The LeanScale Podcast with Anthony Enrico

Anthony Enrico
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We talk about all things RevOps, GTM, and AI.

  1. 2d ago

    Why You Can't Sell Your Way Into PLG | Bryce Winkelman on Turning Typeform Into a Workflow Platform

    Most companies believe they can bolt a self-serve motion onto their sales-led engine whenever they're ready. Bryce Winkelman has run both — and he's convinced it almost never works in that direction. Bryce is the Chief Revenue Officer at Typeform, where he's turning a 140,000-customer forms business into a full workflow platform, with roughly half his organization operating out of Europe. Before that he was an early leader at Qualtrics through its $8B acquisition by SAP and subsequent IPO, tripled revenue from $35M to $100M as Chief Strategy Officer at Quantum Metric, and ran the GTM org at SeekOut. In this conversation with LeanScale co-founder Anthony Enrico, Bryce breaks down why you can PLG your way into sales but never sell your way into PLG, why the growth-at-all-costs premium is dead, how to fight for brand budget when the ROI is nearly impossible to prove, and the industry-expert hire most GTM teams are sleeping on. WHAT YOU'LL LEARNWhy you can PLG your way into sales but almost never sell your way into PLGHow owning the "front door" justifies owning the entire downstream workflow — enrichment, routing, segmentation, paymentsWhy qualitative research was the hardest problem AI could unlock, and how Typeform is rebuilding it end to endHow to shift a brand from "forms" to "workflows" without abandoning the core that made youThe packaging problem no one has cracked: what to give away in self-serve vs. reserve for enterpriseWhy churn will look terrifying in a healthy PLG motion, and how to keep finance and the board from pulling the plug too earlyHow to fight for brand investment when the ROI is nearly impossible to proveWhy bringing the team into the "why" beats one more enablement session on the "what"The industry-expert hire that becomes so valuable you need an intake process to ration itHow "nail it, then scale it" replaced "hire 50 AEs" as the growth model CHAPTERS00:00 — Cold open + intro01:50 — Owning the front door: forms to a workflow platform04:20 — Entering qualitative research — the problem AI unlocked06:46 — Shifting the brand from forms to flows: paid, events, influencers10:47 — The messy middle: running PLG and sales-led at once11:17 — You can PLG into sales, but never sell your way into PLG14:24 — Why sales-led companies can't become product-led18:20 — Fighting for brand investment when the ROI is invisible25:28 — AI search: why brand and content matter more than ever26:25 — Enablement: bringing the team into the "why"32:56 — The roles that make it work: RevOps, PMM, and ops36:27 — The industry-expert hire most teams miss43:12 — Growth at all costs is dead — making bets under scrutiny48:29 — "Nail it, then scale it" and staying close to the signal51:09 — Wrap ABOUT THE GUESTBryce Winkelman is the Chief Revenue Officer at Typeform, where he leads global go-to-market — marketing, sales, partnerships, RevOps, and customer success — as the company evolves from a 140,000-customer forms business into a full workflow platform. Over two decades in tech, Bryce was an early leader at Qualtrics, holding roles from EMEA Head of Sales to Global Head of Revenue and Solution Strategy through its $8B acquisition by SAP and subsequent IPO. He later served as Chief Strategy Officer at Quantum Metric — where revenue tripled from $35M to $100M in two years — and as Chief Business and Revenue Officer at SeekOut. He has also advised Warburg Pincus. ABOUT THE LEANSCALE PODCASTThe LeanScale Podcast is the show for GTM operators building the next generation of revenue infrastructure. Hosted by Anthony Enrico, co-founder of LeanScale. ▶ Learn more: https://www.leanscale.team▶ Follow Anthony on LinkedIn▶ Follow Bryce on LinkedIn #RevOps #GTM #PLG #ProductLedGrowth #SalesLedGrowth #AI #BrandMarketing #B2BSaaS #Typeform #Qualtrics #CRO #LeanScale

  2. 2d ago

    AI Ops: How We Run RevOps for 30 SaaS Companies at Once | Jake Toepel, CTO at LeanScale

