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New!! Hiring Risks vs. Hiring Flags. Make Sure You Get it Right.: My biggest hiring mistake I've made past 5 years that I never made before: I hired folks who didn't really, really, really want the job So far, none have worked out — Jason ✨👾SaaStr.Ai✨ Lemkin (@jasonlk) April 16, 2025   During the Boom Times of late ’20-early ’22, we all often confused Taking Risks in... Continue Reading

I walked into both rooms ready to give. I didn’t expect to leave with something. Last month at SaaStr Ai, I went to my very first Wednesday Women dinner and high tea. I showed up the way I always do. Thinking about who I could help, who I could connect, what I could give. Giving is easy for me. It’s the thing I know how to do. Maybe a little too easy. But Wednesday Women is built on two words, not one. Give and get. And for the first time, I sat with the second half seriously. My get was simple but not easy: learning how to say no. Not because I don’t care. Because I do. Running yourself to the ground doesn’t help anyone. Protecting your energy isn’t selfish, it’s how you stay in the game long enough to keep showing up for the people who matter. Leslie Greenwood, Melissa Moody, Sandy Yu and Ashley Stamps-Lafont helped me see that clearly, always with warmth and no judgment. I’ve made good friends from this circle. People I’d show up for without thinking twice. I left the port with something I didn’t expect to walk away with. Permission to say no. ——- P.S. Still thinking about you!! Patricia DuChene Ashley Faus Madelyn DePrey Michelle G. Hannah Ajikawo Christina Mitine (And many more)

Today Sebastian Cox and I are launching Token Consumption. A video series where we talk to founders, operators and investors about company building, go-to-market and product in this mad new AI world. We kicked it off with a trip to San Francisco accompanied by our highly talented cousin Charlie Brittain of Flightless Films. His video production skills add legitimacy to what was otherwise very transparently a Burrito junket. We talked to some legendary folks. Both long-time members of the SF tech scene (Eros Resmini, Eunjoon (EJ) Cho) and some antipodean imports (Christina Fa, Alistair McLeay, Keith Davison). Also attended SaaStr while we were over there and allowed Jason M. Lemkin to savage my dreams of building a billion dollar solo company. Full episode drops Monday 29th June, but check out the trailer now!

The biggest shift in hospitality isn’t the tech. It’s how we tell the story. Tomorrow, the first-of-its-kind Hospitality Creator Summit is kicking off, co-located right here at HITEC San Antonio. The media is moving at lightning speed. Algorithms are shifting under our feet, AI is altering the playing field daily, and the old B2B playbook just isn’t cutting it anymore. The brands that win tomorrow aren’t just selling a product—they are building a community. Those who did not attend the recent SaaStr Ai Annual event in San Francisco are behind the curve. Alliants sent a team! That’s why the team at Alliants is so proud to stand as a Foundational Partner for this creative storytelling movement. It is incredible to see this curated group of leading builders, storytellers, and brand architects come together to rewrite the rules of hospitality commerce and creativity. If you managed to grab an invite before it officially hit capacity, you are in for an absolute masterclass. I am personally incredibly excited to step on stage for our session, "The B2B Bet," alongside a powerhouse lineup: 💡 Emily Leu – Unpacking massive commercial expertise on how to turn content, authentic connection, and strong market positioning into tangible B2B revenue growth. 💡 Tom Reynolds – Breaking down the precise operational frameworks, systems thinking, and structured problem-solving required to scale content without breaking your daily workflow. 🎤 Moderated by the brilliant Kayla Beardsley, who will be keeping the insights sharp, actionable, and entirely focused on what's next. We’ll be pulling back the curtain on how forward-thinking hospitality vendors are championing B2B creators, structuring deals, and leveraging creator-driven content to drive real business value. Expect some of my vintage Aussie humor and one-liners. For those of us obsessed with the intersection of hospitality tech and human storytelling, this is exactly where the industry is moving forward. If you’re on the ground in San Antonio for HCS or HITEC, let’s connect! What macro trend are you watching closest this week? #Hospitality #HITEC2026 #hitec #HITECSanAntonio #HospitalityCreators #B2BMarketing #Innovation #Alliants #hospitalitytech #ai #hftp #ahla #hotels #resorts #casinos #guestexperience

