The Way of Product with Caden Damiano

Caden Damiano
  • 3.8 (6)
  • TECHNOLOGY

The Way of Product is your graduate school focused on developing a taste for what “great products” look like. Conversations are two professionals talking shop about positioning, segmentation, excellent product design, and most importantly, taste. www.wayofproduct.com

  1. 3D AGO

    #166 Maxine Anderson, Co-founder & CPO at Arist: Iterate Positioning Relentlessly and Ship What the Market Needs

    Maxine Anderson is the Co-founder and Chief Product Officer at Arist, where she helps build what is widely regarded as an emerging default enablement system for large enterprises. Rising to prominence in the early 2020s, she became known for transforming text-message learning experiments into an agentic enablement platform that operates directly inside Slack, Microsoft Teams, and SMS. Under her product leadership, Arist has evolved from simple SMS-based courses to an AI-driven “enablement team in your pocket” that automates needs analysis, content creation, and delivery for distributed workforces at scale. Previously, as Co-founder and Chief Product Officer at Arist, Anderson helped expand the company’s initial seed funding to $3.9 million in 2021 and later raise a $12 million Series A round to fuel rapid enterprise adoption. Her work turned an early Y Combinator-backed idea into a venture serving over 20 Fortune 500 organizations, with pricing starting around $1,000 per month for enterprise deployments. She became known for shipping AI-powered tools such as Creator and the Enablement Agent, which process thousands of complex documents, translate into 100+ languages, and generate ready-to-deliver programs in under eight minutes while proving impact through end-to-end analytics. Her career highlights include co-founding Project W, a student-led organization launched in 2021 to foster interdisciplinary collaboration among women innovators and entrepreneurs across the Babson, Olin, and Wellesley (BOW) colleges, which built an online community of more than 300 members and incubated Project Pods for high-level ventures. As a founding member of College Ventures Network and VP of Marketing at eTower, Babson’s premier entrepreneurial living community whose alumni companies have generated more than $3 billion in combined valuations and over $50 million in funding, she honed a model for building tight-knit entrepreneurial ecosystems. Graduating magna cum laude from Babson College in 2022 with a focus on entrepreneurship, she combined academic honors with hands-on leadership roles that emphasized measurable impact and community scale. Outside of her primary operating role, Anderson serves as a Board Member at Delphian School, bringing startup execution and product thinking back into the education system where she was once Student Council President and a three-time state champion cheerleading captain. Through ongoing advisory work and public writing on enablement, AI agents, and performance diagnostics, she has become an influential figure for operators building the next generation of enterprise learning and HR technology. Listen to this episode on Spotify or Apple Podcasts How Arist navigated seven years of positioning iteration in an undefined category and why shared conviction about the game you’re playing gives product the agency to say no. “We are a new category without ever having created or yet created a category, which is hard to sell,” Maxine Anderson says. There’s no frustration in it. Just the accumulated weight of seven years spent explaining something that doesn’t have a name. Maxine is the co-founder and CPO of Arist, a platform that delivers employee training through Microsoft Teams, SMS, and WhatsApp instead of video-based learning management systems. She started the company at Babson College with two co-founders after they each independently discovered that text-based communication drove behavior change in ways traditional mediums couldn’t. The student in Yemen who could only learn via text. The public speaking coach who sent WhatsApp reminders before talks. Maxine’s own financial literacy programs on Native American reservations where classroom formats failed completely. The insight was simple. The seven years that followed were not. I ask her about positioning, and the answer is a catalog of pivots. They started as a consumer marketplace—Masterclass over text, basically. Learn from professors at Harvard via your phone. “That model was just really hard to distribute,” she says. “Marketplaces are just really difficult, to be honest. Not really good for a medium that people didn’t already believe in.” A former chief learning officer told them about the billions spent on corporate training that drove zero results. They pivoted to corporate learning. Spent two years selling to HR. Got traction—then the market shifted. Enterprise budgets contracted in 2021 and 2022, and HR was the first department cut. “It was kind of a forcing function for us to find a better buyer,” Maxine says. They started selling to operational leaders. Sales directors. Frontline manufacturing managers. People whose bonuses depended on whether their teams improved. The product hadn’t changed much. The positioning had changed completely. I tell Maxine this is the part of product strategy that I think most product leaders miss. It isn’t about filling up a backlog and deciding which features will close deals. It’s figuring out what game you’re playing. There’s a great piece—I think it’s an a16z blog—about how the market is the most important thing. You can change your positioning and your target segment and sales go up. You don’t have to add more features. “Yeah,” she says. “We’ve had to iterate on our positioning a lot.” She describes what it’s like to sell without a category. Not just positioning on a macro level—telling the market a new way of thinking about employee enablement—but positioning per account. Every conversation is a custom pitch. Every buyer needs to understand something that doesn’t map to any existing line item in their budget. “For a while it was hard to lead product,” she admits. “We’re selling all these different use cases yet we don’t want to productize those pathways. We’re not a sales enablement tool. We’re not trying to compete with HighSpot directly. We’re really good for this part of sales enablement, this problem that’s not solved.” I bring up Figma as a parallel. How long it took for Figma to convince designers to switch from their existing tools. How category change requires not just a better product but a change in default behavior. “It did take a long time for Figma to get traction,” she agrees. “They had to change people from their default behavior of going to other tools as a solution.” The conversation moves to roadmap, and Maxine lights up. “There’s this quote that I love,” she says. “Plans are useless, but planning is useful. And I feel like that’s really true in a startup.” She describes the trap she sees product managers fall into: optimizing for delivery. Presenting a roadmap, hitting dates, feeling the satisfaction of shipping what you said you’d ship. She says the feeling of executing on a plan is seductive—and often wrong. “A roadmap often becomes a ton of things people ask for instead of what you’re trying to build towards over time,” she says. “Some of our best features have been where it doesn’t feel good. We shipped this a little too early, or we shipped this to see if we could market it. Or we marketed this five months early and built it in a funny way.” This is the part where most product conversations would veer into framework territory. Maxine stays concrete. She describes how she segments her roadmap into three buckets: what they’re working towards building, what they’re trying to build to convince people, and what they’re building because it’s literally blocking adoption at scale. “Those are the customer requests I take,” she says. “Literally, we would have five times volume if we shipped this feature. Not—oh, I would really love it if you could add this to a course.” She confesses they fell into the feature parity trap early. Customers would compare Arist to existing LMS products. The team spent six months adding features that mapped to what learning management systems already had—instead of building the fundamentally different thing they were supposed to be building. “What we’re building is fundamentally so different,” she says. “I have the agency in meetings with executives to say—that’s actually not our perspective. This is what we’re trying to build. This is what enablement should look like in five years, trust us. And it makes them back off a little bit.” That agency comes from conviction. Not confidence—conviction. Knowing what game you’re playing well enough to explain why certain features will never be built. Maxine tells me she spent significant time enabling the entire company on Arist’s vision. Not just the product team. Everyone. So that when a salesperson gets a feature request in the field, they can explain why Arist won’t build a one-on-one coaching product, and here’s why, and they will never build that, and here’s why. “Them being able to say those things is super valuable,” she says. “Because then you don’t get all these incoming requests of product to manage.” I ask whether finding the right buyer helped with breathing room for product. “Market is everything for product,” she says. Four words. No hedging. Finding the right buyer improved retention, simplified the roadmap, reduced internal pressure. It did what no process improvement or planning framework ever could: it gave product permission to build the right thing. Her co-founder, she tells me, is the one who holds the macro stance. “It’s very easy in a business to just really want the wins and explain things in ways people understand,” she says. “It takes a lot of positioning iteration to stick to the macro.” She mentions other companies in adjacent spaces that built text-message learning tools but positioned them as utilities for learning designers. They don’t see that learning designers won’t exist in their current form three years from now. They’re solving for today’s buyer in today’s category.

    54 min

  2. 6D AGO

    #165 Richard Yu, CPO at LucidLink: Build Products That Disappear, Navigate High-Integrity Commitments, and Treat Strategy as a Hypothesis

    Richard Yu is the Chief Product Officer at LucidLink, where he leads product strategy for the company’s cloud-native file system used by distributed creative and enterprise teams worldwide. Rising to prominence in the 2010s as an enterprise SaaS product leader, he became known for building mission-critical platforms that turn complex workflows into scalable, repeatable systems. He is widely regarded for his focus on outcomes over output, pushing organizations to measure success by customer impact rather than feature volume. Previously, as Chief Product Officer at Formstack, he oversaw a no-code workplace productivity platform adopted by over 35,000 organizations across healthcare, financial services, and education. Under his leadership from 2022 to 2024, the company expanded its automation footprint across forms, documents, and e-signature workflows, helping customers digitize key processes end to end. He became known for driving cross-functional execution between product, marketing, and go-to-market teams to accelerate subscription growth and retention. His career highlights include serving as Senior Vice President of Product at Litmus, where he led a four-year stretch of category leadership that earned multiple G2 and TrustRadius awards for product adoption and customer satisfaction. Earlier, as Vice President of Product Management and Head of Product Management and User Experience at Marketo, he guided one of the world’s largest marketing automation platforms through a period when thousands of B2B organizations relied on it to orchestrate multi-channel campaigns. Across these roles, he has spent more than 25 years building teams, products, and businesses at the intersection of SaaS infrastructure, marketing technology, and data-driven customer engagement. Listen to the full conversation on Spotify Listen on Apple Podcasts Learn how LucidLink’s “invisible product” design philosophy connects to Marty Cagan’s high-integrity commitments framework and why the best product strategies are testable assumptions, not finished artifacts. “We have users who experience it for the first time and kind of call it magic,” Rich Yu tells me. “So it is a bit magical, but obviously there’s no magic in technology. It’s just technology.” He says this with the calm of someone who’s heard the word magic a hundred times from customers and has learned to take it as engineering validation rather than compliment. Rich is the Chief Product Officer at LucidLink, and his product makes cloud-stored video files act as if they’re sitting on your local machine. You open your Finder, there’s a mount point, and the files are just there. Editors on The Bear scrub through footage with zero latency. No syncing. No downloading. No waiting. The company just won a technical achievement Emmy for this. And Rich’s philosophy for what comes next is to make the whole thing vanish. Richard Yu has spent 25 years in product and marketing leadership—Formstack, Litmus, Marketo—before landing at LucidLink, a cloud storage collaboration platform headquartered in San Francisco with an engineering office in Sofia, Bulgaria. The company powers post-production workflows for major streaming shows and found its product-market fit during COVID, when media teams went home and discovered that collaborating on large files remotely was, in Rich’s words, “just not tenable.” LucidLink solved that with streaming technology that caches intelligently enough to make remote files behave locally. The result is a product whose ideal user experience is one you don’t notice. I ask Rich what “it just works” actually looks like from the inside—because from a product design perspective, aspiring to be invisible is a strange thing. We spend our careers building interfaces, flows, and experiences that demand attention. Rich is trying to do the opposite. “We’ve really aspired to become invisible almost in the user experience,” he says. “I know that sounds ironic because as creators and builders of products, we always talk about what’s the user experience and what’s the UI look like.” He holds the irony for a beat. “But ultimately, if we’re thinking about the core value proposition—making large files stored in the cloud act and behave as if they were local on your machine—that’s something that should just happen.” I tell him about the declining weekly active users problem. A previous guest worked on translation software and discovered that as the product got smarter, people used the app less. For most teams, that graph is a crisis. For utility products, it’s proof of success. “Exactly,” Rich says. He gets it immediately. For LucidLink, the dashboard exists so administrators can manage permissions and check billing. But the actual value—the streaming, the speed, the absence of friction—that lives underneath everything. The best interaction is the one where a user opens a file, does their work, and never once thinks about the infrastructure making it possible. We drift into strategy, and Rich surfaces the question that shapes how he approaches product decisions: Are we building outcomes, or are we building outputs? He’s careful to credit the framework to others—”folks have blazed the path before me”—but the way he deploys it reveals conviction earned through experience. Early-stage companies need outputs. You need to ship the MVP, get it into market, learn. That’s the job. But once you have adoption and momentum, the game changes. “The value is what is typically called the outcomes,” he says. “Are users really using your product? Are they happy? Is there a community that’s excited and engaged? And then ultimately those outcomes are also company or business outcomes. Is the company growing and successful as a result of the customers being successful?” This connects to something else Rich is thinking about: the danger of high-integrity commitments. I bring up Marty Cagan’s framework—the idea that product teams should avoid locking into hard delivery dates unless the situation is truly existential. We’re going to lose this customer if we don’t ship. The business is under threat. Those are the only moments where committing to a specific scope by a specific date makes sense. Rich admits he falls into the trap himself. “As a product leader, I have accountability to my peers, to my executives, to kind of say, okay, we are gonna ship X by Y date,” he says. “I mean, that’s sort of one of the key anti-patterns in a way—that we are trying to constantly hit very specific dates with projects and initiatives that are not deterministic in that way.” He catches himself. “But I fall into that sort of trap myself because, let’s face it, in the business world, if we don’t have some forcing functions to get things done, work can fill up the space that it’s given.” The nuance matters. Deadlines aren’t inherently destructive. The anti-pattern is when hitting the date becomes the only thing you’re striving toward. When shipping replaces thinking. When the forcing function forces shortcuts in discovery, in design, in engineering. “It forces maybe shortcuts to be taken in the discovery and exploration and validation of that threat,” Rich says. “And then shortcuts taken in terms of the design and the actual engineering of the solution against the threat.” I push further: when you do make a high-integrity commitment, you need a team that believes in it. Not just one that executes against it, but one that owns it. “That’s where breaking down the silos across the three functions to creating this true triad ownership is critical,” Rich says. “The ownership in that high-integrity commitment is not engineering by themselves. It’s not design by themselves. It’s not product by themselves. It’s really all three.” The conversation turns to strategy and Rich offers what might be the most honest thing a product leader has said to me in 165 episodes of this podcast. “Any strategy, no matter how polished or how baked or how succinctly articulated—they’re just a set of assumptions and hypotheses,” he says. “Hopefully backed by sufficient data and research. But ultimately it’s a thesis. It’s a thesis until you’ve actually achieved the outcome that the strategy is trying to point towards.” I’ve watched the anti-pattern play out in real time. A product leader presents a strategy. The team pushes back. Instead of engaging, the leader hedges: Well, it was more of a thesis. A work in progress. They were hedging to save face. But Rich is saying something different—he’s saying all strategy is thesis, and that’s not a weakness. It’s how the work actually gets done. “I’ll go on a limb that even the smartest strategists out there, the most successful folks in technology, are probably always just running one or two steps ahead of reality,” he says. “And they’re trying to really figure things out.” He reaches for the scientific method. Hypothesize. Test. Verify. Iterate. It sounds basic—cliché, even. But his point is that the discomfort most product leaders have with strategy isn’t that they’re doing it wrong. It’s that they haven’t accepted the nature of the work. Strategy is a hypothesis you test with product decisions. The roadmap is the experiment. The outcomes are the data. “I really believe that strategy is formed in that cauldron,” he says. “Product roadmaps are formed in that cauldron. And great products are built using that sort of scientific method.” There’s one more thing Rich keeps circling back to, and it might be the connective tissue between the invisible product and the hypothetical strategy. He describes how his teams do quarterly reviews to examine the assumptions they made when deciding to prioritize, build, and ship specific features. Did we achieve the user outcomes we assumed? Did those outcomes l