    Most people have never seen what AI-native go-to-market actually looks like under the hood — and almost nobody has seen it run across an entire portfolio at once. LeanScale runs revenue operations for dozens of fast-growing SaaS companies simultaneously. Different CRM, different data, different definitions of basically everything. Small team, and a stack of AI agents doing the work. In this video, CTO Jake Toepel opens the hood on the exact plays — the day-one diagnostic that compresses three weeks of senior consulting into a 20-minute first draft, the QBR where the answer happens live in the room, and the layer of agents that runs the agency itself. Then he does the part nobody does: he shows you why none of it works out of the box. Point raw AI at real revenue data, ask it a simple question like "what is my pipeline coverage ratio," and you get an answer that is confident, instant, and wrong — because four things are missing. Shared definitions. Identity resolution. The plan. Memory. At one company that's annoying. At 30, it's a liability. The fix is the context graph, and Jake breaks down exactly how it's built. WHAT YOU'LL LEARNWhy AI-native GTM runs on operations, not on vibes — and what "AI ops" actually meansThe day-one diagnostic agent: three weeks of senior consultant time to a first draft in 20 minutesHow the QBR changes when the answer happens live in the room instead of "we'll follow up next week"The three background agents running the agency: project management, customer health, team evaluationHow field learning feeds back into the playbooks so the system compounds with every callWhy handing your team a stack of Claude licenses does not get you any of thisThe four things missing from raw AI on real data: definitions, identity resolution, plans, memoryWhy one company's messy definitions become 30 boards' worth of confident wrong answersWhat a context graph is, and how a semantic layer resolves one source of truth across CRM, billing, and productThe build order: a foundation that is true first, then the skills, plugins, workflows, and interfaces on top CHAPTERS00:00 — Running RevOps for a whole portfolio at once01:12 — AI-native GTM does not run on vibes01:45 — What we mean by AI ops02:10 — Play 1 — the day-one diagnostic agent03:15 — Play 2 — the QBR that answers in the room04:15 — Play 3 — the agents that run the agency04:55 — Project management agents: call transcript to scoped tasks05:25 — Customer health and team evaluation agents05:50 — Why the whole system compounds06:05 — Why a stack of Claude licenses isn't enough06:40 — The four missing pieces: definitions, identity, plans, memory07:30 — The context graph, built on Vasco08:15 — A foundation that is true, and the operation on top08:40 — Where to start: an honest assessment of your foundation ABOUT THE GUESTJake Toepel is the Chief Technology Officer at LeanScale, where he builds and runs the AI operations layer behind the firm's revenue operations delivery across dozens of fast-growing B2B SaaS companies. His work spans the semantic layer that resolves each client's data into a single source of truth, the agent fleet that turns calls into scoped delivery work, and the skills, plugins, and workflows that clients use day to day. ABOUT LEANSCALELeanScale is a tech-enabled revenue operations firm building the GTM infrastructure behind the fastest-growing B2B SaaS companies. This channel goes under the hood on how AI-native go-to-market is actually built and operated — no hype, just the systems. ▶ Learn more: https://www.leanscale.team▶ Get an honest assessment of your GTM foundation: [ASSESSMENT-LINK]▶ Follow Jake on LinkedIn #AIOps #RevOps #GTM #GoToMarket #AI #AIAgents #AINativeGTM #ContextGraph #SemanticLayer #RevenueOperations #B2BSaaS #EnterpriseSaaS #GTMEngineering #Vasco #LeanScale

  3. Aug 13

    Why Deflection Is the Wrong Way to Measure AI | Dvir Ginzburg, Founder & CEO of Encore AI

