Peter Lubbers

🚀 Teaser Alert! 🚀 We're on the brink of unveiling a new feature powered by generative AI that will transform the way planners work. This cutting-edge technology automates tedious tasks and provides powerful insights, enabling our users to make more informed decisions with ease. ✨ But with great power comes great responsibility. ✨ At Reposite, we are deeply committed to the ethical use of AI and we have been working with the Gepeto team in partnership to deliver just that. We ensure transparency, fairness, and accountability in all our AI-driven features. By embedding these principles into our product and fostering a culture of ethical AI within our teams, we're not just embracing the future of tech—we're shaping it. Stay tuned for more updates! #Innovation #AI #EthicalAI #TechForGood #Reposite #FutureOfTech

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"Schiff’s bill would not ban AI from training on copyrighted material, but would put a sizable onus on companies to list the massive swath of works that they use to build tools like ChatGPT – data that is usually kept private." If you are using generative AI within your organization (and I'd be willing to bet that's most of us at this point), you should have eyes on this. "Is this legal?" is a massive question that will impact the whole industry, and the ripple effects will include all the companies and individuals using these tools. There are plenty of confident people on both sides of the argument but the truth is...we don't know how any of this will shake out. Understanding how models are trained, where the training data comes from, and the potential ethical and legal concerns of using these tools is the responsibility of every company using generative AI technologies. When in doubt, watch your six. https://lnkd.in/etREQxwi

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Truly mature design systems are almost always looking to have fewer components and less complexity at their core. Let composability and inheritance (systems of systems) build on top of a core foundation. There is a budding "ecosystem" model for design systems that have a maturity / adoption curve we should be able to model.

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There’s two common approaches I’ve seen to #compliance with content #retention mandates: 1. Our employees are “trained” on the retention policy (usually in a 15 online self-paced yearly training module that is in fact a compliance tool itself) and, 2. We delete everything that employees did not manually store in a system of records (but often those systems are not well understood by employees despite point 1). Fact is your people should be working on the business problems that create value for your business. Not making mistakes on low value admin tasks. Shuffling a PDF copy of a Confluence page into a nebulous SFDC “record” is a waste of everybody’s time. So we automate all that for you right in the source system with Retention Manager for Confluence. And keep an eye out for the Jira answer and other modern tools coming soon.

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I often find myself trying to communicate how the depth, breadth and nuance of thoughtful, contextualized product design can create systemic ripples across the landscape of society, culture, and economy. The principle of larger effects and systems seems rather timely given the impacts and implications of the work we find ourselves in the weeds. What might mindful, thoughtful innovation look like? If we are disruptive, working from a place of care and positive intent, are we still able to see the larger picture and the possible ripples from decisions? There is a power differential in recognizing the effects on systems. We often hear things like “technology is not neutral” or “the victors write the history”. This may mean there are far-reaching implications of decisions and systemic impacts without the realization of unintended consequences. If we are seeking to consider equity within a product we must increase our awareness and research, design, develop and execute from a space of curiosity without weaponizing approaches based on moral codes, personal beliefs and misaligned values. What does “for good” look like in practice, and to whom is it good for? We are often reliant on dominant narratives and frame things as edge cases. Those on the “edges” are often perceived as more work than necessary, less important, or statistically insignificant. This leads whole human identities to be framed as outliers.   These focused threads demonstrate how a product can drive change by reshaping perceptions and practices at both individual behaviours, choices, industry standards and cultural narratives. It’s about initiating change that can be sustained, leading to a reimagining of systems that have gone unchallenged. This guides us to examine the influence on social structures, economies, and ethical frameworks. A decolonization perspective asks us to critically examine how historical contexts have shaped products. Dismantling the inequities that are embedded within current systems, our journey begins in a world saturated with products designed without the richness of human difference in mind. The one-size-fits-all mentality prevails. Systems innovation would mean designing products that do not perpetuate colonial legacies but instead respect and uplift local knowledge, traditions, and needs. Who benefits from these innovations? Are these technologies accessible to all, or do they widen the digital divide? Do these innovations respect locality, or data sovereignty? Product equity must address global complexities, considering how a product fits into various cultural contexts and the impact on different communities. It's not just about doing no harm but actively doing good. Understanding balance—the need for steady iteration and the courage for radical change. We can build currents strong enough to redefine systems, rewrite narratives, and reshape these ecosystems. #ProductEquity #PrinciplesOfEquity #SystemsInnovation #SystemsThinking #Decolonization