    52 min

  3. MAR 19

    #164 Chris Silvestri—AI Produces Great Stuff, If You Have a Process.

    Chris Silvestri is the Founder at Conversion Alchemy, where he helps B2B SaaS teams engineer message–market fit across web, sales, and email. Rising to prominence in the early 2020s, he became known for combining deep customer research, UX thinking, and decision-making psychology into scalable messaging systems that lift conversions rather than isolated campaigns. His work positions him as a widely regarded specialist for post–Series A SaaS companies seeking clarity, differentiation, and measurable revenue impact. Previously, as Founder & Conversion Copywriter at Conversion Alchemy, he led projects that generated up to 30% more qualified demo requests by clarifying value propositions and sharpening differentiation on 20+ core website pages and sales assets. He became known for shortening sales cycles by an estimated 15–20% by making value obvious earlier in the buyer journey and aligning messaging with actual customer priorities. His systems consistently drove 10–15% lifts in trial-to-paid conversions while improving internal alignment across marketing, sales, and leadership. His career highlights include serving as Conversion Rate Optimizer and UX Designer at Zeda Labs LLC from 2018 to 2021, where he blended qualitative research and experimentation to improve funnel performance and user experience over 2.5+ years. Earlier, he spent nearly a decade in engineering and industrial automation, experience that shaped his systematic approach to messaging, process design, and experimentation. Since 2020 he has also contributed to Good Product Club, writing on product strategy, UX, and go-to-market for teams building in an AI-driven world. As host of the Message-Market Fit Podcast, he helps B2B SaaS leaders understand how to translate customer insight into narratives that win deals and defend pricing power. Through his Unpacking Meaning newsletter, he publishes weekly breakdowns of SaaS messaging, UX, and buyer psychology for an audience of founders, CMOs, and growth leaders. Listen to this episode on Spotify or Apple Podcasts What a software engineer turned copywriter learned about positioning—and why 70% of the work happens before you write a single word. “If you don’t have a process, AI is gonna produce crap,” Chris tells me. “If you have a process, AI is gonna produce good stuff.” He says it like it’s obvious. Like the whole discourse around AI and creative work has been missing the point. Chris Silvestri spent ten years as a software engineer in industrial automation in Italy before transitioning to copywriting. He moved to the UK, founded Conversion Alchemy, and now helps B2B SaaS companies find message-market fit. He writes for Every. He’s not worried about being replaced by AI. But he has thoughts about who should be. I ask him to break down what he means by process. “First do the research,” he says. “Then don’t feed all the research to AI and have it write—or sometimes they don’t even feed the research and just ask it to write, which is even worse.” He pauses to let that land. “Use the research, distill it into your strategy, and then use the strategy as context for the LLM. So they can actually make sense of the data better.” This is the part most people skip. They dump raw transcripts and survey results into ChatGPT and expect positioning to emerge. But the synthesis—the actual thinking about what the research means—that’s human work. The AI can help you write after you’ve decided what to say. “Seventy percent of the work to me is research,” Chris says. “And then the messaging and the copy almost write itself.” I stop him. I want to make sure I understand the claim. He’s saying the writing is almost incidental? He nods. The hard part is everything that comes before. Chris’s engineering background shows up here. He sees messaging as a system with distinct layers. Positioning defines who you are. Messaging is how you articulate that across contexts—sales calls, landing pages, email sequences. Copy is the final layer, the actual words. Most people try to fix copy when the real problem is upstream. No amount of AI-generated headlines will save you if nobody agreed on what you’re saying in the first place. “A lot of times different departments don’t really agree on what they do better or differently,” he says. “And so then everyone starts kind of saying different things.” The jargon-stuffed copy that plague B2B websites? That’s not a writing problem. It’s an alignment problem. I ask about how he approaches customer research when the data is thin. Early-stage companies often don’t have enough customers to build detailed personas. “I think it’s useful to start with an archetype of your customers,” he says, “rather than saying, okay, this is a specific persona.” He explains the distinction. An archetype is a representative of a group—business buyer versus technical buyer. Under the business buyer archetype, you might eventually differentiate between CMO, CFO, and procurement. Under technical buyer: CTO, data engineers, developers. But if you’re early, you don’t have the data to specify that precisely yet. “We weren’t clear,” he says, describing a recent project with a data integration company. “So instead of crafting these ideal customer personas, we drafted these early customer personas. Business side, technical side. And from there we could move forward and get more specific.” Personas come later, when you have crystal-clear data on psychographics, demographics, decision-making patterns. Archetypes let you start building without pretending to know more than you do. This matters for AI workflows too. If you’re prompting an LLM to write for a persona you’ve fabricated from guesswork, the output will feel hollow. But if you’ve done the research—if you’ve actually talked to customers and heard how they describe their problems—you can give the AI context it can work with. “The more you compartmentalize your tasks in LLMs, the better it works,” Chris says. “I don’t even use ChatGPT or Claude for writing directly. There are loads of third-party tools that let you plug into the APIs without that pre-training those commercial interfaces have.” He’s building his own stack. One tool for finding signal. Another for working through strategy. A third for writing with his editorial style guide. Each chat stays focused. The synthesis happens in his head, not in the model. Near the end of our conversation, I ask what led him to embrace AI when so many writers are defensive about it. “I think first it was actually feelings of never being good enough,” he says. Something shifts in his voice. “Maybe it stems from the fact that I’m a non-native English writer. I’ve always said, what if I could be better? And then I saw AI, and now the playing field is level for anyone.” He decided to try every tool he could find. Learn what actually works. Keep up with the changes happening every week. But what he discovered surprised him. “Once you have a very specific and systematic process, AI can only amplify that.” The people most equipped to leverage AI are the ones who invested in their own brains before these tools existed. They have vocabulary. They have frameworks. They know what good looks like. Chris writes for Every now. He mentions how working with their editors makes him see things from a different perspective. The writer has one job. The editor has another. You try to mirror that same workflow when working with AI. “The craft, the taste,” he says. “That just makes you better and amplifies your ability to do more with AI.” I’ve been thinking about this since we hung up. The fear around AI in creative work is often misplaced. The tools don’t threaten people with strong processes—they expose people without them. Seventy percent is research. The rest is finding the right combination of insights, framing, and context. If you’ve done that work, AI is just another tool in the kit. If you haven’t, it’s a mirror. The Way of Product w/ Caden Damiano is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to The Way of Product w/ Caden Damiano at www.wayofproduct.com/subscribe

    51 min

  4. MAR 16

    #163: Mustafa Kapadia—You're Gonna Need More PMs, Not Less: The Counterintuitive Future of Product Management in The Age of AI

    Mustafa Kapadia is the Managing Director at Echo Point, where he helps product organizations use AI to eliminate operational drag and compound product velocity. Rising to prominence in the 2010s at the intersection of digital transformation and DevOps, he became known for translating emerging technologies into operating models executives could actually run. Today he is widely regarded as a leading advisor to product leaders seeking to turn generative AI into durable leverage rather than surface-level experimentation. Previously, as Global Head of Products & Innovation for Generative AI at Google, he led efforts to help the company’s largest enterprise customers, representing roughly the top 20% by scale, build new products and experiences on modern cloud and AI infrastructure. In that role from 2019 to 2023, he built new global innovation labs, combined sales and P&L ownership with hands-on product advisory, and drove adoption of generative AI across complex, multi-billion-dollar portfolios. He became known for helping Fortune 500 executives move from slideware to shipped product by redesigning how cross-functional teams discovered, validated, and launched new offerings. His career highlights include a seven-year run at IBM, where he grew an internal DevOps capability 3x into a market-facing advisory practice and later led the North America Digital Transformation practice. From 2012 to 2014 he built a cloud automation service that delivered double-digit growth while helping large enterprises compress infrastructure delivery from months to days. Earlier, he served on the Board of Directors at the DevOps Institute from 2015 to 2019, shaping curriculum and thought leadership as DevOps moved from niche practice to mainstream mandate in organizations managing hundreds of applications and billions in IT spend. He also co-founded Science4Superheroes in 2014, running it for eight years to introduce scientific thinking to children under five through playful, family-centric programs. As host of the Masters Of Product podcast and author of the AI Empowered PM newsletter on Substack, he helps more than 2,000 product managers each year learn to convert AI from a curiosity into a core part of their craft. Through private workshops, public cohorts, and consulting engagements, his work routinely unlocks multi-thousand-hour annual savings per organization and resets how product teams think about judgment, speed, and quality in the AI era. Listen to episode 162 on Apple Podcasts↗ and Spotify↗ Building gets easier. Deciding what to build gets harder. Here’s how the top 1% are preparing. “I had to figure out what I wanted to be when I grow up.” Mustafa Kapadia says this quietly, almost to himself. He’s describing the moment two years ago when he left Google—after 20 years at places like IBM and Google, running accelerators, building consulting practices, watching digital transformations succeed and fail. And then he walked away to help product managers stop being terrified of the thing that might replace them. I ask him about the fear. The senior engineers and PMs who’ve told me they’re just... opting out. Done. Can’t adapt. Won’t try. “I think we have really two camps,” he says. He holds up two fingers, almost making the “peace sign”—then stops. “Well, three camps.” Camp one: the AI-first believers. They start every task with an LLM. They use ChatGPT for one thing, Claude for another, Gemini for a third, NotebookLM for synthesis. They’ve rebuilt their entire workflow around what AI can do. Camp three: the skeptics. They want AI at arm’s length. Afraid it’ll outsource their thinking. Afraid it’ll take their jobs. They’re the same people who resisted mobile phones, who pushed back against the internet, who had concerns about every new technology since the printing press. And then there’s everyone else. The 60% in the middle of the bell curve, trying to figure out which way to go. “They want to use AI,” he says of the middle camp. “But they don’t really know how. They’re doing surface-level stuff.” Surface-level. He has a phrase for this. He calls it “using a Ferrari as a paperweight.” Most PMs use AI for three or four tasks. Summarizing documents. Writing emails. Maybe a little brainstorming. They’ve been handed one of the most powerful tools ever created, and they’re using it to check boxes. The top 1% do something different. I’ve felt this myself—the gravitational pull of the easy path. Voice dictation made it so simple to just talk through everything with Claude. I found myself reaching for AI before I’d even tried to think. At some point I started looking for a “brick” for AI, the same way I use a physical lock to keep myself off my phone apps. I tell him this. Maybe I should get my notebook out first, I say. Try to get as far as I can before— He cuts me off. Not rudely. Precisely. “You’re still using AI,” he says. “It’s just a matter of how you’re using AI. Depends on your comfort level.” Some people think things through first, then use AI to refine their thinking. Others start with AI—”just give me all the options”—then choose the ones they care about, move forward with their own thinking, then use AI to refine it again. Their thought process is sandwiched between AI. I ask him if there’s a right way. “I don’t think there’s a right or wrong way,” he says. “I think the more important question is: does it help you become more creative, effective, innovative as a product manager? And if the answer is yes—then more power to you.” He has a framework. Of course he does—he’s a consultant. But when he describes it, it sounds less like a sales pitch and more like a craft. “Five keys,” he says. “Assign a role. Provide first-principle inputs. Give it instructions—best practices. Format. And then an example that ties it all together.” The example he uses is user stories. You don’t just ask AI to write them. You prime the engine. You tell it: you’re world-class at this. You give it the problem, the user, the benefit, the feature. You tell it what a good user story looks like—customer-focused, unique, technical-free. You show it one. “And then—” he pauses. “Even if AI gives you ten great user stories, you don’t take all ten.” This is where it gets interesting. “You take the one or two that resonate. You use your own PM thinking. Your own experience. Your own context.” He calls this human-AI optimization. You’re not outsourcing your thinking. You’re using AI to prime you—to surface options you might not have considered. And then you decide. The middle 60% outsource their thinking. The skeptics avoid AI entirely. The top 1% sit in the tension between—augmented, not replaced. The conversation turns to something stranger. Synthetic personas. Mustafa is working with a client who has years of market research sitting on laptops and servers. Interviews. Surveys. Behavioral data. All of it gathering dust in slide decks nobody opens. “How do you take that research and make it actionable?” he asks. “How do you give it to someone in sales, or marketing, or product?” His answer: build a synthetic user. A simulated persona trained on all that research. Something a salesperson can practice objection-handling with. Something a PM can ask, “What would you think if we priced this at $99 instead of $149?” “It doesn’t replace talking to a real user,” he clarifies. “But in those crazy questions you want to ask—it’s a great way to refine your thinking.” Then he goes further. “We have a client who’s building a synthetic competitor.” I stop him. “A what?” “A synthetic profile of their competitor. So they can think about second-order effects.” He’s more animated now. “If I drop my price, what is this competitor going to do? If I launch this feature—a feature they already have—how are the two comparing? What can they do to make my feature less valuable in the marketplace?” None of this means it’s exactly what the competition will do. But it forces you to think. To make better decisions. You can run war games now that were never possible before. I ask him about the skeptics. The 20% who won’t get on the bus. What happens to them? He doesn’t sugarcoat it. “The ship has sailed,” he says. “The train has left the station. Whatever analogy you want to use—it’s happening. The only question as a PM is: where do you want to be? In the driver’s seat? The passenger seat? Or in the caboose, being dragged?” But then his tone shifts. Softer. Almost conspiratorial. “If you’re a PM and you’re ambitious—and most PMs are, which is why I love them so much—this is the best time to differentiate yourself. Organizations are dying for PMs who can show an AI-first mindset. They just don’t know what that looks like.” He’s not selling anymore. He’s confessing. “I prefer not to talk about what good looks like. I prefer to show them. Because until you actually show someone what a good PM with AI can do—that’s when they say, ‘Okay. How fast can we move?’” One client started with four or five AI use cases. After his team helped them understand what was possible—what the top 1% actually do—they identified over 250. That’s the gap. That’s the opportunity. Near the end, he says something that surprises me. “I think you’re going to need more PMs, not less.” I must have looked skeptical. “When you can build anything,” he explains, “deciding what to build becomes a much tougher decision. Building is going to get easier and easier. But figuring out what to build, what not to build, working with the business to determine what’s actually going to make an impact—that’s the job. And I think we’re going to need more people doing it.” The order-taker PM—business decides, PM translates, engineering builds—that