    Most companies are grading their customer-facing AI on deflection — how many people it stopped from ever reaching a human. Dvir Ginzburg thinks that's like grading a website by how fast people leave it. Dvir is the founder & CEO of Encore AI, holds a PhD in geometric deep learning, and spent years as a recommendation systems researcher at Microsoft, with two granted patents to his name. Encore AI builds revenue-generating conversational AI for banks and lenders — running millions of customer calls a month across voice, chat, and IVR. In this conversation with LeanScale co-founder Anthony Enrico, Dvir dismantles the deflection metric, explains why 'sounds human' is already solved while 'acts human' is the real moat, and tells the story of a customer who lied to an AI agent rather than tell it no. They get into interaction mining, cloning your top performers, the 80-20 rule that separates demos from production, and why the next wave of AI is about effectiveness, not efficiency. WHAT YOU'LL LEARNWhy deflection is the wrong metric for customer-facing AI — and what to measure insteadHow AI deflection can quietly tank revenue (the travel-insurance PPD story)Why 'sounds human' is already solved and 'acts human' is the real battlegroundWhy your moat is your own conversation data, not the foundation modelHow interaction mining finds exactly where revenue is leaking inside a businessHow AI agents learn to clone the tactics of your top performersThe customer who lied to an AI agent — and why that's a signal of trustWhere the real ceiling on AI agents is (hint: it's integration, not technology)The 80-20 rule that separates an impressive demo from productionWhy the next wave of AI is about effectiveness, not efficiency CHAPTERS00:00 — Cold open + intro01:52 — The deflection trap: grading AI by how fast people leave03:45 — From 'show my board I have AI' to 'what's the ROI?'05:20 — Travel insurance: deflection up, revenue down07:01 — The $100-for-$90 problem and the subsidized AI party08:00 — Deployment strategists and interaction mining11:43 — Sounds human vs. acts human — your moat is client data13:30 — Cloning your top performers15:44 — The customer who lied to the AI about his wife19:25 — Do agents actually beat humans?22:42 — The real ceiling is integration, not technology26:01 — The next barrier: 'LLMs see quantity as quality'28:10 — The omni-channel shift: 'text Jim'31:23 — Build vs. buy and the 80-20 rule of production36:44 — The last mile + wrap: effectiveness over efficiency ABOUT THE GUESTDvir Ginzburg is the founder & CEO of Encore AI, which builds revenue-generating conversational AI for banks, lenders, and financial-services enterprises. He holds a PhD in geometric deep learning and spent years as a recommendation systems researcher at Microsoft, with two granted patents to his name. Encore AI's technology combines agentic landing pages with dynamic customer journeys and 'interaction mining' — a layer that classifies every customer-facing conversation (email, chat, text, and voice) to find where revenue is leaking and reverse-engineer how a company's top performers win. Encore AI runs millions of customer calls a month across voice, chat, and IVR, deployed as fully autonomous agents or as a live 'wingman' assistant to human teams. ABOUT THE LEANSCALE PODCASTThe LeanScale Podcast is the show for GTM operators building the next generation of revenue infrastructure. Hosted by Anthony Enrico, co-founder of LeanScale, we go deep with the operators, founders, and executives shaping how modern go-to-market teams are designed, scaled, and transformed. ▶ Learn more: https://www.leanscale.team▶ Follow Anthony on LinkedIn▶ Follow Dvir on LinkedIn #AI #ConversationalAI #VoiceAI #AIAgents #AgenticAI #RevOps #GTM #CX #Fintech #Banking #AITransformation #EnterpriseAI #EncoreAI #LeanScale #LeanScalePodcast

  4. Aug 12

    AI-Native GTM: 3 Agent Plays and the Layer That Makes Them True | Jake Toepel, LeanScale CTO

