Tag: delegation

  • My Always‑On AI Team: How I Get Claude Agents to Tackle Work While I’m Offline

    My Always‑On AI Team: How I Get Claude Agents to Tackle Work While I’m Offline

    Most mornings I wake up to a to-do list that’s already been updated—because my always-on team of agentic AI assistants has been working while I sleep. I rely on Claude to orchestrate these agents so routine prep, follow-ups, and retrospectives never slip through the cracks.

    When a podcast recording hits my calendar, my podcast-manager agent (powered by Claude) automatically creates a podcast-interview-prep task with a concise summary of who I’m interviewing and what they are building. It also creates a transcript review document with the correct share settings. After the recording, it adds a task to my to-do list to share the transcript with the podcast participants.

    For sales, my sales-admin agent (also powered by Claude) prepares a sales-meeting-prep task with notes on who I’m meeting with, where they are in the sales process, and what I need to move the deal forward. After the call, it generates clear next-step tasks so momentum doesn’t stall.

    Every week, my coding-manager agent (still powered by Claude) compiles a report from my prior week’s coding sessions and offers targeted tips. It flags recurring mistakes or dead ends, shows how to avoid them, and suggests ways to work better with Claude. It’s the retrospective I never skip.

    In this walkthrough, I’ll explain how I get Claude to complete tasks for me while I’m away from the computer—and how I designed the system to balance power, safety, and cost control.

    I first explored this approach after seeing the rapid growth of OpenClaw. OpenClaw is an open-source "agent harness" that lets you configure personalized agents to act on your behalf. It’s incredibly promising, but the early wave of enthusiasm also revealed pitfalls: complex safety configuration, overly broad machine access (browser, terminal, files, credentials), third-party skills of varying quality, and surprise usage bills.

    After hearing one too many horror stories about wasted hours and unexpected charges, I set out to design a safer, more predictable way to capture the benefits of OpenClaw while managing risk and spend. That’s what led to my current agent setup.

    For transparency: I’m a long-time practitioner and a genuine fan of Claude Code. I have not received any compensation from Anthropic for writing about my approach. If that ever changes, I will disclose it—both because it’s required by the FTC in the U.S. and because it’s simply the right thing to do.

    An Overview of How My Agent Team Works

    Today, I run three specialized agents: a podcast manager, a sales admin, and a coding manager. As I invest more, I expect this team to grow—because the pattern scales cleanly across use cases.

    This system runs on four core components that keep everything reliable, auditable, and cost-aware.

    First, agent identity. I use a simple but powerful convention: an identity markdown file that tells the agent who it is, where its task folder lives, and provides context for the types of tasks it will do. This keeps scope tight and intent explicit—critical for safety and predictable automation.

    Second, the scheduler. I’m using MacOS’s built-in scheduler (via LaunchAgents). This is like cron, but runs with all your user permissions on Mac. That means I can run all of this under my Claude Code Max subscription or my ChatGPT/Codex subscription. The result is a dependable heartbeat for my AI workflows without relying on fragile cloud glue.

    Third, tasks. Each agent owns a dedicated folder of tasks. A task is a markdown file with frontmatter. That structure makes work items easy to create, parse, review, and version—perfect for repeatable automation with a human-in-the-loop safety net.

    Fourth, scripts. Each agent has its own scripts folder with utilities it can call on demand or that run on a schedule. These scripts are small, composable, and transparent—so I can evolve capabilities without ballooning risk or complexity.

    Agent identity, tasks, and scripts are saved in Obsidian—not Claude Code skills or agents. The scheduler runs on my always-on Mac Mini. The benefit of this is it just works across all of my devices and I can seamlessly switch between Claude Code, Codex—or any other coding CLI—as I need to. All it takes is updating my script that the scheduler uses.

    In practice, this architecture delivers exactly what I want from agentic AI: clarity of responsibility, strong guardrails, and outcomes that compound. My podcast manager keeps interviews buttoned up, my sales admin removes administrative drag, and my coding manager turns lessons learned into steady skill gains—all while I focus on higher-leverage product management work.

    If you’re considering a similar setup, start with a single agent and a narrow task, then expand. Keep identities crisp, scripts small, and schedules explicit. With that foundation, you’ll get the benefits of automation and delegation—without surrendering control.


    Inspired by this post on Product Talk.


