In partnership with
AI agents now read your docs almost as much as humans do.
Mintlify analyzed 790 million requests across its documentation platform. The finding: AI coding agents account for 45.3% of all traffic, nearly tied with traditional browsers at 45.8%.
Two tools are driving almost all of it:
Claude Code: 25.2% of total traffic, more requests than Chrome on Windows
Cursor: 18% of total traffic
Together they account for 95.6% of all identified AI agent traffic
The rest of the field, OpenCode, Trae, ChatGPT, and NotebookLM, is showing up but nowhere close.
One caveat: OpenAI's Codex doesn't send an identifiable user-agent header, so the real agent percentage is likely even higher.
The takeaway for anyone maintaining developer docs: your documentation now serves two audiences. Structure and machine-readability matter as much as clarity for human readers.
High-quality AI coding in 2026 has gone way past just picking a good model and calling it a day.
There's now much more that needs to be properly calibrated and fine-tuned to get the very best results from your agent.
We now have Skills which let you precisely shape AI behavior by packaging instructions, scripts, and context into reusable units.
And that's what the new, wildly popular "Karpathy Skills" have been able to take advantage of to the fullest extent.
Karpathy Skills is a set of strict rules and guidelines that drastically improve the accuracy and reliability of your agent, once you add them to your CLAUDE.md (or CURSOR.md) file.
Let's take a look at some of these key rules, so you can better understand why it makes such a massive difference.
1. The surgical strike
Most LLMs try to be helpful. Too helpful.
You've probably experienced this:
You ask for a fix or new feature.
They make the changes… but also:
clean up unrelated code
reformat files
rename variables
refactor “while they’re there”
It looks productive. But it leads to low model trust and messes up your mental model of the codebase.
The rule:
Only change the exact lines required
No drive-by edits
No unrelated improvements
Why it matters:
Prevents diff bloat
Makes PRs readable
Reduces hidden risk
Think about review time.
500-line diff → slow, error-prone
5-line diff → fast, obvious
This isn’t about style.
It’s about trust.
A good AI agent doesn’t try to improve everything.
It solves exactly the problem.
2. Extreme disambiguation
How Jennifer Aniston’s LolaVie brand grew sales 40% with CTV ads
The DTC beauty category is crowded. To break through, Jennifer Aniston’s brand LolaVie, worked with Roku Ads Manager to easily set up, test, and optimize CTV ad creatives. The campaign helped drive a big lift in sales and customer growth, helping LolaVie break through in the crowded beauty category.