    46 min

  5. MAR 12

    #162: Matt D Smith – Your AI Edge is The Vocabulary You Already Have

    Matt D. Smith is the founder of Shift Nudge, a professional interface design training platform for working designers. Rising to prominence in the 2010s for his systematic approach to visual interfaces, he became known for turning over 20 years of interface design practice into a structured curriculum used by thousands of designers worldwide. His work on design patterns and tools has made him a widely regarded figure in modern interface design education. Previously, as founder of Shift Nudge, he built a global program that helps designers advance their careers in as little as 8–12 weeks while receiving mentorship and support for a full year, equipping them to lead teams and ship production-quality interfaces. He became known for transforming working designers’ income trajectories, with students reporting income growth of 2x within a few years by applying his methods in typography, layout, and spacing. Through Shift Nudge, he has trained designers from leading startups and global brands, positioning the program as a modern alternative to traditional design education. His career highlights include pioneering the Float Label pattern in 2013, a form interaction now adopted across products from Apple, Google, and countless consumer applications. He also created the interface design tools Contrast and Flowkit, Figma plugins that have reached tens of thousands of users and are used to check color contrast and design user flows inside modern design tools. Beyond product work, he has served as an adjunct professor at the University of Georgia and delivered workshops and talks at conferences including Adobe MAX, Dribbble Hangtime, Figma’s Config, Smashing Conference, and others, extending his influence from the classroom to stages across the United States. Listen to episode 163 on Apple Podcasts↗ and Spotify↗ What a decade of design fundamentals taught me about delegating to Claude Code—and why Shift Nudge was secretly an AI onboarding course before AI existed. “I have a weird obsession with trying to get the absolute most difficult username across every platform,” Matt says, and it lands like a confession. He goes by MDS on the internet. Three letters. You can imagine the negotiations, the dead accounts, the patience required. We’re a hundred episodes into knowing each other—he was guest number 50, and now here we are past 150—and he’s still introducing himself as someone in transition. “I’m a designer turned educator now sort of turning into a CEO trying to figure out how to run a design education business.” There’s something in how he says trying to figure out that earns the pause that follows. I’ve watched Matt’s public work for almost a decade. I was the third beta tester to graduate from Shift Nudge back in 2020. I bought low, as I like to say. The course has appreciated since then, but so has something else—something I didn’t understand I was learning until AI came along. When Claude Code got good enough to actually help with design tasks, I noticed I could delegate effectively while other people couldn’t. The difference wasn’t technical skill. It was vocabulary. Every time I’d tell Claude to “adjust the row height” or “try a card component instead of a list view,” I was drawing from a library of concepts Matt had codified years earlier. Those concepts weren’t just design rules. They were the building blocks of clear instruction. The most valuable thing I learned from Shift Nudge was the vocabulary. When I became a design lead, I could articulate with precise vocabulary what wasn’t working in someone’s design. Subject, object, verb. The spacing is off for this reason. That precision made me good at delegating to humans. Now it makes me good at delegating to machines in the form of Skill files to AI agents. Matt nods slowly. “Skill files,” he says, “they’re good at getting directionally correct, especially things that are like absolutely binary. Is this the way you write an HTML link or is it not? It’s definitely right and wrong.” He pauses. “Whereas design... there’s more gray area than black and white.” Capturing the nuance a missed in my observation. He’s talking about Claude’s skill files—those markdown documents that give AI context about how you want things done. And he’s right that they work best for the binary stuff. But here’s the connection he helped me articulate: skill files are functionally identical to the Standard Operating Procedures you’d write for a junior designer. I bring up The Defiant Ones, the documentary about Dr. Dre and Jimmy Iovine. When Jimmy was learning to be a record producer, his mentor taught him by working through him. “Adjust the reverb. What happened there? Why did that work? Why did that not work?” It’s the master-apprentice model, I say. And I think that’s where things are going with AI. Matt leans into it. “You still need that institutional knowledge, the vocabulary. AI can adjust the reverb and adjust the echo and adjust the panning. Oh, you want five different beats? But it’s like—why? How much? When do we stop?” He lets the questions hang. “That creativity... I think there’s gonna be, you know, in the same way that there was a big resurgence of live in-person things after COVID—I think we’re all gonna be like, it’s just refreshing when I read something online and I can tell that a human wrote it.” There’s something in his voice when he says refreshing. Like he’s already tired of the alternative. I ask about the divergence he sees coming—who wins, who loses. He doesn’t hesitate. “There’s gonna be a divergence where the person who doesn’t use AI is just simply not as effective as the person who learned how to use it. But then there’s also gonna be a divergence of—I’m using AI all the time and this other person is like, well, I learned a lot of things before AI existed and I use AI and now I know more than you.” He pauses. “And this other person’s just fully reliant on AI and they don’t know much.” It’s gonna be harder to learn things, he says, because AI is so instant. “It makes it like painful to sit down and read something and actually learn it yourself.” The irony is that the people most equipped to leverage AI are the ones who invested in their own brains before these tools existed. Matt has a framework for mapping where you fit in all this. He calls it Pioneer, Builder, Consumer. Pioneers are the people at Anthropic and Cursor and OpenAI—building the intelligence and the harnesses that give it to us. Builders are the developers and designers using these tools to create products. “We’re sort of converging slowly,” he says. “Designers are over here and developers over here, and some are still better at infrastructure and setup and code—like, oh, that’s why would you use useEffect here in React—and designers over here like, what does that mean? But it’s starting to be irrelevant because some of the tools are getting so good.” And Consumers? “My mom is a good example,” he says. “She’s not choosing to have AI in her life. She’s just seeing it happen through Amazon review summaries or Google AI summaries for the things that she used to search for.” The question isn’t whether AI will touch your life. It’s which persona you want to occupy. I push on the vibe-coding hype. All those people on Twitter saying software is cooked because they built a Facebook clone in five minutes. “I don’t wanna rely on your janky vibe coded app to help me,” Matt says, and there’s a dry humor in it. I have a follow-up I’ve started using. Whenever someone says “I did this with AI”, I ask: Cool. So what’s your plan to maintain it? They never have an answer. That’s when you realize why we pay engineers. DevOps, infrastructure, support tickets—that’s the unglamorous work that keeps the train running. Building something on your own is a lot different than supporting a hundred thousand users at once. Near the end, Matt gets reflective about advice. “You’re gonna need your own knowledge,” he says. “Build that vocabulary through any means possible. Whether it’s asking questions from AI while you’re learning, or watching videos, or attending school. I think there’s still real value in you building your own brain.” He catches himself. “And if you don’t want to do it—you know, maybe you change careers. I don’t know.” Something shifts. The pragmatism cuts through. “Just kind of plot yourself,” he says. “Are you a pioneer? Are you gonna be a builder? Are you just gonna be a consumer? Because either way, AI is gonna be touching a part of your life, whether you choose to or not.” I’ve been thinking about this since we talked. I’m reading books again—not AI books, the fire hose has enough of those. I’m building vocabulary in domains outside tech: marketing, strategy, positioning. The cost of building has collapsed. The cost of deciding what to build has not. Everyone with taste is not in tech right now. It’s in the humanities, philosophy, long-form content. That’s where I’m looking. The Way of Product w/ Caden Damiano is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to The Way of Product w/ Caden Damiano at www.wayofproduct.com/subscribe