    Your CEO or your board has told you they want an AI-native go-to-market. There's an even better chance nobody has told you what that actually means. In this video, LeanScale CTO Jake Toepel puts one AI agent through three of the highest-leverage plays in go-to-market — a real ICP analysis, a messaging teardown from 20 sales calls, and a live pipeline diagnostic — in less time than it takes most teams to book the meeting. Then he does the part nobody demos: he points raw AI at a real CRM, asks it for pipeline coverage, and shows you the confident, instant, completely wrong answer that comes back. The fix is a concept called the context graph — the semantic layer that maps your raw data to what it actually means in your business, resolves every record across CRM, billing and product, and carries your definitions, your plan and your memory. It is the single most important part of AI-native GTM and almost nobody is talking about it. Jake breaks down how LeanScale builds it on Vasco, and why buying everyone a Claude license without it just gets you 50 versions of the truth. WHAT YOU'LL LEARNWhat "AI-native GTM" actually means — a working definition, not a slideHow an agent finds your real ICP by cross-referencing deal size, sales cycle and 6-month retentionWhy the ICP on your website is usually not the ICP that winsHow to run a messaging teardown against 20 real sales calls — with quotes as receiptsWhich lines to keep and which to kill, and why "one platform instead of five tools" backfiresHow to get five-whys root cause on soft pipeline live, inside the forecast callWhy speed — not headcount or tooling — is the new moat in go-to-marketThe four things missing when you point raw AI at your CRM: definitions, identity resolution, plan, memoryWhy a confident guess is worse than no answer when it reaches the boardWhat a context graph is, how it resolves Acme Inc. vs. Acme Co. vs. Acme 123, and why it has to come first CHAPTERS00:00 — The promise: three plays, then the part everyone skips01:24 — What AI-native GTM actually means02:08 — Play 1 — Who is actually your best customer?03:00 — The answer: your real ICP isn't the logos on your website03:34 — Play 2 — Is your messaging actually landing?04:10 — Keep this line, kill that one — with receipts04:38 — Play 3 — The live pipeline diagnostic05:30 — Five whys of root cause before the call ends06:04 — Now try it on your own CRM (it breaks)06:30 — The four things missing: definitions, identity, plan, memory07:44 — The context graph: the semantic layer underneath08:38 — Why buying everyone a Claude license doesn't work09:14 — Where to start, and what's in the next video ABOUT THE GUESTJake Toepel is the Chief Technology Officer of LeanScale, where he builds the AI-native revenue operations systems behind some of the fastest-growing companies in B2B SaaS — not slide decks about AI, the actual working systems. He leads the development of Vasco, LeanScale's context graph: the semantic layer that maps a company's raw CRM, billing and product data to what it means in their business, so agents answer from a model of the business the team has already agreed is correct. This is Video 1 in his AI-Native GTM series. ABOUT LEANSCALELeanScale builds AI-native revenue operations for the fastest-growing companies in B2B SaaS. We design, build and run the go-to-market systems behind the pipeline — and the data foundation that lets agents answer questions about them truthfully. ▶ Learn more: https://www.leanscale.team▶ Get the AI-readiness assessment: [ASSESSMENT-LINK]▶ Follow Jake on LinkedIn▶ Follow Anthony on LinkedIn #AINativeGTM #ContextGraph #SemanticLayer #RevOps #RevenueOperations #GTM #GoToMarket #AI #AIAgents #GTMEngineering #DataQuality #IdentityResolution #B2BSaaS #EnterpriseSaaS #Salesforce #Vasco #LeanScale

  5. Aug 10

    Stop Making Decisions, Start Making Bets | Yishi Zuo on Poker, Expected Value & GTM

