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Curated SaaS and tech insight from around the web repackaged for people to put to good use
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1. SaaS METRIC OF THE WEEK: ASP or Average Sales Price. ASP tracks the average price new customers pay when signing up. Unlike ARPA, which includes renewals and expansions, ASP spotlights initial deal size—a key signal for sales performance and pricing strategy. Track it by region, plan, or channel to optimize revenue growth.
2. UN-SCALE: I've talked about this a few times - we're all focused on building out that repeatable, scalable business model, but along the way, there are things that have to be done that are totally un-scalable. This article highlights three specific non-scalable things sales teams should be doing right now. 3. AI-WARS: With OpenAI's new Browser, 'Atlas', and Perplexity's Comet, a new AI war has started for the Browser - shots are being fired at the dominance of Chrome. Security nightmare? You betcha, but it's part of a bigger play to own the full stack: model, agent, and now interface. The Chrome vs. ChatGPT battle is officially on. 4. AI SECURITY: Another week, another AI report but this one complements the AI Security nightmare in #3 above, Aikido's 2026 State of AI Security has to be a bit of a wake-up call: 90% of AI/ML repos have unresolved security issues, and model-level risks (e.g., prompt injection, training data poisoning) are rising - not even bringing up the browser issues. Security needs to shift - again. 5. FUNDRAISING: Going into fundraise mode is a bit of a full-time job, so check this great free AI-powered fundraising kit. Includes investor matching, warm intro prep, and a due diligence checklist. (and built by founders, not VCs - with a sprinkle of AI on top). 6. LEADERSHIP: Conflict is not necessarily a bad thing, and avoiding conflict is the fastest way to stall your team. In that article, Hypergrowth Partners makes the argument that great companies normalize tension and use it as a growth lever. 7. MARKETING: In many circles, LinkedIn is seen as a bit cringe, but it compounds. MKT1 breaks down the "LinkedIn Flywheel" - how founders and operators can use lightweight posting, engagement, and repackaging to build real pipeline without becoming a <insert vocal fry> thoughtfluencer. 8. TASTE: In our ever increasingly overcrowded SaaS markets, taste can be a competitive advantage. Sam Tomlinson explains why it's more than just aesthetics, as taste can help teams pick the right problems, craft better products, and earn trust faster. 9. SALES: Outreach analyzed millions of sales activities to uncover what's working as we start wrapping up 2025. Top reps are now sending 20% fewer emails but book 25% more meetings. Personalization still wins, but speed to first touch and persistence look to be the real differentiators. 10. CASE STUDY: How Intercom built a $50MM ARR Empire using strategic Content Marketing and SEO. POD OF THE WEEK: Also a bit of a case study, and I've already shared this out a few times. Cursor is turning into a project manager's dream product-management system - featuring Dennis Yang from Chime. 1. SaaS METRIC OF THE WEEK: CARR - Contracted Annual Recurring Revenue. This is a forward-looking SaaS revenue metric that estimates the maximum revenue size of a SaaS company, measuring current recurring revenue from your SaaS P&L and future revenue that sits in newly won customer contracts.
2. PRODUCT-MARKET FIT: Finding Product-market fit isn't a one-and-done event—just as the product you ship, it's an ongoing process. This updated playbook breaks down the key signals, from retention curves to sales velocity, and the tactical moves to iterate faster. If you're still guessing, this is your roadmap. 3. UNDERSELL: If expansion fits into your growth strategy (it should) take a read of two-part series from Tomasz Tunguz and Bill Binch - part one is deliberately underselling as a sales strategy to minimize churn and increase upsell/expansion opportunities as a land and expand strategy and post 2 is an expansion of land and expand witch details how to structure a Startup sales team for optimal land & expand. 4. COMPENSATION: Early-stage comp is more art than science, and most founders are so hectic at this point that it's easy to get it wrong. This First Round piece offers tactical advice on what to break (like "market rate" rules), what to follow (like transparency), and how to build trust before you build out pay bands. A little more in talky format here. 5. PRODUCT: Here is a tech-ism I like - AI changes everything and nothing at all. Teresa Torres is here to remind us all that AI is great and all, but great product work still always starts with understanding user needs. (and here is how you find out what they care about). 6. MENTOR: SaaS founders don't need perfect advisors; we all need people who've broken shit and learned from it. This guide covers why mentorship matters, how to earn it, and how to keep it useful. Includes outreach templates and cadence tips that can work. 7. VENTURE: Good VC pulse check. This pod n' post breaks down the "Great VC Shuffle," what's driving TAM fatigue in AI (bubble anyone?), and why $1B ARR is still just getting started (broken liquidity pipeline). Good follow-up to the State of Software signals from last week's newsletter. 8. LIQUIDITY: Fast follow from #8 above. If IPOs stay rare and private rounds dry up, who buys the next crop of SaaS companies? Lemkin breaks down the likely acquirers (and what they're really after). Probably means some top-of-the-heap consolidation is on the way. 9. DECIDE: Good decision-making isn't just speed, it's perception, insight, and good judgment - which this Forbes article consultingly wraps up as discernment. It also has 10 sharp rules to upgrade how you make calls as a founder or operator. Not new ideas, just well-said reminders worth keeping as an easily accessible reminder. I prefer this analogy, too - A fire ain't no emergency if you are the Fire Department. 10. CASE STUDY: AWS and AI - AWS currently dominates Public Cloud (did you forget what happened last week?) - we all assumed it was supposed to dominate AI too. But bloat, bureaucracy, and missed bets are showing up and slowing it down. Bloomberg breaks down why Amazon's cloud empire is stalling while others race ahead. POD OF THE WEEK: No matter what Robbie says in this Podcast from Lenny's Podcast - Google Search IS changing (60% of Google Search is now unclicked). But launching AI Overviews was cool, and he has also scaled Stories and Reels at Instagram. 1. SaaS METRIC OF THE WEEK: Burn Multiples tells you how efficiently your startup converts cash burn into ARR. It's the clearest signal of whether your growth is efficient - or just an expensive way to burn money. This breakdown covers benchmarks by stage and why 1.5x is the new magic number for survival.
