I wrote recently about how mid and late-career developers need to rebuild their careers around AI. This is the version for directors. Because transforming organizations is harder than rebuilding individual technical skills, and the timeline is just as brutal.
You’ve worked ten, fifteen, maybe twenty years to get here. You’re good at leading teams. You’ve earned your position. I’m writing this because what I’m seeing across the industry needs to be said directly.
The path that made you a successful director won’t make you a successful VP. The directors who understand this in 2025 will be VPs in 2028. The ones who don’t will be explaining in interviews why they stayed flat while their peers transformed their organizations.
The Reality Right Now
Organizations have rolled out AI coding agents and are watching which directors drive dramatic business improvements and which stay flat. Most organizations are going all-in on AI. The ones that aren’t won’t help you remain relevant in 2028.
If you’re at a pure software company (SaaS, platforms, developer tools), you have 12 to 18 months before patterns become clear and start driving promotion decisions to VP.
If software supports a physical product or service (manufacturing, healthcare, logistics), you have three to five years. But the gap between directors building these capabilities now and directors waiting is widening every quarter.
The Market Truth Nobody’s Saying
Right now, companies can’t hire directors with three years of AI transformation experience because those directors don’t exist yet.
In 2028, they will exist.
When that company is hiring for VP roles, are you the director with the transformation track record, or the person being passed over for someone who has it?
This isn’t about job security. This is about being marketable for VP opportunities in 2028. About having a resume that opens doors instead of raising questions about why you didn’t adapt.
Why This Is Hard for Directors
Individual contributors need to prove they can still build software effectively. You need to prove you can transform organizations.
Those aren’t the same skill set.
Developers can rebuild their technical skills in isolation. You need to navigate organizational politics, build coalitions with legal and security, reshape team structures, develop capability at scale, and deliver measurable business outcomes while doing all of it.
You need to understand the technology deeply enough to make good decisions AND navigate organizational complexity well enough to implement those decisions. Most directors excel at one. VP candidates need both.
The directors who succeed won’t be the ones who rolled out AI tools. They’ll be the ones who transformed how their teams work and can prove it with metrics.
What Your 2028 VP Resume Needs
In 2028, when you’re interviewing for VP roles, they’ll ask: “How did you transform your team for the AI era? What business outcomes did you achieve? How did you reshape your organization?”
Your competition will talk about reducing cost of goods sold by 35%, increasing flow by 45%, building teams that ship work requiring 20 fewer people. They’ll describe governance frameworks that enabled speed, org structures they tested and measured, conversations with legal that built trust over 18 months.
Will you have those stories? Or will you say “We adopted some tools and people used them”?
The Five Capabilities You Need to Build
Build Deep Technical Understanding
You can’t lead a transformation you don’t understand. Spend time coding with agents alongside your team. Not watching demos. Not reading summaries. Actually building a feature, fixing a bug, feeling the friction points.
When your team says “the agent can’t handle this,” you need to know if that’s true or if it’s a skill gap. When security asks about agent-generated code safety, you need to understand the technical reality well enough to have real conversations, not just repeat what your senior engineers told you.
The discomfort you feel getting hands-on again is the skill building. That’s how you know it’s working.
Reshape Teams for Higher Leverage
Learn what team structure works at 20 to 40 people when AI agents amplify capability.
The old ratio assumptions don’t hold. Your team doesn’t need to hire 20 additional people because you built AI systems to handle that work. But that only works if you restructured how the team operates.
Experiment with flatter hierarchies. Figure out what ratio of senior to junior engineers makes sense when agents amplify capability differently at different skill levels. Learn how to give people more autonomy when AI systems handle routine work.
Build the muscle of organizational redesign at team scale. The directors who advance to VP are the ones who can demonstrate they actually did this work—tried different structures, measured results, learned what works.
Build Governance That Enables Speed
Build governance for your team that actually works in production, not governance that looks good in policy documents.
