|
|
Curated SaaS and tech insight from around the web repackaged for people to put to good use
|
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. 1. SaaS METRIC OF THE WEEK: Is ARR dead? Not quite — but it is evolving. In a world of usage-based pricing and variable billing, Notable argues ARR is no longer a reliable compass. It's being replaced by CARR, NDR, and cohort-based views.
2. BENCHMARKS: Fresh from the 2025 BenchmarkIT Report (interactive version available here), median growth has dipped to 26% (down from 30% last year), while the top quartile remains at 50%. NRR down to 101%. New CAC is up 14%, but expansion ARR is now 40% of new ARR (50%+ for $50M+ companies). ARR per FTE? $300K at scale. 3. AI: Is AI adoption already hitting a wall? Ramp's latest data suggests AI usage may be plateauing across expense categories, especially in SaaS and infra. The AI hype cycle may be cooling, at least in B2B wallets. Jason Lemkim breaks down why this slowdown may be real (and why it may be an illusion). 4. TRENDS: Every year since 2004, Mary Meeker (a top-ranked VC) has been releasing an incredibly in-depth analysis of Internet Trends. She is back this year with another monster report - 336 slides long with, of course, a heavy focus on AI. Highlights: On the infrastructure side, the big six tech providers are spending $212B/year, and Enterprise AI revenue is insane (e.g., Cursor grew from $1M to $300M ARR in 2 years). 5. AI GROWTH: Adding onto number 4 above is this insane headline/takeaway from a16z data: The median enterprise AI startup now hits $2.1M ARR by Month 12! MEDIAN! Holy smokes, AI-native products are ramping faster than SaaS ever did. I need to try and muster up some AI revenue benchmarks. 6. EQUITY: Not all startup equity is equal, so I highly recommend any founder read this three-part deep dive into the equity terms that matter. 'Dilution' is one of the most feared words- so let's benchmark it - what is the average ownership percentage by SaaS Founders at time of IPO? Sammy Abdullah takes a review, and the median level of founders' ownership is 14%, while the average is 23%, with VCs owning about 54% on average. Obviously, there is a significant difference between bootstrapped and non-bootstrapped data in this dataset. As an added bonus, take a read of this article from Heavybit that discusses Cap Table management in relation to growth and also how to manage that Option Pool. 7. M&A: According to Pitchbook, Enterprise SaaS M&A activity held steady in Q1 2025 with 210 deals, matching Q4 2024, but deal value fell nearly 25% QoQ to $29.1B. VC-backed targets stood out, hitting $14.6B in value—50% of the total. Top segments? ERP ($12.9B) and AP (up 108% YoY). 8. EARLY-STAGE: Is early-stage investing busted? Chris Neumann digs into the shift: more founders, fewer quality startups, and inflated expectations. The bar is higher, and investors are wary — with fewer seed deals closing and many angel syndicates pretty much on pause. Tomasz Tunguz also tracks five years of YC trends: batch sizes are down 54%, crypto is out, and AI dominates. The average valuation has doubled, but startups now raise less per dollar of valuation. It's leaner, more competitive, and very AI-heavy. 9. VALUATIONS: How do investors really value startups? There is a bunch in here for your tech dictionaries, as this breakdown covers eight methods from VC math to the Berkus Method and Scorecard Valuation (). Essential reading for any founder or operator raising capital (or negotiating their next round). 10. CASE STUDY: Founders Fund's $50M Fund I (back in 2005) backed 17 startups—7 hit unicorn status. This retrospective dives into their contrarian bets (SpaceX, Palantir - also a Thiel Biz), the PayPal Mafia, early LP skepticism, and why conviction > consensus. Rare transparency on VC returns and bunch of misses too. POD OF THE WEEK: Stijn Hendrikse has unearthed a bunch of patterns that separate companies achieving explosive growth from those that plateau at $5-10M ARR. 1. SaaS METRIC OF THE WEEK: Here is a new one - The Customer Success Ratio. Calculate this as CSM expense ÷ Net New ARR from Existing Customers. Track it to see if your post-sale team drives growth or burns margin. Rule of thumb: keep it <10%.
