The weekly top 10 for B2B tech operators · Every Friday
Burn multiple measures the capital efficiency of a startup. Burn multiple calculated by net burn/net new ARR. In a surprise to no one (because Burn is now a terrible word in this new market), Startup burn multiples have changed markedly in 2023.
Here is the ultimate deep-dive into PLG from Kyle Poyar of OpenView, one of the OGs of the PLG world. It contains tactical advice, real-life examples, and actionable next steps.
Every year, Benedict Evans goes on an absolute blinder in PowerPoint, exploring macro and strategic trends in the tech industry. He's back with this year's version noting that (across his 104 slide deck!) big-tech is becoming bigger-tech and the ultimate gatekeepers of the tech economy.
Modern-day businesses create Technical Debt via Product Debt. Stop taking shortcuts, as it's all the decisions that have been made, often tactical and acute, without a clear product vision or sufficient consideration about the long-term effects of that moment/decision. The link above also has a great case study of Google Messaging's product evolution, but this link also has a great PM-focused article on how to design out of it (or at least your backlogs).
I have been delivering this newsletter weekly since December 2018, holy smokes - I even took significant breaks that no one noticed! So this article resonated this week on why being consistent matters - outside of his monetization, podcasts, etc. :-).
Here is an excellentdashboard of the top open source projects by growth, retention, and usage. It can be visually confusing, so read the Substack article outlining the dashboard in more detail here.
APIs allow different programs and services to get along and work together, which is why they're essential in today's crowded technology space. For your continuing education credits: A Full Guide: Understand Everything About APIs (with Examples).
Stanford released a massive 386-page report on the state of AI, showing how heated the market has been getting for years - Newly funded AI startups have tripled in the last ten years, primarily in the US - and also showing how the past three years have been incredibly rapid paced across many measures (including AI-related lawsuits).
Optimizing Pricing is complicated, and it's never (ever) perfect. a) If companies decide to have a pricing page on their site (which is that whole other topic. Jason Lemkin lays out some thoughts of what makes a good pricing page. b) McKinsey gets technical, outlining how toleverage big data to make better pricing decisions. c) Want to look at competitor prices? Comptera has a great article on conducting a high-fidelity competitive pricing analysis project, and d) Productled has the ultimate "How to build the right SaaS pricing page" in 2023.
Down rounds are pretty standard this year (and probably next) - so what can we learn from Down Rounds of the past? Here is an excellent report about Docker which went through a down round and a 75% headcount reduction
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