In the Season 2 finale, Anthony Thomas and Zac Henderson are joined by Ellen Li, CFO at AI Fund, the venture studio founded by Andrew Ng that builds AI-native startups from the ground up rather than investing in deal flow. Ellen walks through how her day-to-day has shifted from formatting spreadsheets and manual research to reviewing AI output as she would a capable team member. She shares concrete builds: a folder-scanning script that has saved her team hours a week for over a year, and an investor sourcing pipeline cobbled together with Claude's MCP connectors across Apollo, HubSpot, Gmail, and more.

The conversation is grounded by a distinction worth holding onto: automation a non-engineer can do tends to live in the task, not the full workflow. Ellen is candid about the limits, including a portfolio-monitoring tool she abandoned at two in the morning after overestimating what AI-assisted coding could do for her. Her larger point is that the constraint has moved. Coding is cheap now, so the scarce skill is judgment about what to build in the first place, and where buying still beats building.

Key Takeaways

• Non-engineers can reliably automate individual tasks, but full workflows still need real engineering.

• AI is dependable on general financial analysis and weak on niche knowledge that lives outside its training data.

• Knowing what to build next is now more valuable than the ability to build it.

• Build versus buy still matters, because someone has to maintain, debug, and own what you build.

• Start by automating one workflow you genuinely hate, then expand slowly.

• Token maxing is a vanity metric; ROI and a clear North Star are the real measures.

• Treat AI output like a strong team member's draft that you still review and stand behind.

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

Ali Hussain is co-founder of Tabs, a billing and revenue recognition platform built on an AI layer that reads contracts, usage data, and product context to automate downstream billing and rev rec workflows. In this episode, Ali walks through how Tabs was purpose-built around a problem that was fundamentally unsolvable before LLMs arrived: the commercial complexity between B2B companies is too variable, too contextual, and too fast-moving for traditional automation to handle. That premise now shapes both what Tabs builds and how the company itself operates internally.

The broader conversation cuts through to something that often gets skipped in AI discussions: the cost layer. Ali makes the case that AI is already a utility, with real compute costs that most companies are still insulated from. As usage scales and vendors stop absorbing margin, that will change. Understanding AI as infrastructure, not just software, has direct implications for how operators budget for it, how they price their own products, and how they structure their teams going forward.

Key Takeaways

• AI is a utility, not a tool: compute costs are real, and CFOs will increasingly feel them as usage scales

• The revenue function has shifted from rigid, annual pricing systems to continuous, strategic negotiation enabled by AI automation

• The reporting and insight layer is where AI adds the most value in finance; deterministic, high-stakes execution still requires human traceability

• Tabs embeds a "mini AI lead" within each functional team rather than centralizing ownership, keeping adoption close to the actual work

• Ali runs without an EA: an AI agent handles scheduling, while Claude handles analysis and Gong handles call intelligence

• Design and outbound workflows are seeing some of the largest time savings, with brand-trained agents replacing hours of manual work

• Ali's one non-negotiable: first-pass writing stays human, because the thinking process behind it matters as much as the output itself

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

In this episode, Anthony Thomas and Zac Henderson are joined by Tara L. Waters, Legal Innovation Partner at Harvey. Drawing on her time as Chief Digital Officer at Ashurst, where she led one of the first firm-wide deployments of Harvey, Tara explains what changed when generative AI arrived: technology adoption in legal shifted from something operators had to push against resistance to something senior practitioners actively pulled toward.

The conversation stays grounded in operational reality. Tara walks through how successful rollouts depend on meticulous planning, cross-functional teams, and treating adoption as a true transformation effort spanning governance, training, and performance expectations. She also offers a candid view on measuring success, the limits of efficiency metrics, and why she still feels early in her own AI journey despite being a recognized voice in the field.

Key Takeaways

• AI flipped legal technology adoption from a push by operators to a pull from senior practitioners

• Successful rollouts depend on meticulous planning, cross-functional teams, and in-person activation events

• A deliberate, phased approach now dominates over enterprise-wide deployments

• Using AI as a thinking partner compresses days of mental processing into a single walk

• Define value broadly, since how people feel about the work often matters more than time saved

• The fastest way to start is to write down five tasks that annoy you and work through them with AI

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

In this episode, Anthony Thomas and Zac Henderson are joined by Laura Jeffords Greenberg, General Counsel at Worksome. Laura brings a perspective that is rare in legal leadership: a builder's mindset shaped by nearly a decade in European tech, stints at Unity Technologies and Wordsmith, and a deliberate focus on using AI to do more with less. The conversation covers how she has structured her legal workflows around Claude's skills and Coworker platform, why AI caught things two humans missed in a settlement review, and how she thinks about the real constraints of using general-purpose AI tools in a regulated environment.