2. FINANCE: Think you understand your P&L? Probably not well enough. This teardown by OnlyCFO explains how each line of the income statement connects to growth, margin, and cash. Especially useful: benchmarks, red flags, and why you can't ignore gross margin math at early stages. 3. AI: The 2025 State of AI report just dropped from Airstreet, and it's (313 slides) huge. Training costs for frontier models are flattening, while open-source LLMs continue to close the quality gap. AI safety is (finally) growing up, with more labs publishing evals and investing in red-teaming. AI-first startups are now scaling into tens of billions in revenue (bubble anyone?), NVIDIA still dominates the hardware race, and power supply is fast becoming the new bottleneck. The PDF Version is here, as the Google Slides are a little annoying. 4. STATE OF SOFTWARE: This one plays hard into both #1 and #3 above. The ICONIQ State of Software 2025 is mandatory reading because IMO it's a reality check: the old playbook is officially dead. While the Rule of 40 is still the strongest predictor of valuation, median growth for SaaS companies has dropped to 19% YoY (down from 29% in 2022). AI-Native companies are rewriting what's possible, scaling 2-3x faster than traditional SaaS peers. A new (and bonkers) data point: they're hitting $100M ARR in just 1-2 years, often with fewer than 20 employees. Side note for #1 above - public SaaS firms with Burn Multiples below 1.5 are commanding a 40% valuation premium. 5. GTM: So, based on #4 above, traditional Go-to-Market isn't dead, but maybe it's dying? So shit gotta change. Jason Lemkin warns that mediocre, copy-paste GTM executions are failing faster than ever. AI hasn't replaced sales and marketing; it's made bad playbooks easier to scale, so only truly excellent, AI-augmented execution wins. Buyers want outcomes, not promises. 6. FACILITATE: A super fun and VERY bookmark-able resource this week. It's a library of tools available to facilitate your next session with people or a team, including team building, brainstorming, icebreakers, and check-ins. They are all there! 7. FUNDRAISING: What does it take to raise a Series A? How do you break through the $10M ARR barrier and secure growth capital? More Intelligent offers a comprehensive guide, along with must-hit fundraising milestones—from scaling your go-to-market motion to tightening unit economics and KPIs. 8. VIBE CODING: I give Vibe Coding a (deserving) amount of shit, but to its credit, the idea is maturing. This piece traces that shift - from building fast with AI-assisted tools. Platforms like Solid are bridging the gap with full-stack code and proper control. But the "vibe wall" is real: fast prototyping hits limits without control and scalability. 9. PRICING: Your pricing is broken (but that's kinda OK) - but hey, it's not totally because of your tiers. Kyle Poyar breaks down why most SaaS pricing fails: it's static, and it mashes with my commentary of pricing is like software - it's never done. The best teams iterate on pricing every quarter, not every couple of years, to track the real value. His post unpacks seven pricing traps (like sticking with usage-based just because it's trendy), and gives a roadmap for fixing your monetization blind spots. 10. CASE STUDY: The $2 Trillion Founder Playbook is all about how Larry Page quietly reclaimed control of Google after being sidelined. Page played the long game—shedding titles, backing bold bets like Gmail and Android, and redesigning Google's structure for scale. POD OF THE WEEK: The video version of number 5 above about the new Go-to-Market thinking needed for success in today's markets from SaaStr. 1. SaaS METRIC OF THE WEEK: Forecasting: Forecasting MRR is more art than science - but this post gives you both. A smart walk-through of how to project MRR using cohort-based logic, with a FREEEEE Excel template that looks like it might actually work well.
2. GTM: Tomasz Tunguz just dropped the GTM guide every startup needs. Learn when to hire your first AE (after 10 founder-led deals is a great tech-ism), how to pick your sales model (field vs inside vs self-serve or a hybrid), and why the best GTM teams layer focus before they layer headcount. Includes pipeline targets, comp models, and team structures from $1M to $100M ARR. 3. AI PRODUCT: There is a bit of OpenAI in this week's newsletter - so let's start here with an AI-ism. AI features aren't AI products. This teardown of OpenAI's strategy shows what it takes to go beyond a wrapper: latency-aware UX, agent loops, invisible value, and goal-driven design. But shit moves so fast - that even AI apps don't move as fast as the market. 4. OPENAI: OpenAI Dev Day 2025 happened last week, and a few bombs dropped: GPT-5.5, a native app SDK, and "Agents as a Service." But the bigger shift? Distribution. A new AMD chip deal, first-party hosting, and native monetization rails signal OpenAI's ambition to own the full stack - infrastructure to app store and operating system. 5. TALENT: Is there a tech talent shortage, or is it just a mismatch? The WSJ reports that while layoffs have flooded the market, companies still can't find the right skills for AI, security, and infrastructure. 6. MARKET: Check out the GTMfund's take on the State of the Market: 75% of seed-stage startups have <12 months runway, 60% of Series A+ aren't hitting growth targets, and 25% of sales teams are shrinking. Shheeeeeeeeet. Buyers are more risk-averse, and PLG is on the rise again - not for price, but for speed. 7. SALES 1: Early-stage selling is heavy on Founder-Led sales, but founders often get sales wrong because they confuse product belief with buyer readiness. This playbook is great and covers how to build a sales process from scratch, including market mapping, email scripts, handling objections, founder-led tactics, and why closing isn't the hard part - it's getting to the first meeting. 8. SALES 2: What do you do when growth stalls? Jason Lemkin lays it out for us: double down on sales efficiency, revisit churn (see 10 below), and stop assuming marketing will save you. TL;DR: The answer is almost always "more pipeline." 9. MULTI-LLM: I often run multiple LLM agents on one task just to verify output - I have a lot of hallucination trust issues emerging. Simon Willison explores the rise of using agents in parallel for coding - as it's not just faster, but safer. Think multi-threaded prompts, error-checking via ensemble output, and LLM diversity as a helpful hedge against those friggin hallucinations. 10. CASE STUDY: A two-year mission to reduce churn. This post breaks down what actually worked with onboarding tweaks, activation metrics, internal alignment (and what didn't). The big takeaway is that there are no silver bullets, just sustained efforts to figure it out. POD OF THE WEEK: Finishing it with a little more OpenAI, Reforge founder Brian Balfour on why ChatGPT is on track to become the next major distribution platform. 1. SaaS METRIC OF THE WEEK: AI METRICS AI ARR isn't always what it seems. MostlyMetrics breaks down how companies are stretching definitions to inflate AI-related revenue — bundling, attribution games, and vague "AI features." Timely reminder: inspect the footnotes, stay cynical!
2. ESOP: Employee Share Option Plans are a wonderful idea to incentivize and retain great staff, but under the hood, ESOPs are complex, especially with changing valuations, both positive and negative, in today's market. Check out Airtree Venture's best practices for communicating the value of ESOP to teams. This article also has a bonus financial model template (value calculator, salary package calculator, and vesting schedule). Check this cheat sheet for common ESOP terms. 3. BUYERS vs USERS: The person writing you a check is not necessarily the same person getting value out of your business. So take a read of this insightful article from HeavyBit on differentiating messaging based on this premise and the different profiles. 4. ESOP BENCHMARKS: A fast follow from above is this wonderful site that has compiled a set of Option benchmark data, comprising over 20,000 option grants from more than 1,650 startups across the US and Europe, sorted by Seed or Venture stage. Carta has also recently done the math and found that for seed-stage valuations ($1M to $10M), the median pool size is 12.9% 5. LINGO: Here is a mega Tech Dictionary update for you because AI is changing who writes what, and when, so we need new terms for all that: Vibe Coding, Spec-Driven Dev, Prompt Jail, and more. 6. AGENTIC: This article and also Slide Deck breaks down what the "Agentic Era" of software actually means IRL: autonomy, context awareness, and goal-driven UX. 7. VENTURE: Carta's Q2 report is out and shows early-stage VC is still holding steady - but overall LP appetite is cooling. Time to liquidity is also growing, and markups are slowing. 8. BUBBLE: Is AI in a bubble? One-hundred-friggin-percent it is! But maybe all bubbles aren't all bad? Azeem Azhar takes a look at how over-capitalized hype cycles can actually drive real breakthroughs, as long as excess gets channeled into things like infrastructure. 9. GROWTH HACKING: Hacks that work edition: Growth hacking isn't dead—it's evolving. Foundation shares some cutting-edge strategies to scale in competitive markets. From viral loops to leveraging micro-influencers, there is some true gold in there. 10. CASE STUDY: Complementing #9 above, real growth hacking is about rapid iteration across product, marketing, and data. This First Round piece unpacks what growth hacking actually means today, with examples from Airbnb, Dropbox, and more. POD OF THE WEEK: Growth by experimentation, Albert Cheng shares how his teams run 1,000+ experiments a year (!) to unlock growth. 1. SaaS METRIC OF THE WEEK: Churn. See #2 for more on Churn. According to CatchJS, though, we're all calculating churn rates wrong. If you love Statistics, the article is well worth reading, and it even gives some Python code to perform the more complicated probability-based equation they recommend. You can then check out this tool (as a handy Google Sheet) from Newfund as a way to analyze the strength of revenue streams for any B2B startup. A complementary article outlining the methodology behind the tool is here (and you should read it first).