    53 min

  6. MAR 9

    #161: Steph Cartwright: AI Reads Context, Not Keywords—and That Changes Everything About Your Job Search

    Steph Cartwright is a Job Search Strategist and Certified Professional Resume Writer (CPRW) at Off The Clock Resumes LLC, where she helps tech and industry leaders present as confident, high‑value candidates on screen. She became known for career branding that turns complex experience into clear, employer‑ready narratives that consistently convert views into interviews. She has built an audience of more than 3,200 followers and over 500 direct connections while operating from the Spokane–Coeur d’Alene region. Previously, as Founder and Principal Writer at Off The Clock Resumes LLC, she scaled a boutique career services practice into a specialized partner for job seekers navigating competitive roles with compensation packages frequently exceeding six figures. She became known for a structured, data‑driven intake process that translates into résumés and LinkedIn profiles optimized for modern applicant tracking systems, significantly increasing interview rates and offer quality for her clients. Through one‑to‑one engagements and digital products, she has supported hundreds of professionals across tech and adjacent industries. Her career highlights include earning and maintaining the CPRW credential, signaling adherence to rigorous professional standards in résumé writing and career communication. She has continued to refine a distinctive positioning around “career branding that gets noticed and lands interviews with higher offers,” focusing on clarity of story, on‑screen confidence, and repeatable systems that scale beyond any single job search. By combining structured frameworks with empathy for career pivots, she has become a trusted partner for leaders who need to articulate complex trajectories in two pages or less. Listen to episode 161 on Spotify or Apple Podcasts Why the old keyword-stuffing playbook is dead. And what job seekers should do instead. “I am the face behind my business and in front of my business,” Steph says, “as well as the one that does all the one-on-one work with clients.” There’s something in how she phrases it—face behind and in front—that captures the exhausting clarity of solopreneurship. She’s the product and the salesperson. The expert and the marketer. And she’s been doing it since 2014. She started as a serial job seeker. “I am well rehearsed in job search practices,” she says, with the kind of dry humor that only comes from having lived through too many of them. Now she’s getting ready to attend another annual conference to stay current on hiring tech. The landscape, she tells me, is shifting faster than most people realize. I ask her what current hiring practices are doing to block talented candidates. “It’s gone beyond applicant tracking systems,” she says. “That used to be very keyword based. And now it’s not so much the worry of making sure your resume has all the right keywords.” She pauses. “AI is now adding generative and predictive analytics to this technology. It’s actually going to make it easier for job seekers because they don’t have to worry so much about the specific keywords.” This is counterintuitive. For years, the advice was: mirror the job posting. Product development. Project management. Agile methodology. Match the strings, beat the algorithm, get in front of a human. That era, Steph tells me, is ending. She walks me through an example. Say a product developer five to ten years ago wanted to tailor their resume. They’d add the term product development to ensure their resume would surface in searches. If someone went into LinkedIn looking for that skill, they’d pop up. “It was really important to have the right keywords, the right phrasing,” she says. Now? “If you don’t have the specific words—the specific product development phrase—AI is going to look at your experience and it’s going to look at context. It’s going to look at, you know, predictive. If you say you’ve done this, you likely have this skill.” She lets that land. “AI is going to start making assumptions about you that will help you.” The old systems were deterministic. You could game them if you knew the rules. The new systems are probabilistic. They infer. They read between the lines. This is good news for generalists and career changers—people whose careers don’t fit neatly into keyword buckets. I tell her this resonates. I’ve jumped between design and product management throughout my career, and I’ve gotten direct questions: What do you actually want to do? Few people accept my honest answer, which is basically whatever the company needs and I find interesting at the time. Steph nods. “At some point in the last ten years, the trend shifted from wanting someone with a broad range of skills to: we want a specialist, we want someone who really is an expert in this one thing.” She pauses. “But now that we’re adding in this AI element, we’re kind of going back to the original trend where AI wants to see the breadth of your knowledge and then be able to say, yes, this person has these skills, but they also have these skills, which will likely be a good fit.” The conversation turns to how people market themselves, and Steph lands on an analogy that sticks. “Highlighting benefits over features,” she says. “Those keywords, those skills—those were features, not the benefits. Whereas now, if you shift your mindset to: I’m going to position myself as the best fit for this job, not because of my skills, not because of the features that I bring, but because of the impact I’ve made.” She explains how this plays out technically. “One bullet on your resume can speak to an ATS based on the keywords in it—so that one bullet may be associated with project management skills. Whereas now with AI, that one bullet, depending on how much information you give it, might register five, six, seven different skills associated with that one bullet because of the impact you had.” The example she gives: designing a product that increased efficiency for a large enterprise. That single bullet, written with context, signals project planning, project management, design, strategy—multiple capabilities inferred from one outcome. The question isn’t What can you do? It’s What have you made happen? I bring up LinkedIn, and how I’ve started writing narrative case studies instead of bullet points for each role. The bet is that AI will read it and extract more context to provide better evaluations to hiring managers. Steph lights up. “Storytelling, especially on LinkedIn, is key. I used to work with clients very specifically on, let’s take these bullets on your resume and expand them as projects on your LinkedIn profile. Because that project section is also searchable. It’s also readable by the tools behind the scenes.” She leans into it. “Tell me the full story. How it started. What was the challenge that needed to be resolved. What you did, who you impacted, what obstacles you faced, and then what was the ultimate outcome.” Each project gets 2000+ characters, she says—2000 characters the AI can read, infer from, match you to opportunities. But the real shift in her thinking, she tells me, isn’t about resumes at all. “If you don’t tailor your resume for this specific job before you apply, you won’t even be considered,” she says. “I am still a strong believer in tailoring a resume if you’re gonna apply online. But now, because the competition is so high, I would say it’s more important to have a full blown strategy built outside of applying for jobs online.” What does