jacob lorettson

Code generation is no longer the rate limiter; AI tools like Cursor and Claude Code make writing code cheap, moving the bottleneck to code review and product definition — creating demand for AI review agents and better product tooling.

Existing AI review tools catch syntax but miss architectural impact; the market needs review agents that evaluate system design, security boundaries, and strategic trade-offs — a whitespace for startups.

Companies that create internal AI enablement teams (building custom HR, payroll, dev tools via vibe coding) will compound efficiency faster than those buying off-the-shelf SaaS — a new org design pattern.

Legora's practice of evaluating 10 models per task weekly shows no single model dominates; the winning architecture is a routing layer that selects the best model per use case — favoring model-agnostic platforms.

As agents write code, developers need to review architecture graphs not line-by-line diffs — the next IDE is a visual system planner where agents execute against approved designs.

Just as engineers move above code, lawyers will operate above contract language — defining negotiation stance and risk tolerance while agents handle clause-level work — expanding the legal AI TAM.

Local models (Qwen, Gemma) now run on phones/laptops enabling offline coding and data sovereignty; open source prevents model monopoly and is a strategic necessity for enterprise adoption.

Without European or American open-source alternatives, the model layer risks Chinese duopoly — a geopolitical and commercial risk that demands sovereign model investment.