2. AI: Bond Capital's monster 340-slide AI report is a goldmine: ChatGPT scaled 20x faster than the internet (p. 20), 73% say AI sounds human (p. 26), inference costs down 99% (p. 40), agent apps surging (p. 93), revenue scaling fast (p. 102), 70% of GenAI users seeing productivity gains (p. 109). 3. UNICORN: The 30-year unicorn backlog may finally be moving (this is referencing the 700+ unicorns stuck in private markets). Q2 saw 20 unicorn exits (vs. six last year), led by AI, cyber & health. Wiz's $32B buyout, CoreWeave IPO & more signal some kinda thaw—but with 700+ unicorns still waiting, this logjam may take some time. 4. VENTURE: VCs seem to be funding two things: AI & SaaS—but in very different ways. AI receives massive rounds, but even pre-revenue SaaS companies must show traction and efficiency. AI = 'fund the vision,' SaaS = 'fund metrics.' Same VCs, two mindsets. 5. GROWTH: Unlike the focus of #3 above, mostlymetrics breaks down why 10-15% annual SaaS growth is just fine for many. Not every startup is a rocket ship—and that's OK. Realistic growth expectations & compounding wins > unicorn-chasing. 6. PRODUCTIVITY: I've been having lots of productivity talks over the past few weeks, and this is a great article that validates a lot of the discussions (and, tbh, gave me a few hard truths to act on). It's targeted at engineers, but the 15 productivity hacks here apply to any knowledge worker IMO. High-signal, no fluff. 7. MARKETING: Here is a GitHub treasure trove: Marketing for Founders. Crowdsourced, no-nonsense advice across positioning, pricing, SEO & more. A really practical resource worth bookmarking for revisits. 8. PRICING: Check out this go-to pricing guide for early-stage founders. It covers freemium, premium, usage-based, and hybrid models—plus when (and how) to charge more. 9. MOATS (AI): Clouded Judgement dives into what modern SaaS moats in the modern AI world look like: Speed isn't just important; it is the moat. As well as scale, network effects, brand, and distribution. But because AI compresses product moats, this all matters more than ever. (also read the rest of that post - tons of nuggets always in there - benchmarks on multiples, revenues, gross margin, etc., etc.) 10. CASE STUDY: Perplexity AI is scaling fast! Check this deep dive on its acquisition and retention machine. Sixty percent of traffic is direct, mobile usage is exploding, and SEO and product-led virality do the heavy lifting. POD OF THE WEEK: Adding on to number 9 above on speed as a Moat - Sam Parr and Shaan Puri talk to Jason Lemkin about cloning yourself with AI and how ChatGPT will be the end of incumbent apps. 1. SaaS METRIC OF THE WEEK: ARR - Here is a whole book for you covering ARR. It covers everything you need to know to define, build, and report on ARR from scratch based on experiences at Intercom, Atlassian, and Stripe. I also have Bessemer Ventures claiming to have a founder's roadmap to $100 million ARR.
2. OUTBOUND vs INBOUND: How you handle an inbound lead vs an outbound lead is quite different. Check this article from Jack Jorgovan on how Outbound leads differ (and how to close them). The team at Predictive Revenue has been running over 50 outbound sales experiments to find out what works best (and what doesn't.). Watch the whole series on YouTube. SaaS Weekly also has a guide on automating outbound emails by leveraging intent signals to drive better-targeted campaigns. 3. API: APIs aren't just dev tools—they're products, and pretty much all AI needs them. Zuplo's API guide outlines how to run API product management like a SaaS, covering pricing, usage tiers, onboarding, and churn. If you've got an API, this gives you a roadmap. 4. GROWTH 1/2: Testing new tactics for marketing growth takes a lot of resources, and most of us often don't have much time to run experiments. Check out this Google Doc from Dashly, which collects 100 growth marketing hypotheses tested by their experts. (includes advert retargeting, wait list for product launches, niche glossaries, etc.) 5. GROWTH 2/2: According to Mostly Metrics, companies and deals with ACV in the $50K to $100K deal range are feeling the heat right now as they are caught in the crosshairs of CFOs being tasked with cutting budgets. I'm feeling judged. The data shows that enterprise purchases are stickier due to their complex implementation and high switching costs, while SMB purchases fly under the radar. 6. BENCHMARKS: Check out this benchmark's goldmine with the BenchmarkIT Report (all B2B SaaS), and it's pretty interactive (or snag the PDF here). Median growth for SaaS companies is 30%, and Net Revenue Retention (NRR) is at 105%. Median Customer Acquisition Cost (CAC) payback is 16 MONTHS! and here is one of my favorites - an average of $.69 per $1 of expansion revenue generated. 7. AGENTIC: This article argues that we're entering an agentic web era. This is where AI agents act on our behalf, not just answer questions; they also take action. But the "original sin" of the internet (SEO and ad-based enshitification) could distort this future - dammit. 8. AI SCALE: There's a hidden scaling law for LLMs: performance jumps when trained on multiple languages (original study here) — even if you only test in one. It's a fascinating take on multilingual data as a scale amplifier, not just a translation tool. 9. ADVICE: Here is the motherload of all advice, 99 of the sharpest insights from 99 founders, all in one post. From mindset to mechanics, it's a dense but skimmable wall of gold. There's gotta be at least three things you can copy into your notes. 10. CASE STUDY - MOATS: Complimenting the Pod of the Week (below), CB Insights reports on Moats IRL with 29 examples of enduring moats (from Amazon and Tesla to Starbucks and Coinbase). Key strategies include leveraging network effects, scaling through cost advantages, and capitalizing on brand loyalty. POD OF THE WEEK: Expanding on number 9 and 10 above, here is Jason Lemkin's pod/vid on Top 10 Moats in SaaS. 1. SaaS METRIC OF THE WEEK: AI Metrics: This is a great one from David Kellogg, who recently presented at SaaS Metrics Palooza 2024 on "The Impact of AI on SaaS Metrics" slides in a PDF version here. The event he presented at is actually whacked full of good talks so well worth the (somewhat weird) on-demand replay you can get access to here.