2. CHURN: See #1 above; it's the ultimate leaky bucket. BVP's guide on tackling customer churn explains how to identify root causes and implement strategies to reduce attrition (that can be terminal). Analyzing churn data, improving customer onboarding, and enhancing product value to retain users are all in there. The guide also provides actionable steps for creating a comprehensive churn action plan to plug those leaks. 3. SALES: Do technical products need a different type of sales process vs traditional enterprise SaaS products? Check this guide on Tech SDRs. These Reps, understanding developer needs, are key to selling DevTools efficiently. 4. PRICING: Are AI subscriptions broken? This piece argues usage is too spiky, infrastructure too costly, and churn too high for any SaaS-originated flat-rate pricing to hold. Pay-as-you-go may be the only model that scales sustainably. 5. UNIT OF WORK: How the heck do we all quantify what a "unit of work" is with AI? In SaaS, we all know it pretty well - it's a user capacity or a workflow. In AI, it's waaaaay fuzzier. This post digs into how designing around discrete, value-linked units will make AI tools more usable (and billable). 6. AI PAYMENTS: Speaking of billable (see above if ya skipped it). Google just launched AP2: Agents to Payments. It's an open protocol for connecting LLM agents to tools, data, and real-world actions — including transactions and Units of Work ;-) It's kinda like Stripe for autonomous AI workflows. 7. OPERATIONS: Oh - this one is short but good (and bleeds into these two longer reads here and here)! High performing companies run on "accountability machines" - simple, repeatable systems that clarify ownership and drive consistent execution. 8. SEARCH vs ASK: As mentioned in a newsletter earlier this month, with 60% of Google searches ending in zero clicks, the shift from search to ask is accelerating. ChatGPT already sees 300M+ monthly queries, so how much of that traffic is search-like? This article reframes this as an SEO problem for an "Ask Engine" world — where ranking means getting cited by an LLM, not just showing up on Google - how do you even measure that?? 9. FUNDRAISING: Ouch - This article doesn't mince words: most investors don't care about your business. What they do care about is how fast it can grow and how big the outcome could be. If you're building slowly and sustainably, you're maybe not the product for them. 10. CASE STUDY: I love studies on what NOT to do, and AI is a great one - it can 10x your output, or blow up your credibility. This firsthand account of an intern using AI to write code, emails, and even Slack messages is equal parts impressive, amusing, and alarming. POD OF THE WEEK: Why AI will make everyone a manager, and how the same skills you use to manage people today will be essential for also managing AI. 1. SaaS METRIC OF THE WEEK - VC MATHS: IRR vs Return Multiple — they sound similar but measure totally different things. This post breaks down the math VCs actually use to rank funds, justify exits, and explain why speed sometimes beats size.
2. CHIP WARS: After the US government took a 10% stake in Intel last month, Intel and NVIDIA just announced a major partnership. Intel will manufacture NVIDIA's next-gen AI chips — a move that could reboot Intel's foundry biz and reshape the AI infrastructure race. Huge signal bringing together two of the biggest players in the industry. 3. M&A: Navigating some kind of acquisitions process is a relatively unexplored topic in this newsletter, so check this guide to running an M&A process as a Founder from First Round Review. 4. LANDING PAGES: Want to get better at creating effective landing pages? Scrapbook's SaaS landing page optimization checklist provides a guide to creating compelling headlines, using high-quality visuals, optimizing for mobile, indexing, and, of course, including strong CTAs to boost conversions. BONUS: How to write killer CTAs. 5. PITCH DECK: A great pitch deck resource from Alexander Jarvis, who hosts almost 540 of them (and 10,000 pages)! The cool feature here is that you can search/filter startup decks by stage, topic, and country. 6. SALARIES: Want to retain startup talent? Their pay still matters. This breakdown shows how overall compensation mix (cash vs equity) impacts retention, with really clear data points by role, stage, and geography. Bookmark this for your next comp review for sure. 7. DATA MOATS: The idea that data creates a durable moat? It may be overhyped. The Platforms Substack argues most pure "data moats" leak — fast. Unless you've got proprietary generation and tight reinforcement loops, someone else can out-model you. 8. BOTS: One-third of the internet is now bots (see the live feed of that here) — and we have some very good bots out there, but most of these are not the good kind. Vice digs into how fake traffic, scraped content, and automated engagement are distorting the web. It's not just noise, it's business models built on BS that's enshittingifying what we have. 9. MANAGEMENT: Ever feel weird running a startup like it's a friggin' classroom? If you nodded your head, you're not alone. This piece unpacks "educational trauma" — why many leaders default to teacher mode, and how to build an adult-to-adult culture instead. 10. CASE STUDY: OpenAI isn't just building models — it's building a distribution machine. This breakdown shows how ChatGPT's product, pricing, and plug-ins mirror some classic SaaS GTM… but it all moves faster than traditional SaaS ever could. And it's publishing how people use their products. POD OF THE WEEK: Complementing number 2 in this week's newsletter is from a16z on the Chip Wars. A Deep dive into the AI chip race, TSMC choke points, and why NVIDIA's real moat isn't just hardware. 1. SaaS METRIC OF THE WEEK: CLTV to CAC Ratio: This is the classic signal of go-to-market efficiency. Everyone quotes 3:1 (too low, likely not PMF, too high, you ain't spending enough on marketing) — but this breakdown goes deeper with benchmarks by sales motion (PLG vs enterprise), contract size, and stage. Bonus: includes a free model template to run your own numbers.
