Build a Support System That Scales: How Product Leaders Maximize Impact with Delegation and AI

Podcast cover for Episode 47, Support System for Product Leaders, from All Things Product with Teresa Torres and Petra Wille; mint background with abstract teal and purple network.

I hear the same refrain from product leadership peers everywhere: we’re overwhelmed. Shrinking headcount, constant AI disruption, economic uncertainty, and relentless context switching make it feel like we’re carrying two jobs—setting strategy while shielding our teams. I recently listened to an episode of All Things Product that zeroes in on what a real support system for product leaders looks like, and it resonated deeply with my day-to-day.

Want to listen to the conversation yourself? Find it on Spotify or Apple Podcasts.

Here’s the core tension I see (and felt early in my own leadership journey): product leaders tend to underinvest in themselves. We hold onto work because it feels faster, safer, or “just easier if I do it.” But that pattern quietly taxes strategy, slows learning, and caps team throughput. The hidden cost of “doing it all yourself” is real.

Early in my tenure leading product, I tried to keep every plate spinning—roadmap reviews, stakeholder prep, user research, executive updates—while protecting my team’s focus. I was busy and useful, but not maximally valuable. The turning point came when I started building a lightweight support stack: a few hours of executive assistant help each week, targeted research support for bet sizing, and a personal cadence with a leadership coach. The result wasn’t just more time; it was better time.

One provocative point that landed hard: product leaders rarely have executive assistants—and that’s a problem. If your calendar is your operating system, an EA is an extension of your leverage. Mine now handles scheduling, meeting hygiene, prep packets, and post-meeting artifacts. That shift moved me from “calendar triage” to “strategic curation.” It also reinforced a core principle: delegation is a leadership skill, not a weakness. When I delegate outcomes (not just tasks), my team learns, ownership grows, and we ship decisions faster.

Support for strategy work shouldn’t stop at the calendar. Research and data enable better bets. Lightweight research ops, access to product analytics, and brief synthesis sprints keep me anchored in evidence without drowning in artifacts. Paired with a strong community of practice, I get a steady stream of comparative patterns—how other leaders delegate, scope advisory boards, or run decision reviews—which short-circuits trial-and-error.

Coaches were framed as shortcuts for clarity, accountability, and skill-building—and I agree. A good coach compresses cycles, sharpens decision quality, and holds the mirror up when you drift into doer mode. Two quotes captured the mindset perfectly: “You are a pro athlete. It makes sense to think about how you scale your impact without adding more to your calendar.” — Petra Wille. “As you get busier, it becomes more important to focus on the value only you can bring.” — Teresa Torres.

There’s also a helpful nudge to let go of perfectionism: “80% done by someone else is 100% awesome.” — Dan Martell (quoted). In practice, that means I accept great drafts from others, then add the 10–20% only I can contribute—context, narrative, and the sharp edges of the decision.

What about AI? The conversation hits a practical middle ground I share: use AI where it compounds leverage—meeting summaries, research synthesis starters, doc outlines, and backlog triage. But keep humans where judgment, alignment, and context truly matter—strategy framing, stakeholder management, and the final decision-making loops. In other words, apply an AI Strategy that respects product leadership’s uniquely human work.

Key themes I took away: why product leaders struggle to scale themselves; the true cost of “doing it all yourself”; why not having executive assistants limits impact; delegation as a core leadership capability; how to identify and protect the work only you can uniquely do; using research and data to inform strategy; coaches as accelerators for clarity and accountability; communities of practice as a force multiplier; adopting a “professional athlete” mindset; when AI helps—and when humans still matter; and the liberating mantra that “80% done by someone else is 100% awesome.”

If you’re wondering where to begin, start small and practical. Audit your time: what work truly requires you? Experiment with small amounts of support (even a few hours a week). Delegate outcomes, not just tasks. Keep the hands-on work you love—but be intentional. Use peers, coaches, and communities to learn how others delegate. Don’t wait until burnout to build your support system.

Resources mentioned if you want to go deeper: Follow Teresa Torres: https://ProductTalk.org. Follow Petra Wille: https://Petra-Wille.com. Petra’s Coaching for Product Leaders: https://www.petra-wille.com/coaching-packages. Dan Martell’s book Buy Back Your Time: https://www.buybackyourtime.com.

I’m curious: what’s one outcome you’ll delegate this week, and what support would make it stick? Share your thoughts in the comments—your playbook might be exactly what another product leader needs right now.


Inspired by this post on Product Talk.


Book a consult png image

What is the central idea for scaling impact in product leadership according to the post?

Scale comes from delegating outcomes and building a lightweight support stack (EA help, targeted research, coaches, communities of practice) and using AI where it compounds leverage. This shifts work toward high-leverage activities and accelerates decision-making.

Why does the author emphasize executive assistants?

An EA expands leverage by handling scheduling, meeting hygiene, prep packets, and post-meeting artifacts. This shift moves you from calendar triage to strategic curation.

What roles support strategy work beyond the calendar?

Coaches and communities of practice provide clarity, accountability, and access to patterns from other leaders. Lightweight research ops and analytics keep you anchored in evidence.

How should AI be used according to the post?

Use AI where it compounds leverage—meeting summaries, research synthesis starters, doc outlines, and backlog triage. Keep humans involved for strategy framing, stakeholder management, and final decisions.

What is the '80% done by someone else' mantra and its meaning?

The mantra encourages accepting strong drafts and focusing your own contribution on the final 10–20%—adding context, narrative, and the sharp edges of the decision. It helps prevent perfectionism and moves work forward.

What practical first steps does the post recommend to begin building a scalable support system?

Audit your time to identify work that truly requires you. Start with a few hours of support weekly, then delegate outcomes—not just tasks, and learn from peers, coaches, and communities.

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *

Signup for Weekly Digest Emails

Categories

Archieve