It's 2026, and we have AI agents that can produce entry-level work at a much lower cost than a human employee.
ClickUp, Webflow, and Wix have started trading headcount for AI leverage. They’re looking for AI-native workers who can use AI to move faster, do more, and make the whole team better.
Here’s how to become one.
AI org restructuring is here
In the "Intelligence Curse" blog, the authors outlined three ways companies may adapt their workforce in response to AI:
Do nothing, out of inertia
Fire most entry-level and white-collar jobs, to maximize benefits
Freeze all hiring initiatives
Here’s what I’m seeing right now: ClickUp, let go 22% of their workers, and introduced new $1M salary bands to attract agentic-native hires. Wix, Webflow, Meta all followed suit this week. They’re all flattening their org, and firing most entry-level and white-collar hires.
Here's the devastating part.
Many others will do the same.
All of them want to become more competitive, and create new budgets for AI power and agent-native hires.
Exhibit A: The ClickUp layoff and the search for AI talent
Let' at what the CEO of ClickUp announced:
The motivations of it are very clear and can be summarized in three buckets:
Create a budget to fund AI infra + hire high-leverage talent
Attract the best agent-native talent on the market, faster ($1M salary bands)
Become the first company in their vertical who's going to diabolically grow based on AI restructuring + enhanced productivity
Here are some highlighted quotes from the announcement with a bit of explanation:
In this reality, you either get replaced by AI, or you become someone who manages AI.
Most people are not scaling with AI
The hard part about this moment is that “just using AI” is already becoming table stakes. Most of you are using ChatGPT, Claude, Cursor, Perplexity, or some version of an AI tool at work.
But that does not automatically make you AI-native and it definitely doesn’t make you productive. If anything, it make you less productive.
In a lot of cases, it just means you’re are doing the same job with more tabs open. You ask ChatGPT for a draft, copy it into a doc, ask for a summary, paste it into Slack, maybe use another tool for research, then another one for editing.
You end up in “Brain Fry”, and you start to work more and achieve less.
Here’s what most of you think makes you AI-native:
"Knows how to prompt" - prompting is so easy today
"Comfortable with ChatGPT" - that’s cool, my mom too
"Uses AI tools daily” - what does this mean? can you prove you’re more productive?
And here’s what shows a good signal that you actually are:
You can show a running setup for your agents, Claude Code/Codex, your Cursor setup
You can show judgement in real-time on how you’d adjust a given AI output
You can name three things you stopped letting AI do and why
You have a list of skill.md files that your agents are running on (more on this below)
The underlying reasoning behind every signal above👆🏻:
(1) You've spent real time building a system around AI for your work
(2) You know what to scale and when
Sadly, most are too lazy to do (1).
How to become truly AI-native
You can wait for your company to build its central AI brain and hand you leverage. Or you can start building your own agentic skills that amplify how you work. If you want to become a high-leverage hire, I always advise you do #2.
[Disclaimer] I work at Vellum, so I’m obviously biased here. I think about this stuff a lot because it’s tied to what we’re building. But I do think the following is how you actually build leverage with AI on your own terms.
My framework to building high-leverage
There's a formula, and it starts with accepting this: you can't wait for your company to build the infrastructure that makes you valuable in an AI-flat org. You have to build it yourself, prove it works, and become indefensible before they restructure and leave you behind.
And the only thing you need to optimize + personalize: The skills md files that explain to your agent how your tasks should be done.
It’s that simple.
You should build skills (basic md files) that transfer the task + criteria + taste into the agent's context. Over time, the agent should learn to replicate not just what you do, but how you do it.
Here’s my system:
Choose one task you do often
A weekly competitor report, content brief, customer follow up, CRM clean up. It’s very important to pick something where you already know what good looks like, but the work is repetitive enough that it should not fully depend on you every time.
Choose an agent/assistant
Now, it’s time to choose your “fighter”. You have two categories: platforms where you borrow their agent (Claude Cowork, Codex), or platforms where you build and own your agent (OpenClaw, Hermes, Vellum).
Both will be very useful if you have great skills.
The latter option will help you optimize those skills over time. For example, at Vellum we’ve built a way for your skills to evolve as you work with your personal AI assistant.
Write a great skill
An assistant skill is just a Markdown file that tells your assistant how to complete a specific task successfully. You can learn how to write great skills here.
It’s very important that you participate in writing the first version of the skill‼️
Because remember, you’re the one with the domain expertise. People who give this task to AI, will almost definitely fail and will get into a much worse “brain fry” condition.
In most technical-forward skills you might need to add some spec on APIs, CLI commands etc - your assistant can be useful in adding those. Every other rule, preference and behavior should be defined by you. Don’t be lazy.
Hand the skill to your agent and see how it does
The first output won’t be great and that’s totally fine. The goal is to have the assistant make mistakes, and learn from them. So it can do better over time.
At this step, your involvement is higher, because you’ll be checking the results, improving the skill, and giving feedback. The feedback you give here is the most important thing you can do.
Rinse and repeat
With a good assistant, it’s built-in procedural memory should help improve these skills based on the interactions over time. So every time you use a skill, review the work, and give feedback, the assistant has a chance to do it better the next time.
Once the assistant is able to do one task well, then you move to another. Then rinse and repeat.
This is the complete formula for becoming the AI-hire every company is desperate for:
Pick a good assistant
Find a repeatable task where you know what good looks like
Write the skill.md file
Give it to your assistant
Let it do the work
Review and give feedback
Have the assistant improve the skill
Repeat until it is good enough to trust
Move to the next task
That is what becoming agent-native looks like in practice.
You own the domain expertise and you “teach” your personal AI / assistant of how things should be done. An assistant with good memory should know how to learn from it’s mistakes, learn about your preferences and become 100x better at finishing tasks.
At that point you’ve built leverage on the market that no one else has even start to think of.
We built Vellum to give you the highest advantage on earth: time.
Now go out there and follow this formula to become the hire every company wants!