Top 10 in Tech - What to know for Week ending September 25, 2026

SaaS METRIC OF THE WEEK

$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.

METRICS

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.

MARKETS

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.

VELOCITY

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.

VIBECODING

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!

GTM

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.

EXPERTISE

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.

STAFF

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.

SENIORIZATION

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?

CASE STUDY

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.