What does it mean to be a valuable lawyer in the age of AI? In this episode, Zach sits down with litigator, technologist, and AI evangelist Damien Riehl to explore how legal expertise evolves, not disappears, in a world of generative models and automation. From his unique path as both a practicing attorney and self-taught coder to his widely discussed “All the Music” project, Damien argues that the future belongs to lawyers who understand systems, leverage technology, and rethink what clients actually pay for. This is a conversation about professional reinvention, leverage, and why AI may amplify - rather than replace - the best lawyers.

In this episode:

Zach checks in with second-time guest, Spellbook CEO, Scott Stevenson for a wide ranging conversation on some of the hottest topics of the day:

Why positioning AI for Legal as a two horse race is deeply flawed

The benefits of selling direct to lawyers as opposed to Chief Innovation Officers

In-house legal buyers versus law firms

BigLaw versus small and medium size law firms

In this episode:

Will LLMs Kill LegalAI or Legacy SaaS

Vibe coding vs enterprise software

Zach announces that, for the first time since ChatGPT launched, he's investing in a legal AI startup. In this episode, he's joined by Nick Fleisher, CEO of Sandstone, to unpack why in-house legal teams, not law firms, may be the biggest winners of the AI era. Drawing on Nick's background at McKinsey where he advised law firms on AI, the conversation explores why legacy tools are failing lawyers and how AI can solve a problem that plagues in-house teams: working seamlessly with their business without slowing them down and being a bottleneck.

In this episode:

Why Zach decided to invest in a legal AI startup now

What in-house legal teams actually need from AI

Why CLM tools struggle with adoption and ROI

How AI changes legal’s relationship with the business

Measuring success beyond “time to contract”

Why vertical legal software beats generic AI tools

What makes Sandstone different from Harvey, Legora, and CLMs

References:

$10M Seed Round Announcement

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Zach speaks with Cecilia Ziniti, founder and CEO of GC AI, about why in-house legal teams are often ahead of law firms when it comes to adopting AI - and what that signals for the future of the profession. Drawing on her experience as a former general counsel and AI leader, Cecilia explains why legal AI must be purpose-built for real workflows, how trust and precision shape adoption, and why lawyers who learn to work with AI will gain a lasting edge.

In this episode:

Why in-house legal teams are leading AI adoption

The limits of generic AI tools for legal work

What lawyers actually need from AI systems

Trust, accuracy, and citations in legal AI

How AI is reshaping legal workflows and roles

What it means to be an “AI-native” lawyer

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Zach sits down with NetDocuments Chief Product Officer Dan Hauck to unpack how AI is truly being used inside law firms and in-house legal teams today - from large-scale document profiling to agentic assistants that search, summarize, and edit directly within the DMS. Recorded live at ND Inspire conference, Dan explains why lightweight models are unlocking new automation, how in-house teams are often leading on adoption, and why the real ROI of legal AI goes beyond efficiency to include better onboarding, less isolation, and more confident decision-making for lawyers at every level.

The biggest changes Dan has witnessed after 8 years of the Inspire conference

How firms are using AI at scale — not just on pilot use cases

Why automated document profiling is now possible across millions of docs

Understanding small models vs. large models in legal workflows

How AI pipelines classify, extract, and enrich metadata instantly

New use cases emerging inside the DMS (repapering, diligence, discovery, onboarding)

Why in-house teams are often ahead of firms in AI adoption

How agentic AI assistants reduce loneliness and cognitive overload

The ROI debate: real numbers vs. intangible benefits

What lawyers gain: better focus, faster context loading, and stronger client service

Why this moment feels like a once-in-a-generation shift in legal technology

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Zach talks with Jen Berrent, former WeWork executive and founder of Covenant, an AI-first law firm reimagining how deals get done. They dive deep into what it means to build a law firm from the ground up around artificial intelligence — not as a tool, but as the foundation. Jen shares her perspective on why too much work still runs through Big Law, how AI is transforming the middle tier of legal work, and what it takes to balance human expertise with machine efficiency.

In this episode:

What an “AI-first” law firm actually looks like

How Covenant is redesigning legal workflows from scratch

The problem with Big Law’s “too much work, too few alternatives” model

Why reading comprehension is AI’s legal superpower

Building client trust in the age of automation

How AI can accelerate deals — without sacrificing rigor

The difference between a “relationship ramp” and a “SaaS snowball”

The challenges (and advantages) of raising funding in legal AI

Lessons from Robin AI’s struggles — and why clarity of business model matters

Why this is a once-in-a-generation moment for lawyers who want to innovate

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The origin story of Harvey and how it became the “Dallas Cowboys of Legal Tech”

Lessons from the early days of AI at Google Brain and DeepMind

Why the real opportunity isn’t automation — it’s amplification

How top law firms are already using AI for high-level strategic work

The emerging hybrid model of AI + human legal reasoning

Why firm size and structure could shift dramatically in the next decade

Rethinking ROI: morale, retention, and client trust as key performance drivers

How Harvey is helping firms pitch, collaborate, and win new business

The future of AI-first law firms — from pricing models to client partnerships