2. VENTURE: PitchBook's Q2 report is out: global VC fundraising is down 32% YoY, and new fund launches hit a decade low. But dry powder is very much still around (and remains high), and early-stage rounds are holding firm. The market is slow, but not dead. 3. BOTTOMS UP: Bottoms up adoption is hard to crack😉 (learn more about the bottoms up model here). For example, according to Gergely Orosz, Hashcorp has a total of 4,300 customers, but only ~800 of them generate 90% of their annual revenue. And here is how to forecast. 4. AI: Like the great SaaS Ponzi schemes I joke about — AI may be worse. When we all have 100 agents, who's actually doing the work? SaaStr explores what may happen next: consolidation, vertical focus, and agent collapse? 5. WORKFLOWS: Workflows are eating SaaS. Clouded Judgement breaks down why every SaaS company wants to be a system of action — not just record. Usage-based pricing, AI features, and margin pressure are all fueling the shift. 6. SCALING: Sure, software is scalable, but Startups don't scale by adding people — they scale by building systems. This breakdown covers how to layer ops, reduce founder dependency, and keep complexity from killing momentum. 7. LOOP MARKETING: Hubspot has a brand new term for your teh dictionary: Loop Marketing. It's all about ditching more traditional funnels we all know well and embracing real-time feedback loops designed to connect product, content, and community to drive growth. Sounds a bit froo froo, but this matters because now about 60% of all Google searches end in zero clicks - users are getting answers from AI overviews without ever visiting your website. Looping means getting cited there. 8. SOFTWARE 3.0: Bessemer takes a crack at mapping the future of dev tooling in the AI era and are calling it "Software 3.0," - which is eval-first workflows, agentic infrastructure, and tools that help devs manage hallucinations, kinda the new style of bugs. 9. PRIVATE MARKETS: Super interesting question: What if AI doesn't just disrupt how companies operate — but how they're valued? Colossus explores how AI could reshape underwriting, due diligence, and exits in private markets. 10. CASE STUDY: Do your profit margins need a tweak? Here are 40 strategies for improving your profit margins from Sameer Dholakia, with a case study on SendGrid (from high burn to growth and IPO) POD OF THE WEEK: From CJ Guftason, how much revenue do you need to IPO in 2025? 1. SaaS METRIC OF THE WEEK: Attribution - Marketing attribution models help marketers assess the data behind user touch points and conversions to understand the return on Investment and effort. Learn more here on Single-touch attribution models, Multi-touch attribution models, attribution tools, and more to make better data-driven marketing decisions.
2. HOMEPAGES: IS your homepage a barrier to sales, opportunities, value prop comms?? This article makes the case that it is (as potential users want to get their hands on the end product as quickly as possible) - it's a time to value play across PLG and classic Sales lead SaaS. 3. CONTRADICTION: Point Nine Capital discusses the importance of embracing contradictions in business and also uses one of my new favorite phrases, "Startup Advice Industrial Complex". Startup Leaders should balance conflicting priorities, such as growth vs. profitability and innovation vs. stability, to drive success. In theory, understanding and managing these paradoxes should lead to more resilient and adaptable companies (and teams). 4. DESIGN: For the first time ever, I got the most comments from last week's post based on the Pod of the week - focused on Design Thinking for non-humans (agents, cars, etc), so I figure I should up the Product/Design listings in this newsletter. Most SaaS software/tools today feel like Costco - designed for bulk use, not necessarily individual joy. This sharp piece explains why "good design" now means consistency, speed, and scale over delight or elegance. 5. VC LANDSCAPE: AI now powers 47% of all new VC-backed startups. The Median time from pitch to term sheet? Just 6 days!!!!! Whut?? Infra is hot (as I mentioned last week), fintech is cooling, and round sizes are holding steady. Always Charts galore with The Data Driven VC. 6. MARKETS: Silicon Valley Bank's H2 2025 report is out (yup - SVB is still very much around): flat funding, cautious investors, and a "slow burn" recovery - all the negative hits still on repeat. But signs of life in AI infra and B2B SaaS. Profitable growth remains in vogue - burn multiples are under the microscope. SaaStr also takes a deep look into the market and adds color - some startups are thriving, while others are circling the drain. 7. AI MARKET SIZE: SaaStr pulled some data from a bunch of different sources and made a bold call: AI will be bigger than cloud by 2030. (Despite being 15 years its junior). AI is scaling so much faster, embedding deeper, and monetizing more aggressively than cloud ever did (or could). 8. VENTURE: Anyone that's raised here has heard the dreaded phrases: "Too early," "too crowded," "not in our thesis" - VC-isms. This article breaks down the real reasons VCs say no. 10 rejection themes, decoded with some brutal clarity. A must-bookmark/read in prep for your next raise. 9. EARNINGS: Snowflake just posted $900M in Q2 revenue, growing 35% YoY. Tomasz Tunguz unpacks the numbers - usage-based pricing is working, AI workloads are rising, but headcount growth is flat. Efficiency remains the neo-scale. 10. CASE STUDY: SaaStr shipped 3 IRL apps using Vibe Coding (and lived to tell the tale). What worked: shipping fast with small teams. What didn't: vague specs and AI guesswork. Brutally honest, super helpful. POD OF THE WEEK: Benchmark's Miles Grimshaw drops gold on what actually makes startups venture-scale. Jason Lemkin (SaaStr) and Marc Benioff are also there and go deep on what makes SaaS great — and what breaks it. 1. SaaS METRIC OF THE WEEK: Growth Endurance Score (GES). This is a new one for me, but it's a keeper. It's a metric that assesses a company's ability to sustain growth over time (something I have been discussing quite a bit lately, as I try to maintain my own growth momentum). GES measures this efficiency by factoring in both net retention and customer acquisition efficiency. A high GES correlates with long-term business health and resilience. This score provides valuable insights for businesses aiming for consistent, sustainable growth. Bessemer has drilled deeper into it and plotted ARR growth lost YoY, and found that the decay is fairly predictable at 30%. That's a benchmark - in other words, you should expect next year's growth rate to be 70% of the current year's, as the stakes get higher.
2. PRODUCTS: Balancing the needs of existing vs new customers is a hard product act to balance, and that push and pull is nicely described in this article with some great analogies and tips on how to influence the product roadmap, along with an article from First Round Review with a list of things to avoid when building highly-technical products. 3. AI NOISE: This is a great article, sending a warning that the signal-to-noise ratio in AI markets looks to be collapsing. As AI accelerates all kinds of content and capital flows, genuine information is getting harder to parse, distorting valuations and decision-making. So, the inevitable upcoming market correction may be less about fundamentals and more about all that noise. 4. STATE OF AI: I love me a good Bessemer Ventures Report. Their AI report is out, and it's a beast. TL;DR: Infra is hot, agents are messy, and the winners will balance open-source velocity with enterprise-grade plumbing. And it's kinda adding onto #3 above, over 50% of Series A+ AI startups are building infrastructure (vs apps or agents) — infra is where the early-stage dollars are going (and they are less noisy). Agents still hallucinate. Plumbing, not magic, will win IMO. 5. PR: Getting good PR if you're an unknown startup is hard (and also can be seen as a low priority in the endless stable of things-to-get-done) - but it's not as hard as you think without a publicist. Here is a great 101 article from Point Nine Capital (they call it PR for dummies) on how to get great press coverage. ChartMoguls also has an article on PR for SaaS, complete with sample scripts. 6. OUTAGES: Now is always a good time to front-foot your architecture. For techies, Google actually has a great article on Architecting disaster recovery for cloud infrastructure outages. Here is a good DR Plan article, and here is a good template. 7. GROWTH: Testing new tactics of marketing growth takes a lot of resources, and most of us often don't have much time for running experiments. Check out this Google Doc from Dashly, where they've collected 100 growth marketing hypotheses tested by their experts. (includes advert retargeting, wait list for product launches, niche glossaries, etc). 8. API DESIGN: You know the good thing about APIs? They are pretty much boring AF. That's the point. Sean Goedecke breaks down why a "well-behaved" API should feel predictable, invisible, and dull — like a fav spoon, not a Swiss Army knife. 9. MARKETING: Why do some B2B SaaS ads actually land? Because they nail three truths: product (what you do), emotional (why it matters), and cultural (why now). Stripe and Slack get it. Most don't. 10. CASE STUDY: Slack took 8 years to hit $1B ARR. Zoom? Just 4. Jason Lemkin asking the ultimate question: Does it matter? Because, maybe not. Saastr breaks down why long-haul growth often leads to stronger fundamentals (and fewer layoffs). POD OF THE WEEK: Fascinating thought exercise on what design is (As a design nerd, trying to answer that question is the cool bit). In the SaaS world, we are so CX focused - so what, in this new AI world, if that Customer was a non-human/machine? What changes from a product design and build perspective (API Design is a start) - new acronym alert - AX (Agent Experience). 1. SaaS METRIC OF THE WEEK: The Magic Number measures how effectively your company generates $$ via front-end spend - basically, new revenue generated over a specific period with the expenses incurred on Sales & Marketing during that same time frame. Check the SaaS CFO for guidance on calculating the Magic Number, and refer to this article that deconstructs it, highlighting that it's a complex metric influenced by various factors, such as market conditions and company spending, making it difficult to pinpoint specific areas for improvement.
