

  • Kleiner Perkins notes EngramLab’s persistent-memory approach can match frontier systems while using only 1–10% of the tokens; Microsoft, Notion, and Harvey are already testing it, and founders dan_biderman (CEO/co‑founder) and Sabri Eyuboglu spoke with LM_Braswell in a video.
Source evidence

By scaling compute on user context, we reduce token spend. But it's about more than lowering cost. To develop expertise is to reduce the energy it takes to solve a problem, freeing capacity to solve harder problems yet
Was great chatting about this with the amazing @LM_Braswell!

Kleiner Perkins (@kleinerperkins)

The models we use every day are brilliant strangers. They forget your organization the moment a chat ends, then relearn it on the next query.

@EngramLab fixes that. It learns your world once and reuses that memory, matching frontier systems on 1-10% of the tokens.

@Microsoft, @NotionHQ, and @Harvey are already testing it within their organizations.

Congratulations to the team, and hear directly from @danbiderman (CEO and co-founder) and Sabri Eyuboglu (CTO and co-founder) with @LMBraswell ⬇️

Video

— https://nitter.net/kleinerperkins/status/2069788333937688818#m