Top 10 in Tech - What to know for Week ending October 3, 2025

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.