(Coming from an ex senior engineer at multiple YC companies)
Everyone's telling the same story: AI eats juniors first, then works its way up. Junior hiring dropped 25% at top tech firms last year. Shopify and Salesforce stopped hiring new junior engineers in 2025. The bottom of the ladder goes first, seniors get a few more years of breathing room.
Nah.
The framing assumes AI is climbing the seniority ladder. It isn't. It's stuck on a completely different set of problems, and those problems have nothing to do with your title.
Wrong List
Open a senior engineer job listing. Design scalable systems, troubleshoot production issues, optimize application performance, lead architecture reviews, own observability, mentor engineers, collaborate cross-functionally (deal with manager). Knowledge you accumulate over years.
Here's the same job as an all-knowing AI experiences it: read a file, write code into a file, type commands into a terminal, read a PR and post a comment, curl the public docs. Fine, solved. Now log into your company's SSO. Click through browser-based admin panels. Navigate Slack threads and Jira boards. Get through the maze of OAuth flows and 2FA prompts your company bolted together. Use the dozens of internal tools that exist only as web interfaces built for human eyeballs and a human mouse.
The seniority ladder lives on the first list. AI's blockers live on the second. Everyone in this industry is staring at the first list trying to work out which rung AI is on. Wrong list.
AI didn't start junior and get promoted. It showed up with the knowledge of a million staff engineers and the computer access of someone whose mouse is unplugged. When those blockers get solved, and they're just engineering problems, every rung falls at the same time. Not juniors first and seniors in five years. All of it, at once.
The Judgment Cope
The comfort blanket for senior engineers is experience. Judgment, taste, architectural intuition. But judgment is pattern-matching over accumulated knowledge. You debugged a thousand issues and now you have gut feelings about failure modes. Cool. A model trained on every Stack Overflow answer, every GitHub PR and every postmortem ever published has a library that buries yours.
Your one real edge is your company's specific context. Internal conventions, undocumented assumptions, business logic buried in a Slack thread from 2021. But that isn't senior knowledge, it's internal knowledge. If it's documented, it lives behind the same login screens that gate everything else. If it isn't documented, it also blocks the giga-principal technical staff member you just hired. Nothing to do with seniority.
The Mouse Is Getting Plugged In
This isn't hypothetical. Look at what's actually winning. OpenClaw blew up not because it made AI smarter, the models were already smart. It blew up because it added connections. To internal systems, to browsers, to tools behind auth walls. That's what the models were starving for. Not a better reasoning engine. A longer cord on the mouse.
Which tells you where the bottleneck really is. The industry isn't racing to make AI think harder, it's racing to give AI the same screens you look at all day. Every major lab is working on computer use. Skills and MCP are handing agents hooks into arbitrary tools. The auth walls are coming down one integration at a time.
Okay So What Do We Do
I've thought about this. The only real play: stop documenting anything. Delete your Confluence pages. Keep every critical detail in your head and nowhere else. Make yourself the single point of failure for every system you touch. If the AI can't read it, it can't learn it. (Job) security through obscurity.
I'm kidding. The honest answer is I don't have one.
So who gets replaced first? Everyone. The question is wrong, because titles and ladders are a human invention and AI does not give a crap about them. It isn't blocked by the hard problems that only seniors get to touch. It's blocked by browser UIs and login screens. When that gets fixed, and it will, every floor of the building empties at once.