Why YC just backed an AI law firm

Feb 9, 2026

JP Moeller, attorney and former legal-tech engineer who co-founded AI-native General Legal. He describes building a firm that reinvests in efficiency, the Slack-first client workflow with fast AI-assisted markups, and the attorney-attention engine that triages contracts. They focus on routine commercial work like MSAs, NDAs and DPAs, explain pricing/SLAs, and contrast AI-native structure with traditional Big Law.

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INSIGHT

Attorney Attention Engine Concept

General Legal's internal system ingests client and matter context, then produces AI first-pass markups that surface issues for attorneys.
JP calls this an "attorney attention engine" that points lawyer focus to provisions that need human cognitive effort.

ADVICE

Use Slack For Faster Client Intake

Use Slack as the default intake channel to speed client communication and collaboration.
JP says Slack-first engagement yields faster, more natural back-and-forth than email and improves productivity.

INSIGHT

Reinvestment Defines AI-Native Firms

An AI-native firm reinvests most profits into efficiency and accepts outside capital to scale tools and operations.
Traditional firms typically spend only 1–2% of profits on efficiency, limiting their ability to compete with capital-backed, reinvesting firms.

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What We Covered

* General Legal’s founding story and its roots in Casetext

* JP’s unusual career path from iOS developer to Harvard Law to Big Law (WilmerHale, Cooley) to legal tech engineer

* What makes a firm “AI native” versus a traditional firm that’s adopted AI tools - and the corporate structure and reinvestment philosophy that distinguishes the two

* The practical workflow: how clients engage General Legal via Slack, send contracts, and receive AI-assisted attorney-reviewed markups within a three-hour SLA

* Pricing model: $250 for documents under three pages

* The “attorney attention engine” concept - AI handles first-pass review and context gathering, directing lawyer focus to the provisions that actually matter

* How General Legal differentiates from Atrium by targeting “run the company” work (MSAs, NDAs, DPAs) rather than “bet the company” work (priced rounds, M&A)

* The competitive landscape: not directly competing with Big Law or in-house teams, but filling a gap where neither wants to operate

* The YC experience, the $4.2M pre-seed, and the ambition to build the largest law firm in the world

* Forward-looking topics including MCP-compatible law firms, clients pre-processing contracts with ChatGPT, and the blurring line between engineers and attorneys

Key Takeaways

* The defining question for an AI native firm: are you willing to reinvest virtually all profits back into efficiency rather than distributing them to partners?

* Run the company legal work (routine commercial contracts) is ripe for AI disruption; bet the company work (M&A, priced rounds) still demands top-tier human strategic advice

* The percentage of work done by AI versus humans isn’t fixed; it depends entirely on the matter - a DPA draft might be 90% AI, while advising on GDPR compliance is 98% human

* Traditional law firms spend only 1-2% of profits on efficiency tools, which J.P. believes structurally limits their ability to compete with firms that take outside capital and reinvest aggressively

* The most important hiring criterion is still excellent lawyering - you don’t need engineer-attorneys, you need client-obsessed commercial lawyers who are willing to adopt AI workflows and help shape the tools

* Slack-first client communication is a meaningful efficiency gain over email, even before any AI enters the picture

* The corporate structure mirrors Atrium’s model: a separate law firm entity employing attorneys alongside a partner technology company, sidestepping ABS restrictions

* The long-term play is horizontal expansion across practice areas - starting with commercial contracts to earn client trust, then expanding into regulatory, litigation, and broader transactional work

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