How Maxima moved upmarket from 10-person startups to 500-1,000 employee companies after early customer feedback | Yogi Goel (Maxima)

Maxima is building AI agents that automate enterprise accounting while maintaining the auditability and control standards finance teams require. In a recent episode of BUILDERS, we sat down with ⁠Yogi Goel⁠, CEO and Co-Founder of ⁠Maxima⁠, to explore his eight-year journey at Rubrik from Series C through IPO, and how those lessons shaped his approach to solving the 70-80% of finance time currently wasted on manual work.Topics Discussed:Why Rubrik's approach—entering stagnant markets with first-principles thinking—became Maxima's blueprintSecuring $3K-$5K POC commitments from Figma mockups before writing codeWhy Scale AI and Rippling rejected a point solution and demanded 3-4 modules from day oneThe compound startup model: building multiple products simultaneously to meet buyer expectationsHow 17% of CFOs are adopting AI tools today (vs 51% in software development)Why finance teams view AI agents as "digital college freshmen" who need proof of workHiring from YouTube Studios, Apple, and Robinhood instead of legacy finance software companiesHow NetSuite World conference booth sizes revealed the data integration infrastructure gapThe $3K-$5K validation threshold that proved finance pain was urgent enough to pay pre-productGTM Lessons For B2B Founders:Demand generation unlocks engineering potential: Yogi learned from his Rubrik mentors: "focus on demand and if you have great engineers then they will solve the problems." Maxima built products in 2-3 months they didn't initially know were technically feasible—because customer demand pulled the engineering team forward. $3K-$5K is the pre-product validation threshold: Before writing any code, Yogi secured POC commitments at this price point based solely on Figma mockups. This isn't about revenue—it's about proving urgency. Verbal interest means nothing. Small pilot commitments mean "we'll try it someday." Sophisticated buyers will reject your narrow MVP: Scale AI and Rippling told Maxima explicitly: "If you will only build this one thing, we will not buy. You have to commit to building three, four modules." Conventional wisdom says start narrow, but enterprise buyers with complex workflows won't adopt point solutions that create new integration headaches. Target acute pain over easy access: Early-stage companies (10-30 people) were easier to reach but finance wasn't urgent enough. At that scale, it's "build product, ship product"—finance operations aren't broken enough to warrant urgent attention. Hire intensity and first-principles thinking over domain knowledge: Maxima deliberately hired zero engineers from legacy finance software companies. Their frontend engineer came from YouTube Studios. Others came from Apple, Robinhood, Netflix—none with financial product experience. Yogi's three hiring criteria: "incredible intensity, huge confidence in themselves, and fast thinking mode." Make AI explainable or finance teams won't adopt: Finance teams adopted faster than expected because Maxima showed every calculation step. "If they can prove by looking at the Math, you know, 18 plus 88 plus 36 is X. And I can see the step of the work, they are willing to give it to them." This isn't about fancy UX—it's about auditor-grade proof of work. //Sponsors:Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠//Don't Miss: New Podcast Series — How I HireSenior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.Subscribe here:⁠ https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM