The weekly top 10 for B2B tech operators · Every Friday
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$141,125 of ARR per employee is the 2026 median for private SaaS, which is up from $129,724 last year. Revenue per head climbs with company size at every step, and the whole curve shifted up a rung this year. Go find your row in the report.
The median public SaaS company trades at 4.2x NTM revenue. The top five trade at 36.4x. Clouded Judgment/Jamin Ball's latest markets review shows the gap between the two is wider than at any point since the 2021 peak, and the median is still below the 7.8x pre-Covid average. If your growth rate sits on the low side, that's a discount a buyer is gonna start from.
Stripe just launched a great new data source for us all - the Stripe SaaS Index. Markets wiped close to $1T off SaaS in February; revenue didn't notice, though - up 21% since January (vs 14% for H2 2025). Year-on-year growth is now above 30%. SaaSpocalypse was all hype. Another interesting tidbit in there - in January, mature SaaS businesses were five points more likely than sub-one-year ones to be using AI tooling. By April that had flipped, and young firms now lead by four.
Apparently code changes at Meta have risen 220% year on year and features users could actually see rose 36%. That's Project overtime - replace thousands of staff with AI agents, cut some teams by up to 60% - per Reuters' investigation. Incidents climbed 40% and firefighting time 70%. AI made the engineers faster. The organization, well, yeah - not so much. Same is true for Apps at large - the supply of apps has surged like crazy......but no one is really using them.
The article above at #4 is the teachable moment - but time to be honest with yourself - do you still read the code? Not skim the diff - read it. The test - You can't justify an implementation choice without a long think, and eventually the only way to find out what you built is to ask the model - with no way to check the answer. That's not a middle path. That's vibecoding by accident - looking at you Meta!
Check out these 4 GTM playbooks that pair the data only you hold - champions, closed-lost deals, website visitors, product usage - with the bought signals that tell you when to act. Each playbook has the full workflow, step by step.
Your AI agents are like a bunch of new grads: smart, tireless, and useless on day one. This article argues more context won't fix that.......but a scorebook will - what the agent decided, how your expert graded it, what actually happened. Run it across every customer and that expertise compounds. But hey, even Anthropic runs its own GTM on Salesforce, Gong, and Clay.
Statistically, your staff engagement has never been lower, but productivity is getting higher. And AI is the reason those two numbers no longer move together - reports get written, and the ticket still closes. None of that depends on somebody wanting to do it (or caring) - want some anecdotal evidence. Take a look at this Reddit thread for some real-world apathy.
Bit of a staff-based theme this week and a new term for us all - Entry-level roles in AI-exposed jobs are now seven times more likely to demand skills that used to take a decade to earn. PwC calls it seniorization. Everyone wants to hire for judgment - but where does it come from now that the junior jobs that used to produce all that experience are being cut?
A year ago agents created 3% of the work in Linear. Now it's 50%, installed in 95% of paid workspaces, and NRR held at 177% through this change. Crazy amount of cash at hand.
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GROWTH -: Median growth for private B2B SaaS is 22%, down from 25% last year. SaaS Capital's 15th annual survey (across 1,000+ companies). Only 7.3% reported flat or negative growth, though - the market slowed, but it didn't stall. Equity-backed medians held at 25% while bootstrapped slipped to 20%.
Daniel Dines gave his CEO job up at UiPath to some hired exec. Four months later (after one guidance cut and a 35% stock drop), he took the role back. The founder at Workday just did the same, same over at Intercom - Lemkin calls it The Last Stand - with a pre-AI B2B SaaS company that's big enough to survive, too slow to matter, but nobody but the founder can survive the rebuild needed.
1% of OpenAI and Anthropic's customers generate 80% of their enterprise revenue (and it hasn't moved in three years) - seems like a bit of a risk. The median business spends $11.95 per employee per year on AI. The top 1% spends $7,400. The AI boom has a lot fewer buyers than the earnings calls suggest.
There seems to be a general worry out there that some vibe-coded upstart is coming for your SaaS renewals? SaaS Capital took a good look and says it basically isn't happening - buyers grumble about building it themselves, then pay up like they always did (at least for now). The (more important) real move they're seeing is in reverse: the incumbents are doing the vibe-coding, building that adjacent tool so the client never buys it from anyone else.
Fast and opposing follow-up to #4 above and taking the buyer's side. The "We'll build it ourselves" objection has more than doubled in a year. Before you panic: under $25K, it's a bluff, the win rates don't move. Over $100K, it cuts your win chance 80% - and 60% of those losses aren't losses to a build. A median vendor, according to this post (only 100 anonymized companies), has nearly 10% of lost ACV tied to it.
Would anyone notice if your competitor stole your homepage? It's brutal because you already know the answer. Most hero messages are interchangeable - It's category wallpaper.
Graduating into a severe recession job market typically costs someone about 10% in first-year earnings. But take a look at this data - If you are graduating in 2026 with a degree that is really exposed to AI - it costs 13% - plus a 5-point lower chance of even having a job at all.
Check these 64 creative growth tactics from Tom Orbach (who does this for a living at Wiz). Each of his ideas has been run at least once; most are niche. Heads up: it paywalls just past halfway - but that's 32 things - gotta be at least one for ya!
End of year is around the corner - so this is your annual notice that Annual planning season is open - so start with CJ Gustafson's Annual Planning Bible for 2027. Before you model your dinero, check five things: current headcount, open headcount, this month's P&L, rep attainment history, and 12 months of costs.