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 quarterly commitments, 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. CONFLICTS: David Kellogg suggests designing our businesses to surface essential conflicts. Instead of reducing conflicts, leaders should identify which ones add value and make sure they are heard. For example, separating Sales and Customer Success encourages transparency around upselling conflicts. By purposefully structuring teams, leaders can maintain productive tensions that drive growth and reduce irrelevant friction. 4. INCIDENT MANAGEMENT: We all have incidents and accidents, and incident reviews are critical to improving system reliability and teams, but many of us fall short of making these sessions productive. According to The Pragmatic Engineer, some of the best practices (which I have adopted and now use) include creating a blameless environment to encourage honest assessments, focusing on learning rather than punishment, and ensuring incident reviews are actionable. The template I reference is from Atlassian - they have a very detailed Incident Management book, aaaand you can generate your own template here. 5. CASH MANAGEMENT: Here is Part 1 of a 3-part Guide to Cash Management for Startups, which highlights bank account strategies at different Stages. The startup phase needs basic checking and savings accounts for operational expenses and emergencies, maintaining liquidity, managing cash flow, and keeping financial controls strict. It prioritizes simplicity and security in banking structures. 6. AI WARS (2025): The big public cloud giants are doubling down on AI. AWS, GCP, and Azure are now well in bed with leading LLMs (all three have invested in Anthropic) while also building rival foundation models and AI accelerators. This CB Insights report maps out the battlefronts: infrastructure, partnerships, custom silicon, and AI sec. Looks to be about $250B+ of capex on the table, and OpenAI's $500B Stargate ambitions, plus the crazy io news, are a looming threat. 7. DEVS: a16z outlines nine developer trends shaping up the AI era - from AI agents and LLM-native IDEs to "Bring Your Own Model" platforms. AI integrations with codebases are absolutely reshaping workflows and platform choices alike. And, of course, the smart money is watching these shifts closely. 8. BIZ DEV: Read this before your next "strategic" partnership. Business development does not necessarily equal sales. Jason Cohen breaks down startup biz dev into five distinct types, from co-marketing to integrations. And ya know, most BD flops come from mismatched expectations. 9. EQUITY: Founder equity convos are hard - especially when your co-founder is also your friend, but it ain't equal. This breakdown offers a calm, thoughtful approach to handling founder splits without ruining the relationship. 10. CASE STUDY: Palantir's moat isn't just tech—it's time. This teardown argues Palantir's edge lies in deeply embedded systems, long cycles, and government-grade entrenchment. A strong example of sticky enterprise sales done right. POD OF THE WEEK: Great growth and marketing lessons from the early days at OpenAI and Stripe on building differentiated strategies that can actually work. 1. SaaS METRIC OF THE WEEK: DAU/MAU. The DAU/MAU ratio is a popular metric for companies that need to measure user engagement. Rule of thumb: Average is 13%; apps with over 20% = good. If you have 50%+ - you're world-class.
