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a16zHow AI Is Turning Figma’s Finance Team Into Builders
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At a glance
WHAT IT’S REALLY ABOUT
AI pushes Figma finance from reporting to building automated systems
- The conversation argues that AI is pushing finance leaders toward building automation and systems, repositioning finance as an operational, insight-generating partner rather than a compliance “traffic cop.”
- Praveer Melwani describes how earlier automation at Figma relied on heavy SQL and data-table creation to standardize definitions and enable faster, more trustworthy cross-company decision-making.
- Figma’s finance-adjacent teams are using AI for workflow automation (like credit and collections) and faster diligence and memo iteration (including leader “personalities” to pre-review investment memos), while also managing the risk of low-quality “slop.”
- The speakers emphasize that the biggest unlock is still data integrity and consistent metric definitions, and that organizations need mechanisms to centralize and productize bottom-up agent prototypes.
- They discuss how automation can free finance teams to spend more time on strategy, experimentation, and storytelling, while core finance skills—judgment, communication, and business understanding—remain essential.
IDEAS WORTH REMEMBERING
5 ideasAutomation shifts finance from “traffic cop” to operational business enabler.
He says his own leverage at Figma came from building in SQL, creating “golden tables,” and getting consistent metric definitions into recurring ETL so teams could stop arguing about what’s true and focus on decisions.
Great finance hires still need fundamentals—AI just raises the bar for accountability and comprehension.
He looks for intellectual curiosity, data fluency, strong questioning, and clear communication, and he uses a case study to test whether candidates use AI tools without “outsourcing” their thinking or losing model understanding.
Finance teams are automating concrete workflows, not just writing faster documents.
He describes a credit-and-collections workflow rebuilt into a tied-in, homegrown system (invoice tracking through reconciliation to NetSuite), and corp dev using “vibe coding” to pressure-test diligence and speed iteration.
“AI slop” is a real risk, so teams need standards and intentional review.
He notes internal policies around marking AI-written content and emphasizes that anything you ask others to read consumes time; he also highlights that much of the real work is getting data into the right place.
The path forward is turning one-off agents into shared, maintained systems.
He argues specialists should prototype because they know “what good looks like,” but a strong CIO/systems function should productize what works, manage dependencies, and make tools durable beyond the original builder.
WORDS WORTH SAVING
5 quotesI've always felt like the, the role of a finance individual should be this operational leader.
— Praveer Melwani
You don't wanna outsource your thinking today.
— Praveer Melwani
Anything that you're putting out there that you're asking someone to consume, it's gonna take them time, effort, and energy.
— Praveer Melwani
Ninety-five percent of the challenge there is just, like, getting your data in the right spot.
— Praveer Melwani
If our business complexity was, like, staying the same, I think we probably would- wouldn't need the same number of people a year from now.
— Praveer Melwani
SPEAKERS
Praveer Melwani
guestCFO at Figma, focused on modern finance operations and automation.
Seema Amble
hosta16z podcast host and investor covering software and company building.
Ivan Makarov
hosta16z partner who advises portfolio companies on operations, finance, and scaling.
High quality AI-generated summary created from speaker-labeled transcript.