"What should I look for when I hire my first Head of Product?" This was the most common question from founders when I was consulting with growth stage startups. It turns out, there is a very good article on this topic written by Jason Lemkin, the founder of SaaStr. It contains four things that are really important, and I couldn't agree more. Check out the carousel below. But don't hire a Head/VP of Product unless you are ready to let go of product decision making - to a large extent at least. Because you cannot expect accountability without ownership. This is one of the most common pitfalls I see founders make. #productmanagement #productleadership #hiring

The issue with most pipeline reviews is that "commit" has stopped meaning anything. Three sellers. Same word. Three definitions. One commits the moment a buyer says "this looks great." One commits only after procurement is looped in. One commits whatever clears the number on the board this quarter. Roll those three into one forecast and you're averaging three schemas. That's not a model. That's a vote. The diagnosis: commit accuracy is a definitions problem before it's a prediction problem. Here's the benchmark most teams quietly fail. A healthy commit category closes at 90% or better. Under 80% and your sellers are systematically dumping hope into commit. SaaStr's read on what actually changed in GTM this year lands in the same place: the forecast is only as trustworthy as the exit criteria behind each category (SaaStr, 2026). The prescription, three parts: 1. Write the exit criteria for commit. One sentence. "A deal enters commit when the buyer has confirmed budget, timeline, and the signing path." 2. Score last quarter. Take every deal someone called commit and check what closed. That close rate is your real accuracy number. 3. If it's under 80%, the category is broken, not the rep. Re-cut the definition before you touch the comp plan. At Series A a lean sales team can run this in an afternoon. At Series B it's a quarter and a forecast council. Either way it beats missing the board number twice. Pull your commit close rate from last quarter this week. Then DM me the number and I'll tell you whether it's a definitions problem or a discipline problem. Source: SaaStr — https://lnkd.in/dHEWTrts #RevOps #SalesForecasting #PipelineManagement #B2BSaaS

Selling SaaS in Europe sounds simple. It's not one market — it's dozens of countries, languages, and buying styles rolled into one continent. For seed-stage startups and scale-ups, the opportunity is huge. But you need a plan that fits Europe — not a copy of your US playbook. Start with the market Research which countries actually need your product. Look at digital maturity, industry demand, and who's already competing there. GDPR and local data laws matter. Get compliance right early — it builds trust and keeps you out of trouble. Go beyond translation Localization is more than switching language. Sell and market in the local language. Support local currencies and payment habits — some buyers want monthly plans, others prefer longer contracts. Offer support in their language, from people who understand the region. Use a local domain (.fr, .de, .es) when you're serious about a market. Translate your website — and your docs if developers are your audience. That shows you're here to stay, not just testing the waters. Partner your way in You don't have to build everything alone. Work with local resellers who already know the market. Integrate with regional platforms your customers already use. VARs and MSPs can help you reach more buyers faster. Outsourced sales teams with local contacts can speed up your first deals too. Market with focus Create content for European buyers — not generic global messaging. Track what works: outreach, demos, conversions. Use LinkedIn, Google Ads, and local channels where your buyers actually spend time. Show up at events like SaaStr Europa, Web Summit, and SaaStock. Build the right sales motion Early stage? Lean on partners and small regional teams. Scaling up? Hire reps who understand how deals close in each country. Going enterprise? Use dedicated account managers and tailored solutions. Keep customers after the sale Winning a logo is step one. Strong onboarding reduces churn. Regular check-ins show you care beyond the contract. Local user groups turn customers into long-term advocates. Bottom line Europe rewards SaaS companies that show up with intention. Understand the market. Localize properly. Partner smart. Sell region by region. Focus on customer success. The demand is real. The winners will be the teams that adapt — not the ones that assume one strategy fits all.

