I used to think my biggest strength as a product leader was being a breaker of silos. I’m a business and systems architect at heart — the kind who refuses to just “ship fast” and instead builds systems and processes that make good products easier to ship.
The irony? Those same systems may have made it easier to replace the decision-making with AI.
That’s why a recent post about two Senior PMs stuck with me:
- Senior PM A — Clear roadmap, supportive team, space to decide, loves the job.
- Senior PM B — Constant firefighting, no clear goals, drowning in meetings, exhausted.
Same title. Same salary. Completely different realities.
The obvious answer
Most people see this and think: “Clearly, Senior PM A has the better gig. Who wouldn’t want clarity, respect, and breathing room?”
I agree — if you’re talking about today’s workplace.
The AI-era twist
In a well-oiled, optimized system, Senior PM A’s decisions follow predictable patterns: Quarterly planning? Review the metrics, weigh the trade-offs, pick a path. Feature prioritization? Run it through the scoring model. Resource allocation? Follow the established framework.
Those are exactly the kinds of structured, rules-based decisions AI can handle well — not because they’re trivial, but because they have clear inputs and repeatable logic.
Senior PM B’s world is different. One week it’s killing a feature mid-sprint because a major client threatened to churn over an unrelated issue. The next, it’s navigating a regulatory curveball that suddenly affects three product lines. Then the CEO declares a new strategic pivot — immediately.
This isn’t just chaos. It’s high-stakes problem-solving with incomplete data, shifting constraints, and human dynamics in the mix. Right now, that’s still work AI struggles to do.
Why chaos can be strategic
If you’re Senior PM B, you’re not just firefighting. You’re building skills that are harder to automate:
- Reading between the lines — knowing when “customers are asking for this” means three key deals are at risk vs. one loud voice in the room.
- Navigating crosscurrents — redirecting an “urgent” marketing request toward something that actually moves the business.
- Making judgment calls with partial data — acting decisively while staying ready to adapt.
These skills aren’t “soft.” They’re advanced problem-solving abilities: reading between the lines, navigating political currents, and making judgment calls with partial data. AI can process information, but right now, it struggles to match human problem-solving in high-context, high-stakes situations.
How to use the advantage
If you’re in the chaos seat, you have leverage — but only if you’re intentional:
- Document your decisions — keep a log that shows how you reason through ambiguity, not just what you decided.
- Translate chaos into patterns — identify which recurring problems point to deeper systemic fixes.
- Build your network — the people you can call in a pinch are as valuable as any process.
The long game
Eventually, AI will get better at handling some of this unpredictability too. But the people best positioned to design that AI? They’re the ones who’ve lived the chaos and know which decisions can be structured — and which can’t.
The takeaway
In the AI era, the “worse” jobs might be the ones teaching you the most resilient skills — especially the hardest to teach: problem solving. So, if you’re Senior PM B right now, you may be tired — but you’re also learning how to make high-context, high-stakes calls in ways AI can’t yet match.
The key is to treat it as training for the future, not just survival in the present.