ElevenLabs went from $0 to $100M ARR in 20 months, then $600M+ by month 41 - it friggin accelerated as it got bigger. Also - when their AI agents close revenue on an account, the human who owns it still gets the commission. Also, sales quota is 20x base salary (traditional B2B is 5x).
ARR - it ain't the trophy metric it once was - that and other traditional SaaS metric takes from current VCs here.
The AI price war and the AI debt boom are hanging out at the same time. $500B of other people's money, lent against GPUs. That's Nvidia's new plan with Apollo, BlackRock, Blackstone, Brookfield, Goldman, and KKR - announced at the same time token prices fell up to 80% and memory started building toward its next glut.
It's a trap! Check these 5 magical thinking traps that are common for new founders to fall into - Build it, and they'll come; launch it, and they'll buy; add more, and they'll convert; move faster, and my fav - a few early customers means a viable business.
I find the threat of AI-enabled cyberattacks terrifying (and they are inevitable) - the president at OpenAI agrees - he lists 10 things to do ASAP against AI-enabled cyberattacks (remember his own agents hacked Hugging Face, so he'd know - see #10 here). Give your security team an agent today, read-only first, triage the backlog, security review in CI. His phrase is "turbo speed."
A £10M facility quoted at 10% actually costs 14.3% in cash and gives the lender 16.8% once the warrants land. Every point of the gap is disclosed somewhere in the documents - the 2% fee on day one, PIK quietly compounding the balance to £11.3M, a 3% exit fee someone agreed to as a rounding error.
Every private capital strategy is down this year except one. Private debt raised 27.3% more in H1 than last year and is tracking its second-best year ever. $5 trillion is now stuck in private funds seven years or older - 39% of everything. Fundraising dropped to $1.35T while the number of funds fell 37% to 3,763, showing capital is concentrating - 78.2% of capital went to $1B+ funds, which is up from 59.1% in 2021.
Check this report from Papermrak (they tracked 24,541 decks and 358,672 investor views) - Investors give your deck 4 minutes, and fewer than half of them ever reach the last slide - which is where we all put the ask. Put your best facts in the first three slides, ask early, and the appendix goes behind everything. Super helpful report. BTW - TEAM is the most-read page (at 5.7 seconds).
New one for our tech dictionaries - A graph is a loop with something that can contradict it. It's worth it for the phrase "a larger hallucination with better project management" alone. 20 AI agents reviewing each other's work ignores the same blind spots and agrees with itself twenty times.
Founders are killing the CMO position - brand goes into product, demand goes into sales, problem solved. You are better off with no CMO than the wrong CMO. Good idea from the article - hire the person who could run marketing in 18-24 months, and pay a great CMO to advise them for a year. Cheaper than the mis-hire, and the mis-hire builds a team in their image for years.
DETOX: 3 days without your phone and your brain starts showing the same activation patterns researchers see in substance withdrawal. Check this study - Researchers took smartphones off 25 young adults for 72 hours. The participants reported no extra craving and no worse mood - which seems fine, but their brain scans said otherwise.
This is a new acronym for your tech dictionaries - MMM, or Marketing mix modeling, is used to measure the cross-channel impact of all the various marketing and non-marketing drivers on your startup's sales or business efforts and performance. Google's Meridian is its open-source take on it.
I love me some laws and principles - here is a new list of 10 of the lesser known ones. Hanlon's Razor is a goodie: rather than questioning people's intentions, question their competence.
Sarah Guo built Conviction around one bet: the biggest AI opportunities sit above the foundation models, not inside them. Her logic is simple - the labs become infrastructure, while startups win by owning the application, workflow, and customer.
Counterpoint to Sarah Guo above (#3). Akash Bajwa reckons model labs and agent companies are converging the stack, not separating - Anthropic is building products while Harvey is training models. The endgame may be owning the model, the application, the workflow, and the customer around it.
Last week Anthropic/Claude announced that it will now embed an invisible watermark into the text it generates - and it can survive copy-paste and some editing. The weird bit: even using Claude to proofread or translate your own writing can leave the mark. Heavy rewriting can break it, but a third-party detection tool is coming. (not necessarily by choice - this is part of Anthropic's EU AI Act compliance).
Stop asking if you're above average. This article argues the more useful benchmark question is whether you're improving faster than everyone or anyone else. Your own trend shows change; the market trend tells you whether that change was actually yours or just the tide coming in for everyone.
Speaking of Benchmarks, the SaaS Capital Spending Benchmarks for B2B SaaS Companies is out - bookmark this when it's time to benchmark your wallets y'all! Bootstrapped B2B SaaS companies spend 96% of ARR (hey - I do better than that!!), while VC-backed ones burn 101% (last year it was 95% vs 106%). Equity-backed teams in turn grow at 25% average vs 20% if your boots are strapped.
Meta laid off 10% of staff and reassigned 20-30% of software engineers to AI whatever - now they are reportedly offering $400K-$1M+ in equity to senior engineers trying to resign after layoffs/AI reassignments. Some still left for Google, Anthropic, and OpenAI.
Startup liquidity is quietly becoming its own market. Carta administered 71 tender offers worth $3B in H1 2026 - the highest first-half total it's logged in at least six years. With IPOs taking longer, tenders are becoming the liquidity pressure valve for employees and investors.
WISE: Wise's original Seed deck is basically the opposite of most pitch decks today. No giant TAM slide, no AI-generated design theatre. It explains the problem, shows the before/after economics, proves people are already using it, then asks for $1.3M.
Get the top 10, every Friday
Curated SaaS and tech insight from around the web, repackaged for people to put to good use — free.