Knowing what AI tools exist and actually running them are two different things. That's the trap embedded in SaaSTR's updated VP of Sales interview guide — and it's a trap the article sets while correctly identifying the stakes. The piece is right on the elimination round: "we're exploring it" disqualifies a candidate in 2026. That's a legitimate bar. Where the framing breaks down is prescribing questions as the screen. Asking a VP to describe their AI tool usage is the same category of mistake as asking a rep to describe how they handle objections. Verbal fluency is precisely the thing that masks the absence of real behavior. You've built an interview that rewards the candidate best at talking about the signal — not the one producing it. We've all sat through pipeline reviews where a rep walks the deal stages with confidence and the forecast still misses by 40%. The words were right; the activity wasn't there. Hiring for AI fluency is landing in the same trap. A VP who can narrate their stack in a structured Q&A is demonstrating interview skill. The VP who pulls up a live Clay workflow mid-conversation is demonstrating something you can actually manage to. Those are two different screens, and only one of them transfers. The analogy that holds: a new hire who can walk your sales methodology cold in a training role-play isn't the same as a rep who's run thirty discovery calls with it. That's why top programs include a live call before offer. The same logic applies to VP AI screening. The candidate who opens the tool closes the question. The candidate who describes the tool reopens it. Before the next VP interview, add one instruction to the prep note: "Bring something live." Not a deck about AI. Not a use-case narrative. A working session. The demo tells you what the debrief cannot. #SalesLeadership #AIAdoption ---

We just wrapped SaaStr AI 2026, and the sponsor engagement leaderboard is in. It measures the one thing a sponsor actually cares about: how many leads they pulled from 10,000+ B2B + AI founders, op…

Customer Success may be the next SaaS function that gets exposed by AI. Not because CSMs are bad. Because the old model was built around managing accounts, not changing outcomes. The SaaStr piece on Lovable, Harvey and AssemblyAI had one uncomfortable line running through it: Customers do not want a better QBR. They want someone who can help them build, adopt, and prove value faster. That is a very different job. AssemblyAI found technical buyers got defensive when they heard "customer success." Rename the role to forward deployed engineer and suddenly the same work attracts a full candidate pipeline. Lovable replaced a traditional CS platform with its own command center that ships weekly. Harvey still does heavy in-person change management because legal AI is not a software rollout. It is behavior change. The provocative part is this: AI may not reduce the need for post-sale work. It may make the old CSM playbook look too shallow. If your CS motion cannot build, teach, measure, and adapt at product speed, is it really customer success?

📡 𝗦𝗮𝗮𝗦𝘁𝗿 𝗔𝗜 𝗔𝗻𝗻𝘂𝗮𝗹 𝟮𝟬𝟮𝟲: 𝗧𝗼𝗽 𝟭𝟱 𝗦𝗽𝗼𝗻𝘀𝗼𝗿𝘀 𝗥𝗲𝘃𝗲𝗮𝗹 𝗕𝟮𝗕 𝗕𝘂𝗱𝗴𝗲𝘁 𝗔𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 The SaaStr AI Annual 2026 sponsor engagement leaderboard is out, revealing the top 15 sponsors who pulled the most leads from 10,000+ B2B and AI founders. The sponsors' performance indicates where B2B budget is being allocated, with a focus on LLM integration and scalability. 💡 A game-changer for B2B founders and tech leaders alike. Read more on SaaS Sentinel: https://lnkd.in/e4bwGV7s #SaaS #B2B #Startups #SaaSSentinel #AI #GenerativeAI #Tech #LLM

SaaStr Ai is the world's largest community for B2B software founders, executives, and revenue leaders...bringing together tens of thousands of operators each year to share the playbooks, relationships, and insights that help companies scale from startup to industry leader. It's the best community in all of B2B! They are one of the first companies to be bold and leverage Qualified from Salesforce to modernize and scale inbound engagement with AI-powered conversations for their events at SaaStr. ✨Amelia AI✨ helps SaaStr engage attendees, sponsors, and prospective customers across web and email, personalize interactions at every stage of the journey, support global audiences with multilingual engagement, and operate with always-on agentic AI. Go check ✨Amelia AI✨ out at saastrannual.com! Jason Lemkin and Amelia Lerutte are leading the way when it comes to building agents for their business. They have over 20+ agents working (https://saastr.ai/agents) for them across a variety of use cases. I encourage you all to learn from them as they are truly the thought leaders. In fact, here's a shameless plug from Jason and Amelia at their latest conference...

