One
Externalization
Explain your thinking to people with zero context. Write documentation that transfers understanding. Do pair programming where you make your reasoning visible. The discomfort is the skill building.
Slide 01
Organizations have rolled out AI coding agents and are watching what drives dramatic business improvements and who stays flat. In 12 to 18 months — if you are at a SaaS company — patterns become clear and start driving promotion decisions. The gap between people building these capabilities now and people waiting is widening every quarter.
Slide 02
When you explain things to colleagues, you rely on shared context. You point at code and say "like this." You reference decisions from three years ago that everyone remembers. That shorthand made you effective. It is also completely invisible to an AI agent.
Externalized knowledge. Not "like this" — a complete explanation of what you are trying to accomplish, what constraints exist, what the architectural context is, and why decisions were made.
Mental models, not navigation. The ability to explain why a system works, not just where to find things. Agents need to reason about what to build. Navigation skills do not transfer.
Understanding, not pattern matching. Agents can pattern match. What they cannot do is work from implicit knowledge they never had access to.
Slide 03
At pure software companies, patterns become clear and start driving promotion decisions for senior, staff, and principal roles inside this window. That clock is running now.
If software supports a physical product — manufacturing, healthcare, logistics — you have more runway. But the gap between builders and waiters is widening every quarter regardless of industry.
Your competition will have concrete business metrics: pipeline cost reduced 40%, review time cut 60%. They will show governance frameworks they built and tested. They will have the stories. Do you?
In 2028, when you are interviewing for that senior, staff, or principal role, they will ask: "Tell me about your experience with AI agents. How did you adapt? What business improvements did you drive?"
The 2028 interview question — and the answer gap that's widening right now
Slide 04
Explain your thinking to people with zero context. Write documentation that transfers understanding. Do pair programming where you make your reasoning visible. The discomfort is the skill building.
Don't just know that things work — understand why. Read code without tasks. Draw diagrams. Ask: do I understand why this works, or just that it works? Can I explain architectural decisions, or just that they exist?
Treat agents like mentoring someone capable but context-free. Write out what you're trying to accomplish before giving instructions. If you struggle to articulate it clearly, that's feedback about your understanding gaps.
Slide 05
Slide 06
If you spent your career explaining technical decisions to non-technical people, you probably have externalization. If you built deep mental models and stayed curious about why systems work — not just how to use them — you are in better shape than you think.
Slide 07
The good news: you do not need to rebuild your entire career overnight. You need to start building the new capabilities alongside the skills you already have. Your domain knowledge, your understanding of how real systems fail, your experience debugging production incidents — all of that transfers. The gap is the externalization and the AI systems experience.
Start there. Tonight. One small project. One capability at a time.