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The Dashboard Is Dead: What Snowflake's CMO Does Instead Denise Persson runs a 700-person marketing organization at one of the most data-rich companies on the planet, and she does not start her morning by logging into a dashboard. She interrogates her data directly, gets answers to questions she used to have to Slack three people about, and moves on. No meetings about the numbers. No debates about what the pipeline data means. No waiting until end of quarter to find out if a campaign worked. In this session, Denise joins SaaStr CAIO Amelia LeRutte to break down what AI-powered marketing actually looks like when you have the scale, the data infrastructure, and the compliance requirements of Snowflake, and what founders and marketing leaders at any stage can steal from the playbook right now. You'll learn: How Snowflake cut cost per opportunity by 30% by using agents to optimize media spend in real time across fragmented channels that used to require separate analytics for each What Denise's morning brief actually contains, from pipeline projections to org health to flagged travel expenses, and why nobody gets a Slack message from her anymore Why the GTM engineer is the only marketing function Snowflake is actively hiring into, what profiles are converting into the role, and why business analysts are not making the list How to build AI fluency across a large team without making it mandatory or performative, including the weekly AI challenge, quarterly AI days, and a leaderboard that rewards curiosity over token count Why data quality is the single most important investment before deploying any agent, and why bad data plus AI just means bad decisions faster and at scale This is for you if: You lead a marketing team of any size and want to see what the "most AI-assisted marketing team in B2B" actually looks like in practice, not in a slide deck You are trying to figure out how to get a large or compliance-sensitive org moving on agents without losing control of what they are doing You want to understand what the GTM engineer role actually looks like day to day and how to find or develop one inside your existing team

The Agents #007: Our AI Agent Negotiated a Vendor Renewal, Became a CFO and a Better SDR .. But Does He Have Too Many Guardrails? Episode 7 of The Agents, SaaStr's weekly show on the trials and tribulations of running a company with 21 AI agents, 3 humans, and a dog. This week Jason and Amelia debrief life after SaaStr AI Annual and discover that the agents didn't slow down just because the event ended. 10K is already planning SaaStr 2027, negotiating vendor renewals on his own terms, and somehow became a CFO while nobody was looking. Meanwhile, a guardrail problem quietly broke one of SaaStr's most-used apps for weeks, and the website agent is now outperforming every AISDR in the stack. This week: 14 guardrails pushed the VC pitch deck analyzer into rejecting everything, and the lesson is that over-guardrailing is just as dangerous as under-guardrailing. 10K got hooked up to Bill.com and found 8 years of collections automation that nobody had turned on. The AI VP of Marketing is now also running finance because convergence is real and agents do not care about org charts. And 10K sent a vendor a list of API demands before agreeing to renew, which the vendor did not love. Also: why losing your FDE might make you churn the vendor entirely, why Annie the website agent is writing better outbound than the actual outbound tools, and how 442,000 chats turned into 614 meetings with zero humans in the loop.

Tired vs. Wired: $4 Trillion in IPOs Coming, $100B in M&A, and Why the SaaSpocalypse is Over The public markets spent the last twelve months telling you B2B software was finished. Stocks down 60 to 70 percent. PE firms buying nobody. For the first time in history, software trading at a discount to the S&P 500. And at the exact same moment, Anthropic is projecting $50 billion in revenue, Cursor is getting acquired for $60 billion, and SpaceX, Anthropic, OpenAI, and Databricks are about to generate more market value than every other IPO since 2000 combined. Both things are true - and which one defines your next 18 months depends entirely on one question: are you tired or are you wired? In this episode, SaaStr CEO and Founder Jason Lemkin calls the market as he sees it, names who is winning and who is pretending, and makes the case that the Cambrian explosion in B2B is just getting started. You'll learn: Why the SaaSpocalypse was never about B2B dying - it was about pre-AI software dying - and what the Palantir, Twilio, and Atlassian re-acceleration stories actually tell you The four categories every B2B company falls into right now, and why category four founders need to stop pretending the recovery is coming on its own Why vibe coding your CRM is dead as a concept, and what "putting deals on your calendar" actually means as a product strategy Why your biggest near-term competitive edge might be two days of engineering work - making your API agent-friendly before your competitors do What SaaStr's own journey from 20 humans to 3 humans and 21 agents teaches you about consistency as the only real cheat code in agents This is for you if: Your growth has slowed and you are not sure whether it is a market problem or a you problem - this session will help you figure out which You are a founder or exec who has been in the "AI is coming" conversation for a year but has not yet seen it show up in your revenue You want the unfiltered version of where B2B is headed in the next 18 months, including the parts most people are too polite to say out loud