that strategy look like? “It’s more important to be strategic in who do I need to talk to? Who can I start relationships with—even if it doesn’t result in a job at that company—but is going to expand my reach in my targeted field or industry?” She reframes networking as something that makes people less uncomfortable. “You can’t just think of it as networking—just getting your name out there and hoping something lands. But building professional friendships is what is going to make the difference.” I ask her how she coaches someone who’s just starting out, someone without an existing network. “Find a trade or professional organization that you can join and actively participate in,” she says. “One that opens you up to develop professional friendships with people you would maybe look at as competitors for different jobs, but they’re also mentors.” She tells me about a colleague halfway across the country. “She and I just sat down and had lunch together over Zoom and just talked shop. She has sent me referrals. I have sent her referrals. I would call her a mentor, but we’re also friends.” There’s warmth in it. “I know she’s in my corner. She will never do something to jeopardize that professional friendship.” I share a story from my own career. Five years ago, I had an offer from a company that I turned down for something more interesting. The hiring manager was a class act about it—That sounds really cool, I’m really excited for you—and he kept in touch. For five years. Then, recently, when I was looking again, an opening came up. I interviewed. It went well. Then a budget issue threatened to kill it. Another team needed to shuffle a designer internally. I waited all weekend, assuming it was over. The recruiter called. We want you here. We have to work this out, but we really want to figure out a way to make this work. They talked to the VPs. Got budget approval. Carved a spot out for me. “That’s best case scenario right there,” Steph says. It’s a five-year story arc, I tell her. And it only worked because the relationship was real. “That is the end goal,” she says. “You’re not going to find that by just applying for jobs on Indeed. You have to do that extra work. And the narrative of this is how you’re supposed to find a new job ke

    53 min

  7. MAR 2

    #160: Kasim Aslam – Traffic First, Product Second. The founder of the #1 Google Ads agency shares why solving for traffic before building anything changes everything.

    Kasim Aslam is the Co-Founder of Pareto Talent, a boutique executive assistant recruiting agency helping entrepreneurs reclaim 40+ hours per month through rigorously trained, full-time remote EAs sourced primarily from Latin America. Rising to prominence in the 2010s as the architect behind one of the top-ranked Solutions 8 Google Ads agencies in the world, he became known for building and exiting multiple seven- and eight-figure businesses while positioning himself as a leading voice on performance marketing and founder leverage. Today he is widely regarded as an influential figure in the emerging discipline of Answer Engine Optimization and founder systems design, serving growth-focused entrepreneurs through Driven Mastermind and his briefing series The Daily Sigh. Previously, as Founder and CEO at Solutions 8, Kasim scaled what his M&A advisor described as the largest specialized Google Ads agency in the world at the time of its sale, managing more than $100M in ad spend and growing a fully remote team of over 100 employees across multiple countries. In October 2022 he executed an all-cash eight-figure exit after nearly 18 years building the firm from a one-man web-development operation into a top-ranked Google Premier Partner serving hundreds of clients. That transaction marked his third successful exit after building six different seven- and eight-figure ventures over two decades. His career highlights include co-founding Driven Mastermind, an invite-only growth community led alongside Perry Belcher and Jason Fladlien that brings together multi-seven- and eight-figure founders for high-velocity experimentation and scale. He also co-founded Nido Marketing, a specialist firm dedicated to helping Montessori schools grow enrollments through digital marketing programs and over 20 self-guided courses built for more than 100 school operators. Earlier, as Co-Host of the Perpetual Traffic Podcast, he helped keep the show consistently ranked among the top 10 marketing podcasts worldwide while publishing weekly episodes over four years to an audience of thousands of practitioners. As the author of “The 7 Critical Principles of Effective Digital Marketing,” Kasim was recognized by BookAuthority among the 100 Best Digital Marketing Books of All Time and named one of UMSL’s Top 50 Digital Marketing Thought Leaders in the United States in 2020. Through his current project The Daily Sigh at DailySigh.ai, he delivers a 15-minute daily briefing distilling what actually mattered in business, AI, and entrepreneurship for revenue-generating founders, reinforcing his legacy as a strategist who converts complex shifts into practical, founder-ready decisions. Listen on Apple Podcasts↗ and Spotify↗ Why 20 years of watching “the best product lose” led to a radically different business thesis “I spent 20 years watching the best product lose,” Kasim Aslam tells me. He lets the sentence land. “I spent 20 years watching the best products go by the wayside. The best kept secret stay a secret. Because they couldn’t drive traffic.” We’re an hour into a conversation that started with him saying he builds businesses professionally—a phrase so casually delivered it took me a moment to register its weight. Kasim has built the number one ranked Google Ads agency in the world, exited to a SoftBank-backed organization at an eight-figure valuation, and accumulated a portfolio of 17 companies across digital marketing, real estate, and professional services. He’s not on the org chart of any of them. His favorite answer, he tells me, is “I don’t know.” But before any of that, there were the failures. Over a hundred of them, by his count. Medical transcription. A furniture store. Selling purified mercury. A moving company. Baskets on Amazon. “When I went back and tried to count,” he says, “I couldn’t count every epic failure.” Kasim was raised by a blind single mother on social security disability. At 22, he lost his job in the 2008 crash with $150,000 in debt. What he found on the other side of those hundred failures wasn’t a better product or a smarter strategy. It was a formula that most entrepreneurs get exactly backwards. Find the traffic first. Then figure out what problem to solve. --- The insight came from a peculiar vantage point. As the founder of Solutions 8, Kasim spent years managing $100 million in advertising spend for other people. Two hundred clients. Eighty employees. He got to see everything—what things cost, what they sold for, retention rates, competitor landscapes, what attention was actually worth. “What’s really devastating when you start to wrap your head around what that means,” he says, leaning into the word, “is Google makes more money than you do. You’re slaving away and the traffic stores are eating your lunch. You’re working for them.” An e-commerce company, he explains, will spend more on traffic than on cost of goods, fulfillment, operations, and customer service. Sometimes combined. The math is brutal. And most founders only discover it after they’ve already built the thing. Get full access to The Way of Product w/ Caden Damiano at www.wayofproduct.com/subscribe