    Most operators think they’re making decisions. Yishi Zuo would tell you they’re making bets — they just don’t know it yet. His resume reads like four different people: Goldman Sachs banker, hedge fund analyst, MIT-trained founder who built DeepBench to seven figures and an exit, head of finance at a healthcare AI company, and now Head of Go-to-Market Strategy at Tavus — the CRV-, Sequoia-, and Scale-backed conversational video AI company that just raised $40M to build emotionally intelligent AI humans. He’s also a seriously good poker player. In this conversation with LeanScale co-founder Anthony Enrico, Yishi turns poker’s core disciplines — expected value, process versus outcome, reading tells, mastering the fundamentals — into an operating system for go-to-market. You’ll learn how to size a GTM wager, why the right bet can still lose, how to model the ROI of a conference in ten minutes, and the difference between a decision and a bet that most operators never stop to notice. WHAT YOU’LL LEARN Why nearly every “decision” in go-to-market is actually a bet in disguise How to calculate expected value on a GTM investment — and the two caveats that break the math The process-versus-outcome trap: how to make the right call and be at peace when it loses What losing with pocket aces five times in a row teaches you about a broken process Why fundamentals beat fancy — in poker and in go-to-market How the best players read tells amateurs can’t even see — and why beginners shouldn’t try How to model the ROI of a conference or an outbound agency in ten minutes flat Why “making no decision” is still a decision — with consequences What a finance and hedge fund career actually teaches you about running a revenue org Where conversational video AI is headed: digital twins, senior-care companionship, and B2B enablement CHAPTERS 00:00 — Cold open + intro 02:24 — From Goldman to a hedge fund to founding DeepBench 06:52 — What finance actually teaches you about GTM 08:21 — How poker got its hooks in 11:03 — Winners vs. losers: goals, discipline, fundamentals 14:02 — Expected value, explained 17:03 — Process vs. outcome (and pocket aces five times in a row) 20:01 — A decision vs. a bet — the distinction most operators miss 24:00 — The Hail Mary: when the right call still loses 27:35 — Good player vs. great player: reading the tells 30:30 — Thinking in bets at Tavus: conferences and outbound 33:22 — The career bet: why he joined Tavus 36:30 — Where AI humans go next: digital twins, senior care, enablement 41:19 — The ROI numbers customers are seeing 43:34 — A discovery-agent idea for LeanScale + wrap ABOUT THE GUEST Yishi Zuo is Head of Go-to-Market Strategy at Tavus, the conversational video AI company building PALs — Personified Application Layers, or emotionally intelligent AI humans — backed by CRV, Sequoia, Scale Venture Partners, and Y Combinator on a $40M Series B. Yishi began his career as an investment banking analyst at Goldman Sachs before spending three years at a hedge fund. He earned his MBA at MIT Sloan, where he co-founded DeepBench, an expert network that reached seven figures in revenue and was later acquired. He then led finance at a fast-scaling healthcare AI company before moving into go-to-market at Tavus. He’s also a serious poker player who turns the game’s disciplines — expected value, process over outcome, reading the table — into a framework for placing GTM bets. ABOUT THE LEANSCALE PODCAST The LeanScale Podcast is the show for GTM operators building the next generation of revenue infrastructure. Hosted by Anthony Enrico, co-founder of LeanScale. ▶ Learn more: https://www.leanscale.team ▶ Follow Anthony on LinkedIn ▶ Follow Yishi on LinkedIn — talk to his AI video avatar at yishizuo.com #RevOps #GTM #AI #ThinkingInBets #Poker #ConversationalAI #AIAvatars #DigitalTwins #B2BSaaS #Tavus #LeanScale

  6. Jul 22

    After the Series A: The Capital Clock - The 12-Month Playbook To Earn Your Series B

    The Capital Clock: Your First 12 Months After Series A | Anthony Enrico, LeanScale You just closed your Series A. Here's what nobody tells you at the closing dinner: you didn't buy yourself time. You started the clock. From the day the wire hits, you have about 12 months — 18 tops — before you're back out raising again. Whether that next race is a victory lap or a death march is decided by what you build in the first two quarters. Your Series A proved product-market fit. The market wants what you built. But that bet didn't prove anything about your go-to-market. Your Series B investors aren't buying a product story anymore — they're buying a machine they can pour capital into. The next 12 months have one job: go-to-market fit. In this video, Anthony Enrico, co-founder and CEO of LeanScale, walks through the three builds every founder needs to run in the Capital Clock window — instrument, multiply, prove — and the segmented scoreboard that can be worth tens of millions on your next valuation. WHAT YOU'LL LEARNWhy your Series A proved product-market fit — but not go-to-market fitThe Capital Clock: why the first two quarters after your A decide the outcome of your BBuild 1 — Instrument: why every channel becomes a formal experiment with a goal, a scoreboard, and a decision dateThe "GTM Brain" — the three layers of context (Performance, Market, Process) every decision runs onBuild 2 — Multiply: raising the performance of every motion (CPQ, auto-enrichment, sequencing, buying signals, forecasting and CS agents)Why effectiveness beats efficiency — and how chasing the wrong one costs you the marketBuild 3 — Prove: the segmented scoreboard that turns your Series B pitch from a story into a math problemWhy some bets will fail — and how cutting them fast is part of scaling, not a broken planHow to hold 50%+ growth while you build the machine underneath the story CHAPTERS00:00 — Congratulations, you just started the clock00:39 — What your Series A actually proved (and didn't)01:24 — Series B investors are buying a machine, not a story01:48 — Build 1: Instrument everything before you scale anything02:33 — The GTM Brain: Performance, Market, Process03:09 — Build 2: Multiply every motion with technology03:38 — Effectiveness vs. efficiency — chase the second one04:05 — Build 3: Prove it on a segmented scoreboard04:22 — Turning your Series B pitch into a math problem04:45 — Cutting bets fast and redirecting the fuel05:12 — 12 months from now: walking in with a machine, not a moment ABOUT LEANSCALELeanScale builds the go-to-market machine inside some of the fastest-growing B2B startups — the data, the process, the AI — and sits next to founders through exactly this window. ▶ Get the full playbook: https://www.leanscale.team▶ Follow Anthony on LinkedIn▶ Subscribe for more from operators building the next generation of go-to-market #SeriesA #SeriesB #GTM #GoToMarket #RevOps #Founders #StartupGrowth #FoundersJourney #B2BSaaS #GTMEngineering #AIinSales #LeanScale #LeanScalePodcas