2. PRODUCT-MARKET FIT: A long-running general rule (or a Growth-ism) in the Startup world is that getting to $1m of ARR is a strong sign of Product Market Fit (PMF). Kaiitlyn Henry from Openview runs contrary to this Growth-ism, stating that there's no specific revenue indicator that defines PMF, but also continues to write about concrete signals of PMF available beyond a $$ amount and gut feel. Read more about all those signals here. This sits well with Brian Balfour's work, who wrote an amazing article on the subject that is now almost 10 years old and still incredibly relevant for figuring out what stage(s) you may be at. 3. USER LED GROWTH: ULG is when your existing users become your biggest advocates, driving leads straight into your funnel. It's not for every B2B SaaS company, but when done right, it can build a flywheel that slashes your CAC and ramp times. A classic example is Dropbox's referral program, where users earned extra storage by inviting others—a powerful way to turn customers into evangelists one GB at a time. 4. MARKETS: Carta's Q2'25 State of Private Markets is out and shows venture deal volume up 17% QoQ, but check sizes fell (Seed –9%, Series B –6%). Median Series A valuations slid to $37M (down from $42M in Q1), while Seed valuations held flat. Liquidity is still tight: tender offers down 32% YoY. 5. SCALE: This is a must download. Mark Roberge, the founder of Stage 2 Capital and member of the founding team at HubSpot, has this incredible playbook for scaling. In the book, Mark has defined different stages of scale, with quantifiable measures for each of these stages, structures of the sequences, and signals of when to move from one stage to the next, with the optimal go-to-market design for each. 6. CC/CD: New entry for the tech dictionary: Continuous Calibration/Continuous Development (CC/CD). Unlike CI/CD, AI products drift without constant tuning. This framework highlights why calibration is as critical as shipping for long-term performance. 7. IDEAS: Hunting for your next SaaS idea? Check out 1-star reviews. This is similar to scouring Google Searches in that buried in customer complaints are unmet needs and broken workflows, which in reality is a goldmine for your next thingy. 8. AI RISKS: A core problem in current AI is its ability to be so wrong so confidently. Which really erodes trust. Here's the fix (pretty please, AI companies). Just build models that admit uncertainty and show reasoning. 9. AI: Worth pondering the hype. Casey Handmer argues AI's economic impact will dwarf expectations. Think trillions in productivity gains, new industries unlocked, and labor markets reshaped far faster than past tech waves. 10. CASE STUDY: If it's true that the IPO markets are slowly starting to creak back to life, Canva is shaping up as the next big B2B one. The design giant has crossed $3.3B ARR at a $42B valuation, with 185M+ MAUs. Their playbook is Freemium growth, rapid expansion into enterprise, and a relentless product velocity that rivals the best in SaaS. POD OF THE WEEK: Adding onto 5 above, Funnel and revenue math kindly explained by Mark Roberge and Matt Plank of Rippling in the Science of Scaling podcast. 1. SaaS METRIC OF THE WEEK: The nag Metric, I'm bringing this one out of the archives, as I have been nagged a bit lately (and I'm also away this week;-)): A call to action within a site or customer journey is kinda like a parent trying to get their kid to clean up their mess. It just gets a bit naggy after a while and gets mentally filtered out. This can impact your brand/NPS over time or just irritate people into churn. The Nag Score - outlined in detail here - is an attempt to quantify this.
2. NCT: Crack open your tech dictionaries, I have a new acronym to lob your way. OKRs are old school. Ravi Mehta's NCT (Narrative, Commitments, Tasks) model simplifies goal setting. So instead of vague objectives, start with a clear Narrative explaining the "why" behind each goal. Next, set 3-5 measurable commitments for the quarter, with Tasks as actionable steps. The difference is that OKRs can be overly ambitious, but NCTs focus on achievable milestones that align closely with strategic priorities, more Agile in a way, as course corrections are easier (and it increases team accountability). 3. AI: Polytheistic AI certainly is a phrase to wrap your heads around. It means multiple powerful models coexisting and not one AGI "god.". As part of a top 10 list of thoughts on AI, the article calls today's AI "amplified intelligence," excelling in the middle of tasks while humans still handle prompts and verification. 4. MOATS: Euclid VC digs into why tech moats are harder to build (and keep) than ever. Market speed, AI, open source, and fast-followers erode advantages quickly, meaning execution speed and distribution now trump IP in defensibility. 5. MARKET: Shopify, Datadog, and Palantir are all re-accelerating, showing that in B2B SaaS, the best can still crush it despite the macro gloom. For top players like these guys, growth (and multiples) are back. 6. AI: In AI, marginal costs trend toward zero—so this article points out that if this is true, then pricing should shift from scarcity to abundance. Think access-based, outcome-based, or ecosystem-driven models, not per-seat limits. 7. SHIP IT: AI teams these days are often told to "just ship it," but as us oldies know, rushing shit leads to underbaked products. Leah Tharin breaks down why speed still needs guardrails—especially when trust, safety, and market fit are on the line. 8. MARKETS: Silicon Valley Banks H2 2025 report shows Series A ARR medians nearly doubled to $3M since 2021 (crazy right?), with the lower quartile growing fastest. Translation: "Meh" traction will probably no longer get funded; fewer rounds is a higher bar. 9. PRICING: I make the joke/tech-ism that "pricing is like software - it's never done", too often. But it's true, dammit! So check this great 6-Step Guide to Pricing (With Case Studies), which is good and agrees with my tech-ism about how hard it is. 10. CASE STUDY: Shopify's AI mandate is now "operational law" — no resource or headcount is approved unless a team can prove AI couldn't do the job. AI fluency is in every performance review. An internal LLM proxy + MCP infrastructure makes AI instantly available to the entire company. This is culture remade in some weird AI way. POD OF THE WEEK: How ChatGPT accidentally became the fastest-growing product in history. 1. SaaS METRIC OF THE WEEK: Headcount. Headcount accounts for 60-80% of early-stage burn, which means most burn starts with hiring. So check out this headcount planning module to track every hire and salary