What makes this episode distinct is Laura's refusal to treat AI as a productivity shortcut layered on top of existing habits. Her approach is structural: identify what needs to happen legally, build the skill or plugin to handle it, and reserve human judgment for the work that actually requires it. That reframing has implications well beyond legal teams, for any function trying to figure out where AI creates genuine leverage and where it still falls short.

Key Takeaways:

• AI can outperform two human reviewers on accuracy, not just speed: Laura's settlement review took seven minutes and surfaced errors neither she nor her colleague caught

• Skills in Claude Coworker are essentially structured prompts; start by building one workflow that already lives in your head and give it to AI to execute

• Wrapping individual skills into a plugin creates a reusable legal command center without requiring constant manual setup

• General-purpose AI tools have real limits in regulated environments: audit trails, confidentiality, and privilege are legitimate constraints, not excuses to avoid adoption

• Team structure should lead into individual strengths, not try to lift weaknesses; AI removes the work people hate, freeing up the work they're actually good at

• Curiosity is the foundational skill; if you cannot use AI at work, use it personally until the instinct to reach for it becomes automatic

• Agents are the near-term frontier: skills will evolve into agents that communicate with each other and resolve tasks with minimal human input

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

Preet Gill, EVP at Lockton and head of the firm's global technology practice, joins Anthony Thomas and Zac Henderson to discuss how the world's largest privately held insurance brokerage is embedding AI across both client-facing and internal operations. The conversation covers Lockton's structured approach to AI adoption, from a formal governance group to day-to-day workflow automation, and how being independent and privately held gives them room to move faster than legacy competitors.

The episode takes a sharp turn into territory rarely covered on the show: what AI means for insurability itself. Drawing on his work building coverage frameworks for autonomous vehicles and cyber risk, Preet makes the case that AI liability is on the same trajectory as cyber insurance and will become its own distinct coverage category, underwritten around performance rather than failure.

Key Takeaways:

• Lockton runs two parallel AI tracks: an external client advisory hub and an internal associate productivity hub

• AI analyzing existing data and documents is more reliable than generative tasks; hallucinations drop when the model is given structured, task-specific data

• A proposal and presentation builder tool is saving Lockton teams 1 to 2 hours per week, with formal measurement now in place

• Team roles are shifting from producing raw content to interpreting outputs, challenging AI results, and applying judgment

• Governance investment should come early, particularly in regulated industries; data usage policies and acceptable-use guidelines need to precede broad deployment

• AI liability insurance will follow the same path as cyber: starting as a clause inside general liability, then becoming its own underwriting category as claims precedent builds

• The key risk in algorithmic decision-making is underperformance, not outright failure, which requires fundamentally different coverage design

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

In this episode, Anthony Thomas and Zac Henderson are joined by Jasmine Singh, General Counsel at Ironclad, the leading contract lifecycle management platform. Jasmine shares how her legal team is using AI across contract review, compliance analysis, employment law workflows, and team management, while maintaining the governance structures necessary to do it responsibly at scale.

The conversation gets at something most AI discussions in legal avoid: the tension between a lawyer's instinct to minimize risk and the organizational cost of being the source of friction. Jasmine's approach flips that framing, using the duty of competence as the argument for adoption, not against it.

Key Takeaways:

• A tiered governance model (some tools freely, some with enterprise controls, some off-limits) is more effective than blanket AI restriction

• Legal ops must be involved for AI to scale beyond individual use, playbooks, prompts, and frameworks require active management

• Ironclad's Jurist generates surgical, playbook-driven redlines that mirror how humans actually negotiate, preserving goodwill with counterparties

• AI frees lawyers from reactive, volume-driven work and creates space for more strategic, business-aligned legal advice

• Success metrics worth tracking: minutes saved per contract, deal cycle time, legal ticket deflection, and team AI usage rates

• For lawyers who have never used AI, start with summarization and synthesis on a document already in front of you

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

In this episode, Anthony Thomas and Zac Henderson are joined by John Glasgow, the CEO and CFO of Campfire. John shares how AI has changed both his own workflow and the way Campfire operates as a company, from finance and forecasting to internal tooling and team adoption. What stands out is not just the speed, but the shift from AI as a prompt-based helper to AI as a more autonomous teammate that can review work, surface insights, and deliver first drafts across the business.