2. CASH MANAGEMENT: Part 1 of a 3-part Guide to Cash Management for Startups highlights bank account strategies at different Stages. The startup phase needs basic checking and savings accounts for operational expenses and emergencies, maintaining liquidity, managing cash flow, and keeping financial controls strict. It prioritizes simplicity and security in banking structures. 3. CAPITAL EFFICIENCY: Capital Efficiency has been back in Vogue for a while, and 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, with 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. 4. SECONDARIES: Secondaries (selling private startup shares before exit) were quite recently seen as pretty taboo, but now they are becoming critical for seed funds managing longer timelines and shifting LP expectations. Hunter Walk's post nails the why. 5. BUYERS vs USERS: The person writing you a check is not necessarily the same person getting value from your business. So, take a read of this insightful article from HeavyBit on differentiating messaging based on this premise and the different profiles. 6. VENTURE: The Q1 2025 PitchBook NVCA report is out, and the overall VC mood looks complicated. On paper, the $91.5B in deals (thanks to a few giants like OpenAI) masks weak liquidity, stalled IPOs, and just $10B in new fundraising. Tariffs and uncertainty have investors sitting tight, and early-stage deals remain depressed. 7. LEAN STARTUP: Provocative blog post - but maybe not wrong. The Lean Startup world is gone? AI now writes most of the code—so the bottleneck is no longer dev; it's user attention. Time to rethink how we build. 8. FOUNDER OWNERSHIP: Carta's Spring 2025 SaaS report confirms the dilution game: VC money comes at a steep equity cost. Each round chips away—pre-seed, employees, co-founders, SAFEs, and traditional VCs. By IPO, founders often hold much less than they think. Dilution isn't a bug; it's the whole game. 9. QUANTUM: Late last year, I noted that Google had a new quantum chip, Willow, which marked a bonkers leap in compute power (completing a computation in under five minutes that would have taken the world's fastest supercomputer 10 septillion years - older than the known universe). Quantum cracking isn't hypothetical sci-fi anymore - it's an inevitability. 10. CASE STUDY: Crunchbase crunched the Venture numbers over the past 10 years, and global VC has nearly tripled in a decade ($158B in 2014 to $433B in 2021's peak), then cooling to $285B in 2023. Deal count? Doubled. The US leads as always, but China has pulled back. This is a data-rich look at a wild decade in VC. POD OF THE WEEK: Investor Elad Gil (Airbnb, Stripe, Coinbase) shares his playbook: Insights on why the market matters more than the founder, why AI may be under-hyped, and why he thinks remote work hurts innovation. 1. SaaS METRIC OF THE WEEK: What KPIs do venture firms consistently care about across stages? This article highlights how KPIs evolve from early traction metrics like CAC and LTV to more advanced indicators like NRR as companies scale and also shifting into survival metrics like cash runway to operational efficiencies.
2. CAPITAL (seed): AngelList data shows that, on average, seed-stage companies have about 18 months to secure a Series A. Because if a startup isn't marked up by then, it's likely to stall. 3. REVERSE TRIALS: Reverse Trials are a play on freemium, where new users start with a time-limited trial of all your paid features, and at the end of the trial, they can either buy or downgrade to a fully free tier - this article also explains how Airtable do this well. The benefit here is that, emotionally, users experience loss aversion, where the pain of losing something is twice as powerful of a motivator as the pleasure of gaining. 4. AI EVALUATIONS: Oh - this one is good. Every AI startup sounds like a rocket ship - but we all know about the good ol' Startup Jazz Hands - all sizzle and no sausage. Well, check this framework, which helps cut through the pitch BS—what matters, what's sizzle-y fluff, and how to build (or back) something real (or at least really AI). 5. AGI: Speaking of Jazz Hands - Is AGI (Artificial General Intelligence) real or just Silicon Valley cosplay with a massive budget? Check this takedown of the "AGI startup" wave, which calls out the hype, the grift, and what real researchers actually think. 6. VENTURE PITCH: Wanna know what's really happening behind the scenes in a VC pitch? Avery Law breaks down the VC decision-making process: partner politics and legal diligence bottlenecks. Founders: it's ain't just about your pitch. Timing, biases, and internal champions all matter too. 7. PLG: Upgrade paths are a well-known strategy, especially in the PLG world, for increasing revenue, especially LTV/ACV, but not all users upgrade in the same way. Check out this breakdown of SaaS upgrade paths—feature-, seat-, and usage-based. It's a smart take with practical diagrams (and I love me some good pictures). 8. TESTING: We got customers on the A/B test path this week, and y'all don't actually test enough (or at least test well) - me included. Check out this guide, which lays out a full-stack testing strategy, from messaging to monetization, and shows why velocity, not perfection, is your friend and compounds the wins. 9. GENAI: Google Cloud's new 2025 AI Infrastructure report confirms what we know to be obvious: GenAI is now mainstream. 98% of orgs are developing or using it in production. It's not hype, it's now core infra. But cost, data quality, and hybrid deployments are critical to success. Plus, those IT Consultancy companies are the biggest adopters in Prod. 10. CASE STUDY: How many hours should founders work? Check out this analysis of YCombinator Founders. It's a 3-part series, but a good TL;DR is that pre-product-market fit founders work the most hours, with time spent decreasing as companies grow and gain traction. For many of us, it's a good read for a) Validation and b) Tips on managing your time and not burning out. POD OF THE WEEK: Total Bang for the buck podcast - 11 essential SaaS metrics explained in 11 minutes. |
Archives
October 2024
|