In partnership with
Hey friends, Happy Wednesday!
If you’ve been paying attention to how AI is changing work, you’ve probably had this moment:
You automate a task that used to take hours.
You use a copilot to draft something in minutes.
You realize your team can move faster with fewer people involved.
And you think, “This is going to change everything.”
You’re right.
But here’s the part most people miss:
The biggest shift isn’t speed.
It’s value.
As AI absorbs structured, repetitive, coordination-heavy work, something subtle happens. The layer of work that used to differentiate you starts becoming baseline.
Execution becomes expected.
Judgment becomes scarce.
And scarcity drives career leverage.
This edition is a practical deep dive into what I call the Post-Automation Skill Stack. Not a motivational piece about “soft skills.” Not another tool tutorial. A clear framework for understanding where career value is actually moving — and how to position yourself above the automation layer rather than inside it.
Today we’ll explore:
What the data says about which tasks are being automated first
Why shallow work is declining and ambiguity is increasing
The three-layer stack: Execution Literacy, Decision Quality, and Human Leverage
What interviews are really testing now
Where salary premiums are emerging
And a 90-day playbook to deliberately move up the stack
If automation is expanding around you, the question isn’t whether your job will change.
It’s whether you’ll evolve faster than the baseline expectation.
Let’s explore.
— Naseema Perveen
IN PARTNERSHIP WITH MINTLIFY
AI Agents Are Reading Your Docs. Are You Ready?
Last month, 48% of visitors to documentation sites across Mintlify were AI agents—not humans.
Claude Code, Cursor, and other coding agents are becoming the actual customers reading your docs. And they read everything.
This changes what good documentation means. Humans skim and forgive gaps. Agents methodically check every endpoint, read every guide, and compare you against alternatives with zero fatigue.
Your docs aren't just helping users anymore—they're your product's first interview with the machines deciding whether to recommend you.
That means:
→ Clear schema markup so agents can parse your content
→ Real benchmarks, not marketing fluff
→ Open endpoints agents can actually test
→ Honest comparisons that emphasize strengths without hype
In the agentic world, documentation becomes 10x more important. Companies that make their products machine-understandable will win distribution through AI.