The conversation also highlights an important distinction for finance teams: AI does not replace rigor. John explains how Campfire reduces hallucination risk, where human review still matters, and why strong judgment is becoming more important, not less. The result is a practical look at how a fast-growing company is using AI to increase leverage, improve output, and push every function to become more systems- and AI-forward.

Key Takeaways

• Campfire treats AI as a teammate, not just a tool

• AI helps finance teams move faster, but human review still matters

• Claude, Co-work, and agent workflows are creating real internal leverage

• Teams are building custom apps and workflows for their own needs

• Campfire prioritizes AI adoption and learning over short-term cost concerns

• The real shift is from pulling data manually to acting on insights faster

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

Season two opens with Anthony Thomas and Zac Henderson reflecting on what stood out most from their first season of conversations. Rather than focusing on hype, they revisit what guests actually showed in practice: AI is helping people do better work, free up time, and create more space for thinking, collaboration, and family life.

The episode also serves as a reset on what is actually working right now. Anthony and Zac compare how they use tools like ChatGPT, Claude, Gemini, NotebookLM, Perplexity, and agent-based systems in their own work, while also acknowledging the frustrations that come with today’s tools, from hallucinations to clunky workflows and rising usage costs.

Key Takeaways

• Season one showed that AI is helping people create more human time, not less

• Simple, thoughtful use cases often create more value than complex AI setups

• Anthony and Zac now use different models for different strengths, from thought partnership to execution and research

• NotebookLM remains one of the most practical tools for organizing and querying large sets of information

• AI can create real leverage, but issues like hallucinations, poor outputs, and tool costs still require careful oversight

• Their recommendation for listeners is simple: try one practical tool this week and build from there, rather than waiting to become an expert

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

In the season finale, Anthony Thomas and Zac Henderson are joined by Stephanie Corey of UpLevel Ops to explore practical, high-impact AI use cases for legal operations. Steph explains how AI has fundamentally changed how her team works, helping them stay organized, capture institutional knowledge, and support more client work without adding headcount.

The conversation stays grounded in operational reality: start small, solve annoying repetitive problems first, and use AI to clear space for more strategic work. Rather than replacing legal judgment, Steph shows how bots, note takers, and structured workflows can reduce administrative burden and make legal teams faster, smarter, and more responsive.

Key Takeaways

• AI helped UpLevel Ops scale work without adding headcount

• Note takers and bots improve knowledge capture and retrieval

• Start with small, high-friction tasks

• Bots can automate intake and reduce routine legal work

• Pilot programs with clear metrics drive adoption

• Custom writing assistants are a strong starting point

• Steph also shared three custom GPTs: UpLevel Your Gift Giving Assistant for personalized gift ideas, Wanderlust Travel Guide for itinerary planning, and Master Chef for turning fridge or pantry ingredients into recipes.

UpLevel Your Gift Giving Assistant: https://chatgpt.com/g/g-673a67deb2d88191a40a3ef4b9e2256f-uplevel-your-gift-giving-assistant

Wanderlust Travel Guide: https://chatgpt.com/g/g-eDSeep6qT-wanderlust-travel-guide

Master Chef: https://chatgpt.com/g/g-oVwrdPo0I-master-chef

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.

Tommie Tavares-Ferreira returns to discuss how quickly agent-based workflows are evolving and what has changed since her last appearance. The conversation centers on OpenClaw-style autonomous agents, how teams are experimenting with dedicated servers and guardrails, and why organizations are beginning to treat AI agents as a “digital workforce.”

The discussion moves beyond tooling into organizational impact, including how companies may soon manage both human and digital workers side by side. Tommie highlights how the shift from reactive prompting to persistent agents is creating leverage across operations while introducing new questions around security, ownership, and workforce structure.

Key Takeaways

• Agents shift AI from reactive prompts to proactive work

• Teams are testing dedicated environments and guardrails

• “Digital chief of staff” agents can manage tasks and workflows

• New roles are emerging to coordinate AI agents

• Creativity and ideas gain value as execution is automated

• “Digital workforce management” may become a new software category

About the Podcast

The A to Z of AI is hosted by Anthony Thomas and Zac Henderson and powered by The Suite. The show explores real-world AI use cases across industries, focusing on practical workflows, tools, and lessons learned from operators using AI in their daily work.