2. SALES TRANSITION: On the mission of moving from founder-led to AE-led sales? This article from Bain Capital Ventures makes the case that it's all about the "MVP/ICP Handshake." Nailing the alignment between your Minimum Viable Product and your Ideal Customer Profile is a key step. Without this, bringing in AEs too early can stunt growth (which has been seen time and time again in startup land). Solidify the customer segmentations and product-market fit before even thinking of adding a sales force. 3. VIBE CODING: Those "Vibe coding" tools like Replit, Lovable, and Cursor blend code, creativity, and collaboration. The TAM? Jason Lemkin takes a look, and it's likely much bigger than it looks once you count non-devs building with AI. 4. AI MARKETS: According to Elad Gil, core AI markets like Code, Legal, and Customer Support now have clear leaders. But sectors like Compliance, Security, and Sales are still wide open—and ripe for disruption. A great map of where AI is and where it's going. 5. FULL BREADTH: You heard of full-stack devs - so how about Full breadth? A new one for your tech dictionaries. These are engineers who go beyond deep tech skills, adding product sense, design taste, and business insight, making them deadly effective in those early-stage teams. 6. AI INFRASTRUCTURE: A post on the new AI Data Centers I posted earlier this month was a popular one, so it's obvious that AI infra's second act is here—moving from just GPUs to the 3 E's: environments (realistic testing), evals (robust benchmarks), and experience (seamless dev tools). The next wave is about trust, usability, and real-world performance. 7. AGENTIC AI: Lots of agentic hype at the moment. In this paper, Deloitte outlines why Agentic AI is the (obvious) next leap beyond GenAI; autonomous, reasoning systems executing complex, multistep tasks with minimal oversight (what could go wrong?) Success hinges on process fit, tech readiness, governance, good QA, and upskilling teams for human-AI collaboration 8. VENTURE: According to this new report I've found (The Big Book of Venture Capital), $205B wass raised in H1'25 (up 32% YoY), mega-rounds up, valuations near 2021 highs, and M&A re-surging (driven by AI). But it's not really a comeback, more just a reshuffle favoring top firms, some AI plays, and strategic capital. 9. WINNERS: a16z breaks down why top startups pull ahead, they compound their advantages, build faster loops, and leverage market power. Success isn't just product or timing; it's how to build momentum that's hard to catch. 10. CASE STUDY: Check out how Carta built their own AI agent "Equity Concierge" to automate complex equity tasks for startups. The team focused on high-value workflows, some tight human–AI loops, and fast iteration, which delivered real actual ROI. POD OF THE WEEK: How the heck do you scale an insanely fast growth company like OpenAI's Sales Team? Check how Maggie Hott does it (along with three other Unicorns). 1. SaaS METRIC OF THE WEEK: EBITDA - the acronym's been called "Earnings Before I Trick Dumb Accountants." EBITDA strips out non-operating noise—but misuse is rampant. MostlyMetrics charts its messy history and relevance in SaaS.
2. INVESTORS: Check out this Ultimate Investors List of Lists from The VC Corner. This list includes everything from venture capital firms to family offices, active angel investors, Corporate Venture Arms, and accelerators. Bookmark now! 3. DISCOUNT: Discounting can juice growth but wreak havoc on your metrics. Both ChartMogul and SaaStr warn: reflect actual revenue in MRR, not list price. Misreporting MRR distorts GTM signals and investor trust. But you can also increase prices so salespeople can "discount". 4. RAISE: A whopper guide (149 pages) that provides actionable insights for navigating the complexities of raising capital, covering investor relations, pitching essentials, market awareness, and the fundraising process. 5. AI-JOBS: Microsoft Research measured real Copilot usage across 200K+ chats to create an "AI applicability score" for occupations. Knowledge work—writing, data analysis, sales, admin—ranks highest. Time to retrain as a Bridge and Lock Tender if you haven't started down that path yet. 6. AI REPORT: ICONIQ's State of AI 2025 shows AI is graduating from hype into real P&L impact. On average, companies now allocate 10–20% of their R&D spend to AI. (As mentioned last month, early-stage startups allocate 20–50% of their R&D budget to AI.) However, only ~50% of employees actively use internal tools, despite 70% having access. Power users deploy 7+ AI use cases and report 15–30% productivity gains, while AI-native GTMs drive 56% trial‑to‑paid conversion (vs 32% for traditional SaaS). But stickiness? I think that is too early to say - but there is such a thing as AI Tourism. 7. TECHNICAL CO-FOUNDERS: Hiring a technical co-founder as a non-technical founder? This guide lays out how to frame the opportunity, where to look, and how to build conviction (and success) on both sides - clear, tactical, no-fluff advice. 8. PRICING: Pricing is like software; it's never done, but it also shouldn't be mainly guesswork. VC Corner's Go-To Pricing Guide breaks down early-stage frameworks for choosing value-based models over your gut-feel. Meanwhile, Mostly Metrics' Evolution of Software Pricing traces six pricing "eras", from seats to usage to outcome‑based pricing. 9. IPOs: Almost 3 years ago, I reported on the acquisition of Figma by Adobe; 15 months later, I noted that the deal had fizzled. Well, Figma IPOd last week and it's the biggest VC-backed tech debut in yeeeeeaars. Does this signal life returning to the tech IPO market? Liquidity's certainly back on the table, and founders, funds, and bankers are watching very closely. If the pipeline really is opening. Who's next? 10. CASE STUDY: Adding onto number 9, Pre Adobe debacle and IPO, FIGMA famously wandered around in the wilderness in the early days until they found Product Market Fit. First Round Capital has broken its growth down (from stealth to enterprise) into 5 phases, and this article dives deep into Figma's Early Days and how patience & discipline fostered a killer product and PLG motion. POD OF THE WEEK: Following up on numbers 5 and 6 is AI's real impact on sales with SaaStr's CEO and Co-Founder, and SVP & GM. 1. SaaS METRIC OF THE WEEK: CLTV vs CAC: An essential SaaS ratio. This post breaks down the Customer Lifetime Value to CAC ratio: why 3:1 is the rule of thumb, when to ignore it, and what your ratio says about growth vs. efficiency - a classic metric read for everyone.