I would not run another open-ended demo before you have scoped the pilot that follows it. Here's the pattern I keep seeing. A buyer is interested. Sales runs a great demo. The buyer says "let us play with it." Three weeks later the deal is in limbo, nobody agreed what success looks like, and the champion has gone quiet. The diagnosis: an unscoped trial is not a sales stage. It's a place deals go to die slowly. A structured pilot is table stakes now, not a nice-to-have. The 2026 GTM data is clear that the teams converting evaluations into revenue are the ones who design the proof, rather than the ones who hand over a login and hope. So scope it before you start. Three things, agreed in writing: 1. The success metric. One number the buyer will check at the end. Not "we liked it" but a measurable outcome they defined. 2. The time box. Two weeks, not "whenever." A pilot with no end date never ends. 3. The decision. What happens if the metric is hit. Name the next step and who signs. A pilot without those three is a free trial wearing a suit. At Series A this is the single highest-leverage change you can make to your motion. It costs nothing and it filters tire-kickers in the first week. Scope your next eval with a number, a deadline, and a decision attached. Then comment below with the success metric you would pick. I am collecting patterns across teams. Source: SaaStr — https://lnkd.in/dHEWTrts #RevOps #SalesMotion #POC #B2BSaaS

The founders most at risk in 2025 are not the ones ignoring AI. They are the ones who are worried about it and still running the same company they were running in 2023. Anxiety is cheap. It does not close the gap. It does not change release cycles. It does not rebuild GTM. It does not signal to investors, customers, and operators that this founder is moving at the speed the market requires. Jason Lemkin's 2025 SaaStr analysis is blunt. Founders anxious about AI but still running quarterly cycles and three-day office weeks have a coherence problem. Their actions do not match their stated concern. That misalignment is visible to everyone deciding whether to bet on them. The Slush 2025 Startup Struggle Survey found the same. Founder concern about AI has surged. Operational behaviour has not. Most founders are processing the threat intellectually and stopping there. That gap has a cost. Urgency looks specific. Faster release cadence. A rebuilt GTM that reflects how AI is changing buyer behavior. A public, non-consensus thesis about where your market goes in the next 24 months. One that would be wrong if you are wrong. Madrona's 2025 AI success analysis found that founders with the strongest investor relationships right now can articulate exactly what they changed in the last 90 days because of AI. Not what they are planning to change. Not what they are worried about. What they changed. That gap between anxiety and urgency is where founder credibility is won or lost right now. What have you changed in the last 90 days?

Looking forward to joining a panel with the Launchpad.io in Waterloo and Toronto next week! I'll be reunited with John Huehn post our talk at SaaStr to continue sharing more about Outcomes-as-a-Service. If you are in the Waterloo or Toronto area, please come out to what is sure to be a great event.

A few weeks ago, we attended and sponsored SaaStr Ai in San Francisco. There's something you can't replicate about being on the floor, face to face with the people living and breathing the problems you're solving. The conversations that stood out weren't just about cap tables, scaling complexity & integrating AI - they were about employees & getting the most out of their equity. Real conversations. Real problems. Apparently very good merch too 😉 🧢 Britt de Visser Garrison G. #SaaStrAI #StartupEquity #EquityManagement

AlleyWatch published its April 2026 funding rundown last week. Buried in the list: Avoca, a New York company building AI agents for inbound and outbound phone, closed a Series B and crossed $125.5M in total equity funding. The thesis is the same one every AI SDR has pitched for 24 months. Replace the human on the phone. Run 24/7. Pay per conversation. The difference: Avoca is not chasing cold outbound. They are eating inbound first. Customer service. Lead intake. Appointment booking. The boring stuff. That is the right play. AI on cold outbound is still getting flagged as spam. AI on inbound, where the buyer raised their hand, is a much shorter trust gap. #AISales #B2BSales #SaaStr