  7. Jul 20

    Why AI Means More RevOps Hires, Not Fewer | Jimmy O'Halloran VP of GTM Strategy at New Relic

    The consensus says AI plus a couple of GTM engineers just shrank the RevOps org. Jimmy O'Halloran thinks that's exactly backwards. Hand him a tool that makes his people 300% more productive and he won't cut two heads — he'll hire two more and go faster. Jimmy has spent nearly two decades close to revenue: he recruited himself out of a staffing job into EMC, spent 13 years across EMC and Dell, ran field operations at Snowflake for four and a half years, helped Glean make the jump from startup-mode ops toward enterprise scale, and today owns Revenue Operations and sales enablement as VP of Go-To-Market Strategy & Operations at New Relic. In this conversation with LeanScale co-founder Anthony Enrico, Jimmy breaks down the two flavors of RevOps and which one actually has influence, how to build an operating cadence that mirrors the way your customer buys, why sales enablement is the secret sauce almost nobody staffs correctly, the brutal reality of running a consumption revenue model — hunter/farmer, comp, quotas, forecasting — and the career-defining reframe that changed everything for him: the difference between leverage and trust. WHAT YOU'LL LEARNWhy the "AI shrinks RevOps" thesis is backwards — and what a productivity gain should actually triggerThe two flavors of RevOps, and which one gets invited into the roomHow to build an operating cadence that mirrors how your customer buysWhy sales enablement is the secret sauce — and the span-of-control trigger for building itWhy acquisition is a process, not an event, in a consumption modelThe hunter/farmer model and the 600-pound gorilla: how you actually pay repsWhy consumption forecasting belongs to finance and data science, not go-to-marketHow to define ARR in a consumption world you can actually raise againstLeverage vs. trust: how operators earn a seat at the table instead of forcing their way inWhy you're on the leadership team but annexed from it — and how to steward the information you hold CHAPTERS00:00 — Cold open + ground rules02:04 — The two flavors of RevOps02:18 — Recruiting himself into EMC: finding his lane04:19 — Structuring your week to stay in the field06:59 — An operating cadence that mirrors the customer journey10:28 — Sales enablement: the secret sauce21:29 — When to build a formal enablement team24:33 — The real challenges of consumption revenue26:22 — Hunter/farmer: acquisition is a process, not an event29:00 — Don't land at scale: the 18-wheeler vs. the lawnmower34:35 — Setting quotas in a consumption world40:32 — Forecasting & defining ARR you can raise against43:26 — Should data science report to RevOps? The grocery store problem48:15 — Anthony's Emailage story: hire #28 to a half-billion exit53:05 — Leverage vs. trust: getting invited to the table59:09 — Part of leadership, but annexed from it01:01:30 — Does AI change everything?01:04:04 — Why more AI means more people, not fewer ABOUT THE GUESTJimmy O'Halloran is VP of Go-To-Market Strategy & Operations at New Relic, where he owns the full Revenue Operations org and sales enablement. He has spent nearly two decades close to revenue without ever carrying a bag — from EMC (13 years) to Dell, then field operations at Snowflake for four and a half years, and helping Glean make the jump from startup-mode ops toward enterprise scale. His through-line: RevOps is won on trust, not leverage — and the best operators get invited to the table instead of forcing their way in. ABOUT THE LEANSCALE PODCASTThe LeanScale Podcast is the show for GTM operators building the next generation of revenue infrastructure. Hosted by Anthony Enrico, co-founder of LeanScale. ▶ Learn more: https://www.leanscale.team▶ Follow Anthony on LinkedIn▶ Follow Jimmy on LinkedIn #RevOps #GTM #AI #SalesEnablement #ConsumptionRevenue #B2BSaaS #Snowflake #OperatorMindset #LeanScale

