
Hosted by Erik Torenberg
Written by a model from the transcript; not yet reviewed.
This episode explores how artificial intelligence is fundamentally transforming the finance function, moving the CFO role from a backward-looking traffic cop into a proactive business enabler. Figma CFO Praveer Melwani joins a16z partners Seema Amble and Ivan Makarov to discuss how his team uses automation, from reconciling messy financial data across disparate platforms like Stripe, Ramp, and NetSuite in minutes, to running investment memos and product prototypes against simulated leadership personas during corporate development diligence. Melwani explains that while AI handles tedious data preparation and fuzzy matching, finance professionals must remain rigorous critical thinkers rather than blindly trusting AI-generated slop. The conversation highlights the emergence of decentralized builders within finance, the enduring value of Excel for foundational modeling, and why technical curiosity and data fluency are now mandatory hiring traits.
The hosts introduce the episode and set the stage for a discussion on AI’s impact on finance.
Closing remarks on how finance teams will evolve over the next 12–18 months with AI and automation.
The conversation shifts to how AI transforms finance from a regulatory role to a strategic, enabling function.
Praveer explains how Figma’s finance team is automating collections, reconciliation, and corporate development workflows using AI tools.
Discussion on the importance of hiring individuals who can use AI as a tool while maintaining critical thinking.
Exploration of the finance engineer role and the need for centralized teams to manage AI-driven automation.
Praveer stresses the need for consistent financial definitions while embracing rapid AI-driven iteration.
The hosts discuss how AI frees finance professionals to spend more time on strategy and less on reconciliation.
Discussion on whether finance efficiency will plateau or continue to improve through automation.
Exploration of Excel’s continued importance despite AI advancements.
How AI tools can help finance leaders understand and prioritize data insights.
University professors struggle to keep AI courses current with rapid model changes.
SQL queries and manual data stitchingstory
Before modern AI tools, the guest spent hours writing hundreds of lines of SQL queries and manually mapping product utilization data from Stripe.
Vibe coding products during diligencestrategy
The corporate development team uses AI to recreate and test an acquisition target's product during due diligence to evaluate the strength of their technology moat.
Simulating leadership personas for investment memosinsight
Figma's finance team created distinct AI personalities for individual executives to run investment memos against before presenting to the actual leadership team.
Reconciling T and E portfolios with AIdata
Corporate finance stitched data across Nirvan, Sip, and Ramp using AI to perform fuzzy matching on travel expenses, cutting hours of manual work down to minutes.
Data science and accounting collaborationinsight
The team leverages data scientists with accounting backgrounds who understand debits, credits, refunds, and uncollectible metrics to build more accurate automation tools.
The enduring love for Excelinsight
Despite advanced AI tools and natural language prompting, Excel remains essential because manual modeling builds deep business intuition and trust.
“I want folks that feel extremely intellectually curious. You're coming in and trying to solve and try to understand the business really well.”
“If our business complexity was staying the same, I think we probably wouldn't need the same number of people a year from now.”
“I would hope that more and more can get completely automated. I think maybe I'd start with the pieces that are like, truly deterministic, and like, how can I feed it with enough information so that I can feel that the output there, you know, is completely, completely trustworthy?”
“Like the unlock that sequel was for me is, you know, now, you know, net new unlock with like AI as a tool and capability driver for me.”
“If I were to give advice to anyone, it's like hire someone who feels a similar amount of business ownership and wants to be the, you know, an operational rigor as you as the CEO does.”
AI is moving finance from reconciling what happened last month to helping decide what the business should do next. Figma CFO Praveer Melwani argues that the best finance teams are becoming builders themselves, automating repetitive work so they can spend more time understanding customers, running experiments, and shaping strategy. Praveer joins a16z’s Seema Amble and Ivan Makarov to share what that shift looks like inside Figma, from collections and expense analysis to M&A diligence, where the corp dev team now uses AI to prototype products and simulate how Figma leaders might challenge an investment memo. They discuss why AI “slop” is a real risk, how Figma decides what to build versus buy, and why successful internal experiments eventually need a centralized systems layer to turn one-off agents into reliable infrastructure. They also get into what this means for hiring the next generation of finance leaders. Praveer’s bar isn’t simply whether someone can use AI. It’s whether they can understand the business, interrogate the output, communicate clearly, and use automation without outsourcing their thinking.
11,519 words · 4 speakers
Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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