There's a flood of go-to-market news right now. New AI launches, new data, new layoffs, new funding. Most CEOs and GTM leaders I talk to are either drowning in it or ignoring it completely.

Neither works. You can't run your business on headlines. You also can't afford to miss the ones that change how you go to market.

That's why I'm doing these weekly lives. Sometimes I'll break down the news that matters. Other times I'll predict where go-to-market is headed. Either way, you'll leave with what I think it means and what to do about it.

This week is a news one. Three stories.

44% of CEOs can't prove their AI investments are generating returns. 75% of them plan to spend more.

Gartner surveyed 203 global CEOs at its IT Symposium in Orlando this week:

Gartner's lead analyst David Furlonger said CEOs need technology to create "strategic freedom: the ability to enter markets, reshape offerings, reconfigure operations and respond to disruption faster than competitors."

This isn't an AI problem. It's an operating model problem. CEOs are running AI through org charts, processes, and GTM motions designed before AI existed. It's a jet engine bolted onto a horse carriage. The returns are trapped inside an operating model that can't turn AI capability into revenue.

This is why the 8-pillar GTM OS exists. AI without an operating model is just spend. 63% of CEOs already know the answer.

The move: pick one GTM pillar this week (pricing, positioning, pipeline, or partner ecosystem) and rebuild it for AI. Don't buy more AI tools until you can show revenue from the ones you already have. If you can't draw a line from an AI investment to a revenue motion, cut it.

Source: Gartner press release, Oct 20, 2026

AI is now the #1 cited reason for layoffs in America. 120,000 jobs gone. And the companies using AI the most are hiring.

Challenger, Gray & Christmas reported that employers cited AI in 120,136 job cuts through September. That's about 21% of all announced layoffs, the leading reason this year.

Here's the part nobody talks about. Research from Revelio Labs and Ramp, covering nearly 22,000 U.S. companies, found the heaviest AI adopters grew white-collar headcount by 10.2% over two years. Entry-level roles grew 12%. As CIO put it: "AI won't kill jobs. Bad team design will."

The companies cutting in the name of AI and the companies growing with AI are doing the same thing: adopting AI. One cuts headcount and hopes. The other redesigns the work. Same technology, opposite outcomes. The variable isn't AI. It's team design.

Look in the mirror. If you're cutting heads to pay for AI tools, you're treating the symptom. The disease is your org chart.

The move: don't cut first. Redesign first. Map every role in your GTM org to what AI does and what humans do.

That's the FDO model: a fractional leader running a lean team with AI underneath. The companies growing headcount with AI aren't lucky. They redesigned.

You can cut 120,000 jobs and blame AI, or you can redesign your teams and grow with it. Your competitors already chose. Which side are you on?

Sources: Challenger, Gray & Christmas via Entrepreneur, Oct 17, 2026; Revelio Labs and Ramp research via CIO.com, Oct 16, 2026

Anthropic's S-1 is out. Here are 5 of the many interesting learnings.

1. 900% net revenue retention. Usage customers are spending 9x what they spent a year ago. About 250 customers now pay $10M+ a year. That's labor budget, not software budget.

2. Compute fell from 201% of revenue to 55% in a year (H1 '25 to H1 '26). It happened while they cut customer cost per task by about 40% with Opus 5.5.

3. Sales, marketing and partnerships went from $120M to $3.2B, a 26x increase. It's now larger than total payroll. The fastest-growing B2B company ever is still spending heavily on forward-deployed engineers, SIs, and partners.

4. $6.6M in revenue per employee, up from $1.4M a year earlier. Is this the new normal?

5. Adjusted operating margin went from -159% to +10% (non-GAAP). Revenue was $16.3B in H1 2026, up from $1.2B a year earlier. The $80.7B net loss is mostly paper: $72.4B of it is fair-value markups on convertibles. The operating loss was $693M.

The takeaway for how you build your team: revenue per employee is the number to watch. Even the most AI-native company on earth still pays for people and partners to get its product into customers' hands.

If this was helpful, I'm putting out go-to-market strategy and frameworks on YouTube every day right here (deeper dive all things GTM)

And if you want the full system for running your go-to-market, head to runongtmos.com/move.

Let's get moving.

love,

sangram