Devin Skolnick

Execution capacity used to scale with headcount. Throw more people at the problem, get more done. That math has changed. A small team with strong AI orchestration skills will outpace a large team without them. Every time. The new constraint is finding the right people. That's the bottleneck now.

18

4 Comments

How confident are you in your roadmap this year? Are you playing it safe, or taking real swings at opportunities that could change your product’s trajectory? Today's insight on The PM Brief, featuring John Cutler, hits this tension perfectly. He reminds us that prioritization isn’t just about how confident we feel right now. It’s about how quickly we can learn, reduce risk, and collapse uncertainty early. This is just one of many strong insights in John’s article. All 10 prioritization traps are worth a read if you’re rethinking how you plan and prioritize heading into 2026. #ProductManagement #AI #Prioritization

19

2 Comments

Ever wonder what product teams are doing all day?? 🤔 ...Here's a great visual of The Struggle from Ed Biden! My thoughts 👇 I would also expand on the importance of the upfront Ideation and Prioritization phases. Without the right amount of rigor here (read 'analytics, insight sources, biz metric alignment') you will have a lot of wasted cycles and quickly lose trust & velocity from downstream dev teams. Also very cool to note that THIS IS A CIRCULAR, REPEATING CYCLE of continuous learning and iteration from both your winners and losers (post go-live). Cheers 🥂 #ProductManagement #ProductStrategy #ProductDevelopment #Agile #ContinuousImprovement #Leadership

17

A Question I Ask Before Any Launch: “What happens if this works too well?” It sounds like a good problem—but it’s how you uncover: - Capacity issues - Support gaps - Operational debt Every launch plan needs a success plan

11

✍️ New essay published: Playing the headcount accordion As product leaders - how do we navigate the tension between a desire to run faster/harder with smaller teams, with the realities that nudge us to keep growing our staffing? Today's essay explores that tension - and introduces a new, superior approach - playing the accordion. 🔗 Link in reply 👇

8

2 Comments

✔️Clients don’t want your flashy AI tools. They want data that backs your performance. In the latest episode of Between the Briefs, we explore how this translates into the world of legal amidst an industry-wide tech revolution. Tune in as Ashley Gibbs, Senior Director of Product Value, Engineers and Solution Sales Executives at Litera joins Adrian Cea and Joe Stephens for a candid conversation on why data quality makes or breaks AI success and is critical to drive positive change in tech adoption. Spotify: https://bit.ly/4gCOQ02 Apple: https://apple.co/47WBTfn YouTube: https://lnkd.in/gHjcNV8W #thestenostory #technologyinlaw #betweenthebriefs

2

I was CPO at Blend before their $4 billion IPO. We rejected the “forward deployed engineer” Palantir model that everyone is copying now. Here’s why: Blend could have followed the forward-deployed engineer approach. Both our CEO and CTO were early Palantir. They'd seen it work. Instead, we built a SaaS product with core components. Move fast, iterate, use data to learn. Not custom code for every client. That Palantir model is having a resurgence. Now Sierra, Decagon, and others are hiring forward-deployed engineers. But it’s not the right approach for every company. It’s fundamentally the wrong answer for Assembled’s customers. Here's what we understand about support teams and why we’re not going the forward deployed route: Customer Support teams are used to getting no resources and no support. On the surface, you'd think they'd be excited about engineers building custom solutions. "Finally, someone's offering us developers!" The reality is support teams are terrified of getting help they can't afford to keep. Support teams are wary because they know the math. They don't have budget for expensive, scarce resources. At some point the shoe drops. The engineers disappear when priorities shift. And custom solutions break. Support is left holding the bag with something they can't maintain. They're resource-starved by design. The idea of a dependency on resources they can't control is terrifying. So instead, the goal should be to give support teams the ability to manage, change, and solve their own problems. Not dependencies on engineers they can't keep. Smart, competent people who teach them to do it themselves. Palantir wasn't even a product company for years. They were a custom development shop with reusable components. Show up, build something bespoke, maybe extract learnings. That's not scalable for any but the largest support teams who need sustainability. Forward-deployed engineers are the new shiny object. I wasn’t a fan of it at Blend. And I’m not a fan today either. What I see in the customer support space is that teams need empowerment, not dependency. I want the teams we work with to be able to say: "I love that you’re partnering with me. And I love that I can do this myself too." That's the difference between building a product and building a consulting practice.

80

6 Comments

Invested in AI but still not seeing the payoff? That’s what happens when your AI tools don’t work together. ServiceNow breaks down the walls—connecting every AI, workflow, and data source—so your team can put AI to work and actually see the returns.

1

For years, commerce systems quietly relied on humans as the execution layer. Humans reconciled inconsistent pricing, interpreted ambiguous policies and smoothed over failures between systems that didn’t quite agree. When execution shifts from humans to systems, commerce stops being forgiving. Ambiguity becomes a liability. Policies have to be executable, not just defensible. Ownership has to be explicit. Execution paths have to be deterministic. This is why the Universal Commerce Protocol (UCP) matters—but not in the way it’s often discussed. UCP isn’t a product, an API, or a shortcut to AI-driven shopping. It’s a reflection of a deeper shift: execution is moving away from interfaces and toward capabilities. Here's a study that looks at UCP from that structural angle: a. why AI interfaces alone can’t safely scale commerce b. why execution (not intelligence) is the real bottleneck c. what breaks inside organizations when humans stop being the glue and d. why protocols only matter once execution maturity exists It’s an attempt to reason about why a protocol like UCP had to exist now and what it exposes about how we have been building commerce systems for the last two decades. Sharing the piece here: https://lnkd.in/gybyffFG

1

“AI is rewriting product leadership—skills over roles, taste as your moat, and fundamentals that still win.” Great insights from Julie Zhuo and Aakash Gupta

1

In the fast-paced world of product development, acceptance criteria are often the unsung heroes ensuring product success. Detailed and clear acceptance criteria can bridge the gap between vision and execution. Acceptance criteria aren't just a checklist, they’re the guardrails that align teams and stakeholders, ensuring everyone speaks the same language. This alignment is critical; according to a recent survey by PMI, projects with well-defined requirements and acceptance criteria are 2.5 times more likely to succeed. But how do we craft these criteria effectively? Here are three insights from my experience: 1. Clarity and Precision: Ensure each criterion is specific and measurable. Vague criteria lead to misunderstandings and scope creep. How do you ensure precision in your criteria? 2. Collaborative Creation: Involve cross-functional teams in drafting the criteria. Diverse perspectives can highlight potential oversights. Have you found collaboration to improve your product outcomes? 3. Continuous Iteration: Acceptance criteria should evolve with the product. Regular reviews can adapt them to changing market needs or customer feedback. How often do you revisit your acceptance criteria? Ultimately, strong acceptance criteria are not just about defining "done" but about defining "done right." As we continue to innovate, how do you see acceptance criteria evolving in your industry? #ProductDevelopment #ProjectManagement #AcceptanceCriteria #Innovation #ProductSuccess

1

Investors take note. The Sass-pocalypse is overly sold off. Innovation and AI adoption will look like this going forward. Time tested platform and capablities, like Intuit, combined with agentic orchestration. Both pieces create the big wins for customers.

12