Hey everyone,

So Gartner went and studied 350 companies spending a combined $725 billion on AI this year. 80% of the ones that fired people to fund AI got literally nothing back. Zero. Not "less than expected." Zero.

And the layoffs keep coming anyway. Cisco just cut 4,000 people for the third time since 2024, same week they posted record revenue. This week we're breaking down why the math doesn't add up, and what the companies that actually got AI right did instead.

AI Job Cuts Aren't Improving Returns — The actual Gartner study. Read this before your next interview so you can quote it back when they ask about "AI transformation."

Amazon Employees Are "Tokenmaxxing" — Amazon built internal leaderboards tracking how many AI tokens you use. Employees are now gaming them by running fake tasks. Nobody told them this was what winning looks like.

Stop Learning to Code — The take getting traction: architecture plus AI tools is now enough to build real products, and the window to get ahead of your non-technical competition closes in 6 to 12 months.

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Here's a thing companies have been doing: cutting engineers to fund AI, then wondering why their AI isn't working.

Cisco, 4,000 people gone, third round since 2024, same quarter they posted record revenue. LinkedIn cut 875 engineers last month. Tech is at 85,411 cuts year-to-date, up 33% from 2025. Every single announcement mentions AI as the reason.

But here's the part they don't put in the press release. 80% of those companies got absolutely nothing back.

Gartner surveyed 350 executives at billion-dollar companies and asked them straight up: did cutting headcount to fund AI improve financial performance? The answer was no. Not "it's complicated." Companies that cut the most aggressively showed returns nearly identical to those that cut the least. Gartner Distinguished VP Analyst Helen Poitevin said it directly: "Workforce reductions may create budget room, but they do not create return."

$725 billion in AI infrastructure this year. 80% with nothing to show for it. That's not a transformation. That's paying a tax to look like you have a strategy.

So who actually won?

The same data shows the companies generating real AI returns did the opposite. They retrained people instead of replacing them. Moved engineers toward higher-leverage work. Built teams that mixed AI capability with human judgment. Focused on real operational change, not headcount announcements.

Here's what that changes for you right now.

The question that filters every company you talk to. Ask them how the engineering team's role is changing with AI. Companies cutting for the optics will give you a vague non-answer. Companies that actually know what they're doing will say something specific, like: our engineers spend 30% less time on boilerplate and 30% more on architecture decisions, and here's how we track it. That specificity is everything.

The one project that separates you from everyone else applying. Right now almost everyone can say "I use AI tools." Almost nobody can say "I built a system where one model classifies input and a second acts on the output, and here's what broke in the pipeline." Pick one task you currently do with a single prompt and rebuild it as two steps. Don't even deploy it. Just document what broke and why. That gap is learnable in a weekend and it's exactly what hiring teams at places like Anthropic and Scale are screening for.

The red flag you're probably walking past. Amazon employees are running fake tasks to game AI usage leaderboards. That's what it looks like when a company tracks AI adoption as a number but has no idea what good AI adoption actually means. Ask in every interview what success looks like for an engineer working with AI. If the answer involves token counts or Copilot suggestions, that's your sign.

Here's the honest version of where this leaves you. You're entering the market right when this split is happening, between companies that figured out AI and companies still paying the tax. The ones that figured it out are actively building and hiring right now. The ones still paying the tax are going to do another round of layoffs and wonder why returns aren't improving.

You already know which side you want to be on. The Gartner question in your next interview will tell you which side they're on.

The companies getting AI right aren't cutting engineers. They're converting them. Figure out which side of that bet you want to help build.

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Until next time,

Team Jobless