  8. Jul 17

    Why Only 500 Apps Can Sell to the U.S. Government | Irina Denisenko, CEO of Knox Systems

    There are fewer than 500 software applications cleared to sell to the U.S. federal government. Anthony has more than that on his iPhone. That gap is a $150 billion market — and almost nobody can get through the door. Irina Denisenko lived through the FedRAMP gauntlet at a prior company, then did something almost no one else has: she acquired a 15-year-old managed service provider that already held a FedRAMP boundary serving Adobe, and built on top of it. Today her company, Knox, runs the federal infrastructure for Adobe as its anchor tenant plus 50+ customers — ClickHouse, Sierra AI, Armis, BigID — and turns a process that traditionally takes three years and $3 million into 90 days. In this conversation with LeanScale co-founder Anthony Enrico, Irina breaks down the real economics of selling into the government: why the hardest part isn't the 425 security controls but getting a federal sponsor to put their job on the line for you, why an ITSM duopoly is costing taxpayers billions, and why FedRAMP has become a 'super SOC 2' that closes commercial deals in financial services and healthcare long before the first government contract. WHAT YOU'LL LEARN Why fewer than 500 applications have FedRAMP — and what the 425 controls actually requireThe real reason the federal sponsor, not the technology, is the hardest part of the entire process Why you literally cannot throw money at getting a sponsor — and how companies get one anywayHow Knox compresses a 3-year, $3M process into 90 days with the 'luxury condo' model The FedRAMP 'halo effect' — why your first call after certifying is a commercial customer, not the governmentWhat the $20M ARR unlock looked like at Irina's prior company (and how little of it was government)The self-assessment checklist before you spend a dollar on federal Why the government can't buy anything for under $1M — and what that means for your ACVThe ITSM duopoly (ServiceNow and Salesforce) and what monopoly conditions do to price and quality Why AI collapsed breach-to-exploit time from 45 days to under a minute — and why that makes FedRAMP urgent CHAPTERS00:00 — Cold open + intro01:40 — What FedRAMP actually is (and the 425 controls)05:30 — Continuous monitoring and the forever-audit06:40 — The exclusive zip code: building your own house07:00 — Why the federal sponsor is the hardest part11:00 — How you actually get a sponsor — and why you can't buy one15:20 — 500 apps, $150B: the most underbuilt market in software16:00 — The ServiceNow / Salesforce duopoly19:50 — 45 days to under a minute: why AI makes this urgent24:50 — The luxury condo: FedRAMP in 90 days28:40 — 'I had to buy a company': the Adobe origin story33:40 — The smallest company that can pull this off42:30 — The halo effect + the $20M ARR unlock50:00 — FedRAMP as the new SOC 254:10 — The biggest check: Oracle's $100M government deal1:01:40 — Wrap ABOUT THE GUEST Irina Denisenko is the CEO and co-founder of Knox, a FedRAMP managed cloud that unlocks the U.S. federal market for modern SaaS companies. After navigating the FedRAMP process as COO of Class.com — where achieving FedRAMP unlocked $20M in additional ARR — Irina acquired the 15-year-old managed service provider behind Adobe's federal applications and spun it out as Knox. Today Knox serves 50+ customers including ClickHouse, Sierra AI, Armis, and BigID, holding 16 agency sponsorships across DoD, DHS, VA, Treasury, and Commerce. ABOUT THE LEANSCALE PODCAST The LeanScale Podcast is the show for GTM operators building the next generation of revenue infrastructure. Hosted by Anthony Enrico, co-founder of LeanScale. ▶ Learn more: https://www.leanscale.team ▶ Follow Anthony on LinkedIn ▶ Learn more about Knox: https://knoxsystems.com #FedRAMP #GovTech #PublicSector #RevOps #GTM #FederalSales #Cybersecurity #B2BSaaS #GovCon #LeanScale

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