2. LAW-ISMS: From CBInsights is a 67-page report covering the 11 laws driving success in tech. These law-isms cover concepts such as Amazon's 2-pizza rule, the 80/20 principle, and more. 3. DE-SKILLING: A must-read research paper on how AI tools are flattening skill hierarchies in the knowledge economy. From law to marketing, it's not just junior jobs or the big-4 at risk — it's entire workflows. Is "Judgment-as-a-Service" the new job title? 4. AI CAPEX: Companies are increasing AI-related capex, especially in infrastructure, signaling long-term commitments. This surge is also sector-agnostic and showing up in [laces like healthcare, manufacturing, and finance. This capex is from a few companies (think Nvidia-fueled data centers), which is inflating industrial investment metrics and masking broader economic softness. This article argues we're mistaking this AI boom for general economic health—when really, it's a narrow, GPU-fueled anomaly. I also did some math - the new Meta Data Center is rocking in at about 5GW of power needed (and check it overlayed over Manhattan for size), OpenAI's behemoth is planned for 10GW. That's larger than many mid-sized nations. New Zealand, for example, clocks in at about 4.5 GW. 5. TAM: Total Addressable Market slides are not realistic, according to the Clouded Judgement blog this week. The comparison here is that early AI markets are being misjudged, just like early cloud; static TAM maths misses dynamic shifts and new market creation. Cursor and Claude Code are great examples: starting small, unlocking new users and workflows, and turning wedges into reinvention. 6. VENTURE: The CB Insights Q2'25 Venture Report is out: $94.6B invested this quarter, which is the third straight >$90B quarter. But deal count hits a 9-year low. AI dominated 50%+ of all funding, but defense tech and hard tech are surging. Nuclear, quantum, and stablecoins are also heating up. 7. CAP TABLE: I don't have the paid version of this newsletter - so no template available - but here is a handy resource for founders: this Series A/B cap table article from VC Corner helps visualize dilution, ownership, and round dynamics. Whether you're raising or just planning ahead, bookmark this to model out your future (paid sub optional). 8. GTM (Modernize time!): Your 2025 GTM playbook probably needs a refresh. From transactional sales to consultative, from outbound to dark social, and from tools to ecosystems - this post outlines nine key GTM shifts shaping how SaaS is sold today. 9. DELEGATE: One of the biggest bottlenecks in startup land IMO is often founders. Those who can't master delegation become their own bottlenecks. This guide breaks down what to keep, what to hand off, and how to do it without losing control, patience, or your goddam mind. (none of this is abdication). 10. CASE STUDY: LOOPS: Top startups don't grow by accident; they figure out how to run growth loops that compound effects. This playbook breaks down tactics from the likes of OpenAI and Pinterest. POD OF THE WEEK: Thinking of launching a second product? Check this podcast from ChartMogul: Going multi-product: what SaaS founders wish they knew before expanding. 1. SaaS METRIC OF THE WEEK: Here is a highly bookmarkable Guide to SaaS Metrics from equals.com that covers all the greatest hits and more (ARPA, LTV:CAC, Burn Multiples, etc).
2. STARTUP PLAYBOOK: Check out the Emerging Startup Playbook that lays out eight key emerging strategies taken from high-growth SaaS leaders. Emphasizing "speed over perfection," it suggests streamlining decision-making and embracing usage-based pricing for sustainable growth. Key takeaways? Optimize product stickiness before scaling sales and pivot based on data to stay competitive. This is a great read for early-stage founders figuring out their growth tactics (well, more like experiments). 3. AI BUDGET: Here is a quick, fun one. How much should you spend on AI? Tomasz Tunguz says early-stage startups are allocating 20–50% of their R&D budget to AI. Nope - not a typo. AI isn't just a feature, it's a core investment now. Just pretty sure you can't claim those R&D costs back in any tax breaks. 4. SOFTWARE 3.0: Stuff is moving so fast these days, it's hard to keep up. This post (taken in inspiration from these slides) makes the case that we've moved beyond Software 2.0 (ML/neural networks) to Software 3.0: AI-native and conducted in your native language, with API-connected agents reasoning over dynamic data. Tools like LangChain and LlamaIndex aren't the future—they're gonna be the foundation. 5. SPEND: Brex has launched something called the Brex Benchmark, and so far, the May 2025 Benchmark is a gem: it's real spend data from millions of anonymized transactions. Despite economic headwinds, ad spend is up — a signal of renewed growth bets. But spend on consultants and real estate is falling. SaaS and infra? Holding steady with Claude being the numero uno AI app. 6. JOBS: AI may be a primary culprit for a bunch of the current economic payoffs. A new CNBC analysis shows AI is playing a much bigger role in job losses than companies admit. The reshaping of work is happening faster than we're told. 7. ACCOUNTING AI: This one is a bit of a mind-bender from Penrose and explores if LLMs can do accounting and how LLMs can transform ledgers into language, enabling a new term "explainable accounting". It's a weird and dense page, but super interesting for any of you finance ops peeps. BTW - Claude is already on it! 8. PERSONAL CO-PILOT: This is def another AI-heavy newsletter—but here's how to build an AI co-pilot for your day-to-day. From task routing and meeting prep to knowledge surfacing and auto-recaps, Lenny's Newsletter shares a stack of tools to make AI actually useful (and sticky.....and on-brand) in your workflow. ChatGPT now has a next-level co-pilot, an agent that can actually perform tasks on your behalf. 9. OUTAGES: We all have them - especially if we host in Public Clouds - for example, last month GCP service control tripped, creating outages across GCP and Google Workspace, triggering Cloudflare issues, which in turn triggered AWS and Azure outages - it was wild. This piece digs into why reliability is so hard at scale—even for top-tier teams. From incident fatigue to architectural tradeoffs, it's a sharp look at how engineering orgs really manage risk (or don't until hindsight). A must-read if you don't know how resilient or redundant your stack is. 10. CASE STUDY: ONBOARDING: AI onboarding isn't just UX—it's growth. This teardown shows how ChatGPT, Claude, and others use template-activation loops to turn cold signups into active users. POD OF THE WEEK: Want to know what Software 3.0 (number 4 above) may look like in real life - this dude has been figuring all this out since only January and presents an extensive (and IMO quite compelling) overview of the new AI-based management paradigm. Makes me feel really far behind. 1. SaaS METRIC OF THE WEEK: CHURN: We never like to call it, but when should churn be recognized? ChartMogul walks through 4 churn recognition models and why choosing the right one matters for your SaaS metrics, Ops, and board reporting.
2. TERM SHEETS: Bookmark this for future reference. This Term Sheets guide explains the most important clauses—like valuation, liquidation preferences, and anti-dilution protections - and it also offers some strategies for negotiating more founder-favorable terms. 3. AI 1: Every year, Benedict Evans goes on an absolute blinder in PowerPoint exploring macro and strategic trends in the tech industry, and this year's version is just an updated version of his last from late last year (both titled 'AI eats the world'). 4. AI 2: This is also a Ben Evans part 2 as he dives into the messy reality of measuring generative AI. Are metrics like tokens, MAUs, or revenue actually useful objectively? Turns out maybe not. As AI tools blur the lines between product and infrastructure, he suggests we need new ways to define what "success" is. Tomasz Tunguz also asks a similar Question on token I/O. 5. COMPETITION: Being asked to talk about your competitors? This post breaks down the dos and don'ts of competitive framing—how to show you're different without sounding insecure, clueless, or an asshole. 6. SPEND: According to Bessemer Venture Partners, here are the benchmarks for B2B SaaS to measure your payback against (full report here). Across all companies, Engineering is consistently the largest department, Customer Success and Product at about 10% and Marketing at only 7%. This slide also has median headcount by stage, which is a great metric to track. 7. CUSTOMER SUCCESS 1: Great SaaS-CSM-isms from Jason Lemkin: 1. Each Customer Success manager should be able to manage 50–100 customers for a $20K ACV product. 2. Hire one customer success manager for every $2m in ARR. But it's a relative rule and varies with deal sizes, and you can forget the $2m/CSM rule at the earlier stages of growth. But start segmenting & investing early: For big deals ($50k+ ARR), hire a CSM per 2 customers. For mid deals ($5k+), proactive outreach is possible with 400 customers. Just automate! 8. CUSTOMER SUCCESS 2: Follow-up question: Where should Customer Success Sit on your balance sheet? This article from Mostly Metrics looks to answer if CS teams should report to Sales, Product, or operate independently. The answer? It depends. So read through, and you may need to take a more flexible approach. 9. SALES AND MARKETING: ChartMogul delivers a great 101 for startups on when (and how) to scale sales and marketing (as a pair). If you're early-stage and wondering how to figure all this out and CAC traps, this is a pretty good playbook. 10. CASE STUDY: Checkout PagerDuty's IPO prep playbook: lock in top talent 18 months out, scale finance ops (especially FP&A), get a grip on churn math, and overhaul comp plans. Bonus: founders were still hands-on with sales and forecasting. POD OF THE WEEK: This is from David Skok (a legend in the SaaS world) and covers hardcore B2B SaaS metrics such as Rule of 40, Repeatability, Net new ARR, Bookings, LTV:CAC, churn, etc., etc. - it's a metric-packed 20 minutes. 1. SaaS METRIC OF THE WEEK: Not all ARR is created equal - and some is faster! This week's breakdown from The SaaS CFO explains how to separate AI ARR from traditional SaaS ARR, which is vital as more tools incorporate AI features, infrastructure, services, and usage-based models.