    54 min

  8. FEB 23

    #159 Kelly Price — HR as Partners, Not Police: Control, Compliance, and Coaching Your Way to Better HR

    Kelly Price, SHRM-SCP is the Founder & CEO at ThriveHR, LLC. Rising to prominence in the 2010s as a high-impact HR and Total Rewards leader across multi-location service organizations, she became known for transforming people operations into a strategic growth engine for small and mid-sized businesses. Today she is widely regarded as a people-first operator who helps owners turn culture, compensation, and benefits into durable competitive advantage. Previously, as Senior People Partner – Total Rewards at nbkc bank, she led compensation and benefits strategy for a rapidly evolving financial services organization during a period of tightening labor markets and accelerated digital transformation. In her earlier tenure as People Operations & Benefits Manager at nbkc, she was responsible for end-to-end HR operations for the Kansas City metropolitan footprint, supporting several hundred employees through multi-year change while maintaining compliance, retention, and engagement metrics. Her career highlights include a seven-year rise at Samson Dental Partners, LLC, where she progressed from Recruiting Manager to Vice President of Human Resources while the organization scaled across multiple states and dozens of dental practices. During that period she built the recruiting function from scratch, hired clinical and non-clinical teams across home office and field locations, and expanded the HR organization to support rapid growth in headcount and locations. Earlier in her career, she sharpened her recruiting and talent acquisition craft at Ferrellgas and Waddell & Reed, managing nationwide and regional hiring mandates in highly competitive markets. A graduate of Kansas State University with a bachelor’s degree in Hospitality Administration and a SHRM Senior Certified Professional credential renewed through 2027, she has also been an influential figure in the Kansas City HR community through board service with Total Rewards KC and L’Arche Heartland. Through ThriveHR, she continues to advise founders and leadership teams across Kansas City, Southwest Florida, and Houston on building resilient people strategies that scale. Listen on Apple Podcasts↗ and Spotify↗ The Netflix Problem Everyone loves the Netflix talent philosophy in theory. Treat adults like adults. Pay top of market. Fire fast. No vacation tracking. But Kelly sees the gap between billion-dollar companies and the small businesses that make up most of America. A 50-person company in Kansas City can’t offer five engineers’ salaries for one rockstar. They need B players and C players for repetitive, supervised work—and that’s not a failure, it’s reality. “An A player can’t sit in every single role because they won’t be happy,” Kelly told me. “There are lots of different levels of work that needs to be done.” The talent strategy has to match the business. A startup founder passionate about their product doesn’t need—and can’t afford—Netflix-style HR. They need someone to take the compliance burden off their plate so they can focus on what they love. --- Control and Money When I asked about return-to-office mandates, Kelly didn’t hedge: “It’s all about control. Control and money.” She’s watched clients cling to eight-to-five, sit-at-your-desk policies despite every study proving flexibility drives productivity. COVID revealed something we can’t unsee—life is precious, and there’s more to it than work. But that doesn’t mean 100% remote works everywhere. Some jobs require physical presence. Some small businesses can’t manage a distributed team. The mistake isn’t having people in the office—it’s treating flexibility as a perk rather than a tool. “That is 100% a people problem,” Kelly said. “Do you have leaders in place that are holding their employees accountable? Creating an environment where they can ask questions when they don’t know what to do?” The system—remote, hybrid, in-office—doesn’t determine success. Leadership does. --- The Three-Tier Audit When Kelly onboards a new client, she starts with the business fundamentals: How do you make money? What are you trying to accomplish? What type of people work best here? Then comes the audit—every policy, every state, every compliance requirement. Hiring, I-9s, performance management, payroll, termination, offboarding. Top to bottom. The findings get prioritized into three tiers: **Compliance first.** “You’re gonna get sued for this stuff.” Fix what the government could fine you for before chasing strategy. **Tactical second.** Hiring processes, performance reviews, HR systems. Are they efficient? Are the people running them trained? **Strategic last.** Only after the foundation is solid do you ask: How can the people function support business growth? “If you don’t have these foundational things in place,” Kelly said, “you really shouldn’t be thinking about strategy.” --- Ask Permission The most practical advice Kelly shared was disarmingly simple: ask permission. “I wanna be honest with you, and I’d like permission to share my thoughts.” She’s never had anyone say no. They might disagree afterward, but they listen. And often they come back later, having processed what was said. It works with founders, CEOs, leaders with egos—anyone who needs to hear something they don’t want to hear. The phrase reframes confrontation as collaboration. You’re not attacking. You’re partnering. Get full access to The Way of Product w/ Caden Damiano at www.wayofproduct.com/subscribe

    50 min
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The Way of Product is your graduate school focused on developing a taste for what “great products” look like. Conversations are two professionals talking shop about positioning, segmentation, excellent product design, and most importantly, taste. www.wayofproduct.com

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