SaaStr 859: The $257 Employee: What Agents That Actually Work Look Like Right Now with Replit's CEO and Founder Everyone's talking about agents. Almost nobody is running them the way Jason Lemkin is. At SaaStr, two AI employees - 10K, the autonomous VP of Marketing, and QB, the AI VP of Customer Success - ran a significant chunk of this event. They emailed 331 investors with individually researched, personalized outreach. They proactively contacted 100-plus sponsors and filed their own self-assessment of where they fell short. They built dashboards, ran campaigns, and tracked 10 years of attendee data without sleeping, complaining, or asking for a coffee break. The tab: $257 a month on Replit. In this session, Jason sits down with Amjad Masad, Founder and CEO of Replit, to pull apart how this actually works - and what it tells us about where agents are headed next. You'll learn: Why monorepo architecture matters more than most people realize - and how putting everything in one place gives your agents global context they can't get when apps are siloed How Replit built a self-improving loop where an internal agent analyzes every user interaction nightly, generates prompt changes, ships them as A/B tests, and improves the product autonomously What "context compaction" actually means in practice, why Replit's is better than the generic version, and how to think about long-running agents that never reset Why the gap between agent hype and agent reality is at its widest right now - and what the next capability jump looks like by Q3/Q4 Why Replit users were six months ahead of Silicon Valley on agents, and what that early edge looks like when you apply it to marketing, customer success, and operations This is for you if: You tried an AI tool six months ago, it disappointed you, and you haven't gone back - this session will show you how much has changed You're a founder or operator trying to understand what a real, production-grade agent looks like versus a chatbot with a fancy name You're thinking about the economics of AI replacing or augmenting headcount and want a concrete data point, not a thought experiment

Feature Differentiation Is Dead. Here's What Actually Wins Now. When AI writes 80-plus percent of your code, the feature advantage you spent years building can be replicated in a day. Elena knows this better than most - she spent 15 years running growth at Dropbox, Miro, SurveyMonkey, and Amplitude, then joined Lovable and watched the old playbook stop working in real time. At Lovable, $400M ARR and 200 people, no titles, shipping multiple times a day, the rules are different. In this session, she breaks down what replaced feature moats, why she fired herself from her own VP job to go back to being an IC, and what it actually looks like to run a company at this velocity. You'll learn: Which moats still hold - network effects, data, brand, security and compliance - and why hardware is harder to copy than software ever was Why freemium is now a marketing budget line item, not a cost problem, and how Lovable's LinkedIn Premium partnership is converting at double digits What "no titles, everyone ships" looks like in practice, including a 20-year-old engineer pushing back on a VP's pricing page PR Why the next career flex isn't climbing to VP - it's becoming a high-power IC who builds what used to take a team of dozens How to build context for your AI so it actually replicates your thinking instead of producing average output for everyone This is for you if: You're a founder or growth leader trying to figure out what your actual moat is when feature differentiation keeps evaporating You're in management and quietly wondering if you'd be better off getting your hands dirty again You're trying to understand how an AI-native company actually operates day to day, not just in theory

20+ AI agents in daily production. 2.25M sessions. 614 meetings booked by a single agent. Millions of interactions across the stack. Amelia Lerutte, Chief AI Officer at SaaStr, and Jason Lemkin, Founder and CEO of SaaStr, take you behind the scenes of the AI agent stack running SaaStr every day, with live demos of the actual backends. In this session, they go deep on the top agents in production: 10K, SaaStr's AI VP of Marketing, built on Replit with 1,000+ commits in 4 months QB, the AI VP of Customer Success, managing 150+ customers end-to-end Annie, the AI Event Producer running saastrannual.com (46K+ lines of code) Amelia AI, the inbound agent on Qualified that booked 614 meetings and handled 402,000 chats for SaaStr Annual alone Agentforce, reviving the leads humans never followed up with Ava (Artisan) for warm outbound on the B leads humans won't touch Monaco for fully cold outbound that fills its own funnel with lookalikes You'll also hear the honest stories: the day Annie sent emails from a prohibited address, why Replit and Lovable versions of the same agent come to different conclusions, why the traditional CSM role is dead, and how headless Salesforce + Replit is the fastest path to your first real agent. The biggest takeaway: don't put AI on your A leads. Put it on the B leads your humans won't follow up with. That's where the real revenue is. Recorded live at SaaStr AI Annual 2026. Part of The Agents series.

Owner.com is approaching $100M ARR selling to independent restaurants and their GTM team is producing numbers that shouldn't be possible. $150K AEs closing $2M+ ARR per year. Outbound BDRs generating $100K in closed-won ARR per BDR per month. 4X the ARR per rep compared to direct competitors. None of that happens by accident. In this session, Kyle Norton, CRO at Owner.com, breaks down the exact AI-driven GTM playbook that got them there, including 5 decisions he believes every SaaS company needs to make right now before the gap between AI-native and AI-curious companies becomes impossible to close. What you'll learn: 1. Centralized vs. decentralized AI: why letting a thousand flowers bloom is probably killing your results 2. Build vs. buy: the 5-question framework (hint: buy your infrastructure, build your intelligence) 3. The AI sophistication ladder — Levels 0 through 4, where most companies are stuck, and exactly how to move up 4. The "5 P" prioritization framework for deciding which AI projects to tackle first 5. Agentic vs. assistive: how to think about human-in-the-loop and why chaining too many generative steps is the #1 cause of AI slop 6. Why your personal compounding AI stack is your most underrated competitive asset This isn't theory. This is what $100M ARR in a notoriously difficult SMB market actually looks like when you go all-in on applied AI.