Most CSM hiring loops are screening for the wrong thing. And it's the thing that's easiest to put on a resume. I keep seeing leaders screen candidates on two signals: which tools they've run (Gainsight, ChurnZero, you name it) and whether they've executed the standard plays. Both are reasonable. Both are easy to interview for. And both, I think, are increasingly the wrong bet. Jason Lemkin's writeup from the SaaStr AI 2026 CS track is the best thing I've read on why. One line has been rattling around in my head: leaders are hiring builders over playbook-runners. "Show me your projects" beats "tell me your process." Here's what worked for us when I was building CS at Dell: the people who moved the number weren't the ones with the cleanest QBR cadence. They were the ones who could read value across three layers. How we deliver value. The motion, the workflow, the mechanics. This is what tool-and-play experience screens for, and it's table stakes. How the customer receives value. Are they adopting the right workflows, or just logging in? The article makes this point sharply: daily use of the wrong workflows still ends in churn. How the customer perceives value. Do they connect what happened to an outcome worth paying for again? This is the layer nobody interviews for, and it's the one that renews the account. The reason perception matters most is the cleanest idea in the whole piece, from John Gleason: he framed every business model as the distance between when a customer pays and when they pay again for value. If the customer can't perceive the value, that distance never closes, no matter how flawless your delivery was. So I'd push back gently on the instinct to hire for tool fluency and play-running. Not because that experience is worthless, it isn't, but because it's the most legible thing on the resume and therefore the easiest thing to over-index on. The harder skill, sensing how value is received and perceived, is the one that's about to matter most. Curious whether other CS leaders are seeing the same thing in their hiring loops. https://lnkd.in/eg-KJ6Ba

New!! Who Got the Most Leads at SaaStr AI Annual 2026? The Top 15 Tell You Exactly Where B2B Budget Is Going: We just wrapped SaaStr AI 2026, and the sponsor engagement leaderboard is in. It measures the one thing a sponsor actually cares about: how many leads they pulled from 10,000+ B2B + AI founders, operators, and buyers on the floor. Here’s the full top 15 by engagement: Replit — 1,423 leads (Vibe Coding / AI... Continue Reading

Build-vs-Buy - the 90/10 software rule small businesses can use There's a rule going around among AI-native operators, cleanest version from SaaStr (a media company reportedly run by about three people and a couple dozen AI agents): buy 90% of your business software off the shelf, and build only the 10% where no tool fits. Don't try to out-build Salesforce in a weekend. But the slice that's genuinely yours — the workflow that drives your business, the one no vendor sells — build that. The split isn't new. Good engineering leaders have always bought commodity software and built only their differentiators. What's new is who gets to follow it. For decades the custom 10% was a luxury good — months of work from six-figure engineers, hundreds of thousands of dollars before anything shipped. Big companies funded it; a 40-person distributor or a regional clinic couldn't. So small businesses bought 100% off the shelf and bent the business to fit a tool optimized for the average customer, which is nobody's actual case. AI didn't change that by writing flawless software. It doesn't. It removed the grunt work — scaffolding, boilerplate, glue code, test stubs — that made building the 10% headcount-intensive. The cost of that custom slice fell by roughly an order of magnitude, so one capable, AI-fluent developer now covers what a team's budget used to. And one such developer is something a small business can finally afford. The catch is worth stating plainly: letting a model generate unsupervised produces slop — code that demos well and breaks in production. An MIT study found ~95% of attempts to put generative AI into business processes show no measurable return. The barrier that fell is writing the code; making it grounded, capped so a bug can't run up a fortune, and instrumented so you can see where the money goes is a separate discipline. That's the part I build around — and the honest boundary holds: if the work needs a standing team, that's work for a team, not a thing to fake with one person and a model. The test for everything else: is running this product someone else's full-time job? CRM core, payments, auth, accounting — keep buying. The custom 10% is for what's specific and differentiating to you. I built MailPilot as my own checkable receipt: a production AI agent that reads an incoming email, searches a knowledge base, and replies with a sourced answer in under a minute. The code is open, every model call is traced, and you can email the agent yourself and watch what it does. Read the full post: https://lnkd.in/gzeXJk-z