What can agents touch in your specific codebase? How do you review agent-generated code effectively? What’s your testing strategy for AI-enabled systems? How do you handle agent orchestration in production environments?
Get legal and security comfortable with your specific approach by proving that good governance enables speed rather than preventing it. Have the metrics: 45% flow increase while maintaining or improving quality. Show governance worked because you measured before and after.
Master Getting Legal and Security to Yes
This separates directors who advance from directors who plateau.
Learn how to have these conversations without creating organizational fear. Build relationships with compliance before you need them. Address concerns with specificity instead of generalizations. Document your approach so thoroughly that legal can actually review it and make informed decisions.
Build trust through transparency and metrics. When security asks “how do we know this is safe?” have an answer based on actual governance frameworks you built and tested, not theoretical promises.
The directors who can demonstrate they navigated these conversations successfully—who can show they built trust with legal and security over 18 months—those are the directors who get VP offers.
Develop Capability Systematically
Learn what makes someone effective with AI agents at the individual level and how to develop people who are struggling.
Build assessment frameworks that identify who can build AI systems, who understands agent orchestration, who gets governance in the SDLC. Create environments where capability flourishes rather than just checking training boxes.
Prove that capability development drives business outcomes with actual metrics. The directors who can show they built capability across entire teams—who can demonstrate specific programs they created and results they measured—those are the directors companies want leading larger organizations.
The Timeline Reality
You have twelve months to start building the track record that matters for 2028.
Directors who started a year ago already have compelling stories. They can talk about specific transformations they led. They can show business outcomes: “My team ships work that used to require 45 people. We’re 25 people. Cost of goods sold dropped 35%.”
Directors who start today will have solid track records by late 2026. They’ll have reshaped multiple team structures. They’ll understand what governance actually works from real implementation. They’ll have relationships with legal and security built over time.
Directors who wait another year will be competing in 2028 against candidates with three years of demonstrated success transforming teams, building governance, getting legal to yes, and driving measurable business outcomes.
What Success Looks Like
By 2028, you should be able to walk into any VP interview and tell stories like:
“I led a team of 25 people that ships work that previously would have required 45 people. We didn’t hire those 20 additional roles because we built AI systems to handle that work. Cost of goods sold dropped 35%. Flow increased 45%. We hit those numbers while maintaining quality because I built governance frameworks that actually work in production.”
“I reshaped our team structure three times as we learned what works at scale with AI agents. The final structure is flatter, gives people more autonomy, and delivers better business outcomes than our old hierarchy. I can walk you through what we tried, what failed, and why the current structure works.”
“I got legal and security comfortable with AI agents in our SDLC. I documented everything, built trust through transparency, and proved with metrics that good governance enables speed. When we rolled this out company-wide, legal already understood the framework because I’d spent 18 months building that relationship.”
“I developed systematic capability across my entire team. I know what makes someone effective with AI agents, how to identify capability gaps, and how to develop people who are struggling. I have the metrics showing that capability development drives business outcomes.”
These are the stories that get you VP roles. These are the capabilities that make you valuable regardless of what specific AI tools exist in 2028.
Your Career in 2028 Starts Today
The market in 2028 will have directors with proven transformation track records. Directors who can walk into VP interviews with compelling stories, real metrics, demonstrated capability transforming organizations.
Those directors will get the opportunities—the VP roles at the companies you actually want to work for.
You can be one of those people. But you need to start building that track record today, while companies still develop people internally, so you have it when the market has options and you’re competing against people who already spent three years building theirs.
You can do this. The capabilities are learnable. The path is clear enough if you start walking it.
Start today. Where you are three years from now—what opportunities you have, what companies want to hire you, what your trajectory looks like—depends on what you do in the next twelve months.
Engineering leader who still writes code every day. I work with executives across healthcare, finance, retail, and tech to navigate the shift to AI-native software development. After two decades building and leading engineering teams, I focus on the human side of AI transformation: how leaders adapt, how teams evolve, and how companies avoid the common pitfalls of AI adoption. All opinions expressed here are my own.