Rosa Del Mar

Daily Brief

Issue 12 2026-01-12

Venture Market Structure: Concentration, Scaling, And Fund Positioning

  • Venture is experiencing a structural 'death of the middle' where mid-sized generalist funds are disadvantaged versus large generalists or small specialists.
  • When investors realize they were wrong about a company that is becoming a winner, a key corrective action is to re-enter later at lower ownership rather than let pride prevent participation.
  • If robotics works well, it could expand the technology-addressable market by roughly 100x.

Venture Underwriting, Ownership, And Fund Structure

  • Series A as an 'entry point' cannot be generalized as good or bad because round nomenclature now spans widely different company states.
  • The strongest software businesses create lock-in with high switching costs such that customers are effectively 'hostages' rather than voluntary customers.
  • Even if AI reduces demand for certain roles (e.g., support labor), companies may redeploy remaining human labor toward higher-touch, revenue-generating customer experiences rather than eliminating it entirely.

Spot Listing Frictions And Stalled Breadth

  • Hyperliquid’s spot ticker auctions generated roughly $25M in Q1 2025 and fell to under $1M in Q4 as auctions largely disappeared.
  • BLP is Hyperliquid’s native portfolio margin system and entered a pre-alpha rollout in late December with a 5 million USDC supply cap and USDC-only support.
  • Hyperliquid’s outsourcing listing model requires trusting third-party deployers for safe/effective builds and splits listing revenue 50/50 with deployers.

Company Specific Operating Theses Robotics Fintech Convergence And Defensibility

  • Amazon’s human headcount has been roughly flat over the last five years while robot headcount has grown around 20–30%.
  • Alliance automates about 50% of startup application review by encoding heuristics into prompts to filter out obviously weak applications rather than selecting the best ones.
  • AI coding assistants benefit early-stage startups more than large companies because context-window limits make small new codebases easier for AI to operate on than large legacy systems.