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  • Stop Obsessing Over the Roadmap: The High-Impact CPO Playbook for Ambition, AI, and Focus

    Stop Obsessing Over the Roadmap: The High-Impact CPO Playbook for Ambition, AI, and Focus

    I used to treat the roadmap like a sacred artifact. Over time, I learned the uncomfortable truth: the best product leaders stop obsessing over the roadmap and start obsessing over ambition. My number one job isn’t shipping features—it’s raising the bar for what the team believes is possible and carving out the time to think deeply. When I spend half my time thinking (not doing), the business moves faster, customers feel the lift, and outcomes finally outpace output. The impact of a great product leader starts with context-setting. Under a founder, the role often skews toward influence without deference—pressure-testing ideas, bringing data and customer insight, and helping translate founder vision into a portfolio and product strategy. Under a hired CEO, it’s about aligning capital allocation, setting clear investment theses, and ensuring product roadmapping and sprint planning connect directly to financial and go-to-market realities. Ambition beats activity. I push teams beyond “what we can fit this quarter” and anchor on value creation: how does this create net-new customer advantage? We measure with outcomes vs output OKRs, tie initiatives to activation, retention, and Net Recurring Revenue (NRR), and celebrate learning velocity as much as shipping velocity. When the narrative moves from features to outcomes, customers notice—and so does the business. I’m demanding without breeding fear. The trick is a high bar plus psychological safety: crisp quality standards, blameless postmortems, and an expectation of intellectual honesty. I separate people from problems, model curiosity over certainty, and use stakeholder management to align early, not late. The result is a culture where empowered product teams volunteer for the hard problems because the path to excellence is transparent. Most “politics” is an incentives problem. When functions optimize for different scorecards, status games fill the vacuum. I fix this with a shared driver tree, clarified decision rights, and compensation aligned to company-wide outcomes. Once incentives match the strategy, alignment stops being a meeting and starts being momentum. I use a three-bucket framework to delegate decisions. Bucket 1: I decide (irreversible, cross-company implications, or existential risk). Bucket 2: Team decides; I’m consulted (reversible or scoped risk with clear guardrails). Bucket 3: Team decides; I’m informed (local optimization and execution details). This creates speed without surrendering strategic coherence, and it’s a practical approach to building empowered product teams. I’m militant with my calendar to protect thinking time. I block two to three mornings per week for deep work, partner with executive assistants to defend those blocks, and aggressively prune low-ROI rituals. “Thinking time” isn’t a luxury; it’s where product strategy is forged, complex bets are sequenced, and product-market signals get synthesized. I also fly at a low altitude—joining customer calls, reviewing designs and PRDs weekly—so judgment stays grounded without micromanaging. The AI era demands more risk in our roadmaps. I place a few venture-like bets, timebox them, and instrument eval-driven development so we can kill or scale quickly. The concept of an app is changing—from static screens to adaptive workflows, assistants, and agentic AI. This shifts product roadmapping and sprint planning toward capabilities, data leverage, and safety systems (privacy-by-design, data governance, and AI risk management) rather than a linear feature list. Innovation teams need shelter from the core. I separate their KPIs from immediate monetization, create technical sandboxes with clear guardrails, and run a parallel discovery track. Forward deployed engineers sit with customers; continuous discovery ensures we converge on problems worth solving; and when something works, we integrate it into the core without smothering it with legacy processes. I use a barbell planning horizon: 12 weeks of executional clarity and 12–24 months of strategic theses. Anything beyond that is scenario planning, not a promise. We revisit the theses quarterly, tie them to product strategy and go-to-market strategy, and ensure each increment is measurable. This balances focus with optionality. Excellence in 2026 looks different. It requires fluency in AI Strategy, strong data governance, and the ability to move from feature leadership to system leadership. Product leaders must be bilingual—equally comfortable discussing LLMs and retrieval-first pipelines as they are speaking in NRR, gross margin, and payback periods. The job is to translate technology shifts into durable customer advantage. Being a great C-suite partner means acting enterprise-first. I co-own capital allocation with finance, sequence hiring with people and engineering, and encode our strategy into operating cadence. I treat sales-led growth and product-led growth as complementary systems, not rival religions, and I bring clarity to trade-offs with driver trees and scenario plans. Chase impact, not titles. The fastest growth I’ve seen comes from optimizing for scope, learning rate, and mentors—not for role labels. If you want comp and career to compound, maximize the value you create: fix activation, improve retention, unlock expansion, or reduce cost-to-serve. Titles follow impact, not the other way around. Four bottlenecks stall careers repeatedly. First, a scope ceiling—holding too much IC work and not scaling through delegation. Second, stakeholder friction—underinvesting in alignment and communication. Third, weak people leadership—not hiring, coaching, and performance-managing decisively. Fourth, fuzzy strategy—if your strategy can’t be drawn as a driver tree, your teams can’t execute it. Remove these bottlenecks and your trajectory changes fast. In the end, the roadmap is an instrument, not the strategy. Raise the team’s ambition, align incentives, protect deep work, and take smarter AI-informed risks. Do that consistently and the roadmap stops being a crutch—it becomes a flywheel.
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  • Build a Support System That Scales: How Product Leaders Maximize Impact with Delegation and AI

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

    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.


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