2. VENTURE-STRAPPED: This is a Top10inTech-ism's for your tech dictionaries for a hybrid startup that is a mash-up of the old debate of bootstrapped vs VC financing and applies to startups who raise only once. Which, anecdotally, seems like a more common practice in these new market conditions (and includes Klaviyo and Zapier). Jason Lemkin notes this new one-and-done third way. 3. UNDERSELL STRATEGY: If expansion fits into your growth strategy (it should) take a read of two-part series from Tomasz Tunguz and Bill Binch - part one is deliberately underselling as a sales strategy to minimize churn and increase upsell/expansion opportunities as a land and expand strategy and post 2 is an expansion of land and expand witch details how to structure a Startup sales team for optimal land & expand. 4. GROWTH: a16z's AI revenue benchmarks are bonkers: the median enterprise AI startup hits $2.1M ARR by month 12. That's not the outlier—that's the middle. Consumer apps? Also wild: top quartile = $1.3M ARR in 12 months. 5. EU AI ACT: The EU's AI Act is now real policy, and compliance isn't optional - talking to you, Gemini, ChatGPT, Claude, et al. Vanta's new EU AI checklist breaks down what companies (especially those selling into Europe) need to do to stay above board. 6. VENTURE 1: Check the Pitchbook Global VC First Look (yup - it's an Excel "book" ): VC is still in a liquidity nowhere land. IPOs remain scarce (for now), exits are rare. But AI? It's pulling in 'poke-me-in-the-eye-please' valuations and dragging the market back to some 2021 energy levels. Not sure if that means a bubble or bounce-back, this all needs to play out - AI is also gobbling up more than a third of venture debt. 7. VENTURE 2: First impressions matter. This tactical guide walks you through how to nail your first VC call—what to say, what not to say, and how to leave them wanting more. 8. PRICING: Pricing your SaaS too low won't make you a product-led success (but it'll make you broke). This guide breaks down early-stage pricing strategies that can actually work, from value-based to tiered. 9. GO-TO-MARKET: This is my kind of report! From Chartmogul comes their SaaS Go-To-Market Report, examining how SaaS companies acquire and convert customers. CAC payback is now 19 months, and inbound is king—75% of sales-led SaaS companies still rely on it. 10. CASE STUDY: PRODUCT MARKET FIT: A big Startup-ism - More than 50% of the time, the lack of Product-Market Fit (PMF) factors into the reason a startup fails (keep reading this article, though, as it goes through how StartupOS figured their PMF out). AirTree (an early-stage VC) has just published this article, taking a look at what metrics VCs like them look at for signs of Product-Market Fit - and also what the red flags are. Also, this article has some great PMF definitions. PMF was called "the only thing that matters" to early-stage startups by Marc Andreessen 12 years ago. Now his team gets a little more nuanced, suggesting to focus on Product-User-Fit as an indicator towards achieving PMF. A similar nuance is also true post-PMF, with repeatable and scalable revenue models as a precursor to a repeatable and scalable business model (you know - the one with actual profits). POD OF THE WEEK: Reed Hastings, ex-Netflix CEO, breaks down how to scale trust, talent, and bold bets - without turning your company into the Hunger Games. No PIPs, no micromanagement—just clear values, adult treatment, and $100M risks.
1. SaaS METRIC OF THE WEEK: BURN MULTIPLES. In this neo-capital-efficient SaaS market, operators are expected to find the balance between growth and efficiency. So it's time to brush up on those efficiency metrics in this 2 part post covering Burn Multiple and Sales Efficiency metrics (see post 2). A Burn Multiple measures how much a startup is burning to generate each incremental dollar of ARR. The higher the Burn Multiple, the more the startup is burning to achieve each unit of growth. Here is how to calculate this metric, and here is an example.
2. GROWTH: I love this article from First Round Capital. Mainly as it justifies my sentiment around rigor, data, and insight. To quote: "Growth is about implementing a rigorous, customer insight and data-driven process with sustained effort to remove friction." 3. SPEED MATTERS: I write this newsletter during downtime, such as "Coffee Spints ."I prioritize speed and finding quality content over spelling, editorial tightness, and grammar. (My bad!) James Somers feels the same. As does Google, they obviously also made speed a priority for their tech stack, and speed is UX moat for tech companies. Netflix is another great speed-focused tech company that (amazingly to me) de-prioritized uptime in favor of speed and also became their own CDN as part of their speedy experience solution. 4. REVERSE TRIALS: Reverse Trials are a play on freemium, where new users start with a time-limited trial of all your paid features. At the end of the trial, they can either buy or downgrade to a fully free tier. This article also explains how Airtable does this well. The benefit here is that, emotionally, users experience loss aversion, where the pain of losing something is twice as powerful a motivator as the pleasure of gaining. 5. METRICS: SaaS Capital's latest 2025 report is out. Median ARR growth across all private B2B SaaS companies? 22.4%. Growth drops fast with size: under $1M, ARR companies grow ~66%, $20M–$50M grow at just 16%. Tuck this one away for board decks and sanity checks. 6. AI-FIRST: a16z outlines what an "AI-first" company really looks like. Key traits: systems built for agents from day one, constant fine-tuning, and orgs designed around feedback loops—not functions. If AI feels bolted on, this is a good blueprint reference point. 7. MARKETING: Great question - Does every marketing channel suck right now? According to MKT1… kinda. Acquisition is way harder, and it looks like the best teams aren't just optimizing channels—they're building long-term growth engines. Strong POVs on attribution, sequencing, and content that converts. 8. LEAN: Notion VC's new data shows that startups are getting radically leaner; it's a whole new LEAN startup paradigm from the old Lean Canvas one. Median team sizes are down from 25 to 14. AI is the driving force behind this shift. The best Cloud Challengers are AI-native, founder-led, and operationally tight. They embed AI across workflows, automate decision-making, and scale without bulk. 9. EVALUATION: This VC Corner guide breaks down startup exit strategies—acquisitions, IPOs, secondaries—and when to consider each. 10. CASE STUDY: What should your marketing team look like? MKT1 breaks down how org charts shift by stage, with templates from Seed to Series D. Real-world examples, trade-offs, and when to hire what. |
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