AI has Collapsed the Career Ladder. The Four Questions That Define Your Career Stage

A "Senior Product Manager" at Google does fundamentally different work than a "Senior Product Manager" at a 50-person startup. An "Associate Designer" at a pre-seed company might be making high-stakes decisions that a "Principal Designer" at an enterprise never touches.

Job titles are organizational artifacts. They reflect salary bands and hierarchy, but they're a poor reflection of the level of thinking you're actually doing.

The same goes for years of experience. You can find two people with identical tenure where one has spent five years solving complex, ambiguous problems, while the other has spent five years executing well-defined tasks. Both have the same resume. Only one has developed high-level judgment.

If titles and tenure are noisy signals, how do you know where you actually stand?

The Four Questions

Your career stage isn't defined by what's printed on your business card. It's defined by the question you're primarily trying to answer in your work. There are four questions, each representing a distinct level of thinking:

• Level 1: "Is it done?" 
  You're given specific tasks. Your value is speed and reliability.

• Level 2: "Is it solved the right way?" 
  You're given problems. Your value is your judgment to choose the best methods and tradeoffs in delivering full solutions.

• Level 3: "Is this the right problem?" 
  You're given outcomes. Your value is your ability to think in cross-functional systems to identify the real problems to solve.

• Level 4: "Is this the right direction?" 
  You set the frame itself. Your value is in defining the best outcomes to pursue, which requires calibrated decision-making under uncertainty.

These aren't about seniority in the traditional sense. They're about cognitive work. And in the age of AI, the gaps between the levels are compressing faster than ever.

The Vanishing Floor: Level 1 is Being Automated

For decades, the first two years of a career were spent almost exclusively at Level 1. You learned the ropes by "doing the thing." But as discussed in the ebook, AI is now the ultimate Level 1 employee. It can produce outputs a lot faster and the quality bar is improving all the time.

This means Level 1 has effectively vanished as a viable career stage. You can no longer spend years exploring different spaces and building pattern recognition on how to solve distinct problems. To be employable today, you have to move into Level 2 immediately. 

You aren’t just producing work; you are directing the systems that produce it.

Level 2: Designing Solutions (Table Stakes)

Level 2 is now the entry point. When someone says "We need to improve onboarding," you need to know the different options available and the tradeoffs of each. There are always many solutions, from implementing a tutorial flow to adding contextual tips to providing an empty state design. The skill is knowing which fits this situation.

The challenge is that the repetition which used to build judgment is gone. You must now develop it deliberately: studying principles, shipping side projects, and learning from people who explain their reasoning.

Level 3: Where Humans Still Win

Level 3 professionals stop accepting the problem statement as given.

When a stakeholder says "We need a mobile app," the Level 2 thinker asks "Flutter or React Native?" The Level 3 thinker asks "Why do we think an app solves the retention problem?"

This requires seeing across functional boundaries because a design decision affects engineering, a product choice ripples into sales cycles, and a pricing change impacts customer success.

AI excels at individual tasks but struggles to connect insights across disciplines. This is where breadth becomes more valuable than depth. You need to be "comb-shaped": moderate depth across multiple areas, with the ability to connect them. That's where human leverage now lives.

The trap is staying in your functional home. If you only ever see the design perspective or the engineering perspective, you'll only ever see part of the picture.

Level 4: Setting the Frame

At Level 4, you're no longer diagnosing problems within a frame someone else set. You're deciding what outcome the organization should pursue at all.

These decisions happen under uncertainty. Data is incomplete. Causality is unclear. Feedback arrives late and filtered. You're making evidence-informed bets and creating enough shared belief to test them.

The trap is that your influence changes. Casual suggestions now consume organizational resources and half-formed ideas become directives. You need to know when to use your weight and when to hold back, and most importantly, you need people around you who will tell you the truth even when it's uncomfortable.

The Compression Reality

While AI is replacing the tasks at level 1, it is also acting as a catalyst, pushing people up this ladder faster than ever before. What used to take a decade to learn now has to be mastered in five years with an AI sparring partner that can stress test your ideas and identify gaps (when used correctly). 

This is an incredible opportunity for those who are intentional about their growth, but it’s a massive risk for those who stay in their comfort zone.

Breadth is becoming more valuable than deep, isolated expertise. To reach Level 3, you need to be "comb-shaped", where you have enough understanding across multiple domains to see how a change in one area ripples across the entire organisation. 

AI can't connect these dots across a business yet; that is where human leverage now lives. And as for setting company direction, the old maxim is still true: 

“A computer cannot be held accountable, so a computer cannot make the final decision.”

Which Question Are You Answering?

The goal isn’t to feel behind; it’s to gain clarity. If you’re early in your career, it’s natural to spend time in Levels 1 and 2. But if you’ve been in the industry for years and you're still primarily asking "Is it done?", you are competing with a machine that doesn't sleep.

Your title might lie to you, but your daily work doesn't. If you want to progress, stop trying to do more tasks. Start trying to answer a harder question.

This is the first article in a series exploring how AI is reshaping career progression. The next article examines the actions that junior employees can take as they start their careers at a time when level 1 jobs are being automated. You can read the full details in our free ebook: Managing your Career in the Age of AI.