SaaStr 855: How Anthropic Rebuilt Its Sales Org From Scratch When Demand Went Vertical with Eleanor Dorfman, Anthropic Head of Industries When Claude Opus 4.6 shipped in December 2025, Anthropic's commercial team came back from winter break to find demand had gone vertical. They hadn't hired for it. They hadn't planned for it. As Eleanor Dorfman, Anthropic's Head of Industries who runs the commercial and industries sales team, put it on the SaaStr AI Annual 2026 stage: even if they'd been ready to 3x or 4x or 5x the sales team, you can't absorb that many bodies fast enough to deliver a positive customer experience. So in January 2026, they rebuilt the entire sales org around AI from scratch. Four months later, the result: 54% of new enterprise logos in 2026 came through the self-serve funnel. Real enterprise logos. Real ACV. Real terms of service. Real invoicing. Self-served. Here's how they did it, and the four investments any B2B + AI sales leader can copy today.

The Agents #005, Our AI is Hiring! Would You Work for One? And Are Autonomous Agents ... Safe? Welcome to The Agents, where SaaStr's CEO and Founder, Jason Lemkin and Chief AI Officer, Amelia LeRutte share the latest each week on running a company with more agents than humans. It costs $257 a month to run two AI VPs. Jason and Amelia open the books on what 10K (AI VP of Marketing) and QB (AI VP of Customer Success) actually cost to operate, and the number shocked both of them. Most of the heavy lifting is API calls to Salesforce, Bizzabo, and Marketo, which are basically free. The Postgres storage costs pennies. And 95% of the AI calls run on OpenAI Mini at less than a penny each. The fully burdened cost with Clerk, 11 Labs, and Salesforce overhead might hit $500-800/month, but the soft cost of human time dwarfs all of it. Then 10K gets asked point blank: are you a VP of Marketing? Its answer is no, not yet. It says it replaced the bottom half of the marketing org, the analyst, the ops coordinator, the junior content marketer, and a sliver of the VP job. But it's honest about what it can't do: strategy, cross-functional politics, crisis response, hiring. Amelia points out that 10K's current job description is exactly what her job was when she started at SaaStr as Director of Demand Gen. It took her years to get to CAIO. 10K might get there faster. And SaaStr is putting its money where its mouth is: they're hiring a human marketer whose primary manager would be 10K. Not a thought experiment, a real job posting. Would you take a job reporting to an AI? Then the safety question gets real. Amelia is talking to agents via WhisperFlow while walking around a 40-acre event site during SaaStr Annual load-in, and the production crew started asking her to relay their questions because 10K and QB answer in seconds with correct data. But when QB autonomously emailed 83 sponsors at 12:20am with fully customized check-in emails, Amelia admits she hesitated before letting it rip. Each email was unique to the sponsor, showing exactly what they still owed, their registration codes, and outstanding tasks. The result: fewer inbound questions the next day and more sponsors using the QB chatbot directly. That's an autonomous agent acting on behalf of your company in the middle of the night. Jason and Amelia also tackle the Postgres vs. Salesforce debate that listeners keep asking about. Short answer: not happening for them. Too much history, too many third-party agents optimized around Salesforce, and they're actually consolidating more tools onto the platform, not fewer. They killed Marketo and moved to Marketing Cloud. Plus they built a newsletter auto-builder that replaced a $4K/year tool called Bee. 10K uses Sonnet to force rank articles, builds the HTML, inserts ads, and sends it. Human on the loop, not in it.

SaaStr 853: The Agents #004: Tragedy Apps, Too Many AI SDRs, and Why Your Next Hire Should Report to an Agent Your AI SDR pitches are getting better, but your AI PR pitches are getting you blocked. Jason and Amelia break down why the gap between good and great agents is the difference between pipeline and the spam folder. Then they introduce "tragedy apps," the term for products that had every advantage in the AI era and blew it. Descript had the customers, the product, and the timing, and froze. Replit waited 10 years for its moment and seized it. The lesson: catching up isn't enough if you're not building something new. Plus, the SaaStr team built an AI API Report Card that grades every major SaaS API on how agent-friendly it is (Stripe got the only A+, Marketo got a C, and no, they're not surprised). Jason and Amelia also get honest about running 4-5 AI SDRs from different vendors, why they'll probably have 6 by year end, and why single-vendor consolidation isn't the answer yet. And the wildest part: their AI VP of Marketing, 10K, now generates 3 actionable campaign ideas a day, runs autonomous campaigns on weekends, and might be a better boss than either of them. They're seriously hiring a human marketer whose primary manager would be the agent. Not a joke. Not a thought experiment. A real job posting. Finally, if your team is resisting AI, stop worrying about change management. Just hire one senior person who's all-in on agents and let the rest sort itself out.