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New post: AI is accelerating my technical writing output, and other observations At the start of the year, I wrote a trends post and noted uncertainty about the directions AI will take tech writers this year. (See My 2024 technical writing trends and predictions.) Now that we're into April, I have a better sense of how things are going and wanted to provide an update here. My main observation is that AI is accelerating my technical writing output, making me about twice as productive as before. Also noted in this post: prompt engineering is a non-obvious skill that many tech writers still struggle with, even though documentation is more within AI's sights than creative content. Read more » https://lnkd.in/gmBrGswb

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I can never talk enough about digital content accessibility for creative entrepreneurs. There's such a risk of them missing someone who could become their biggest fan because they post inaccessible content on their websites, in emails, or on social media. Many thanks to Kobo Writing Life for having me and Michele Lucchini on the latest episode of the KWL Podcast to talk about this topic and offer tips to authors. You can find the episode anywhere you listen to podcasts. There's also a transcript on the website. https://lnkd.in/g7J2eEaj #ContentForEveryone #ContentAccessibility #WebAccessibility #AccessibleSocialMedia #AccessibilityMatters #a11y

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Question for engineering leaders (managers, directors, VP's, etc): I'm curious about the current landscape of developer productivity analysis + management tools - things like LinearB and Jellyfish. Which tool, if any, are you using? Any opinions/pros/cons on the tool you're using (or the entire domain overall)?

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We had a fantastic Globalization Strategy Playbook Workshop at #Locworld51 in Dublin, Ireland! The participants shared their real business use cases, discussed strategic approaches, and walked away with a Strategy Statement for their organizations. We had the biggest turnout in the history of this Workshop! Thanks to The Localization Institute and Karen Combe for making this session possible. Inés Rubio showcased her implementation based on the Playbook. Karen Combe addressed working with stakeholders. Wayne Bourland went over technology and recent changes with AI. If you missed this event and would like to participate in the future, look for the session at #LocWorld52 in Monterey. Check out the book! It is free! #strategy #globalization #localization #business

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The reactions vary wildly when stakeholders hear the acronym, "PRD." Some folks dread them in companies with rigid ways of working. Those are our traumatized Product Managers in the crowd. The phrase, "That's not in the PRD!" rings loud on loop for them. (Poor one out for the jaded PMs out there). Other folks hate them because they represent planning work. Planning? Ugh. Defining scope? Eww. Timelines? Not very sexy. Especially when UX has "the Figmas" ...and Engineering has live demos. Some folks ask, "PR-what?" Product. Requirement. Docs. The thing that maintains alignment. It keeps your 4itB, 3itB, or maybe (but not hopefully) your 40itB on the same page. For the Fortune 1? PRDs are great for CYA. For the Fortune None? They're for tracking of your ever-changing scope (and maturing your fledgling org via forcing tough decisions). Oh yeah. And it rolls up into your roadmap. They are as flexible and adaptable as your Product leader needs them to be. And your company's SDLC maturity needs them to be. Ideally, the former drives the latter (but that's for another day). DM any questions you have on PRDs and how they could drive value for your org.

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In my experience of interviewing and working with many product leaders, a common trait among the great ones is treating their craft more as a science than an art. Delighting users, creating magical experiences, and ultimately developing software that users love to use is a science. An immediate red flag during interviews is when product leaders can't express details beyond "talking to customers" on how they build lovable products. While talking to customers is paramount, I listen for the structure and tools they use to become customer-centric and experts in the users they serve. Here’s what I look for: Methods to Listen For When Evaluating How Product Leaders Create Lovable Products: 🗺️ Journey Mapping: Understand what users do before and after they interact with your product or attempt to accomplish their job. 🔑 Key Moments Identification: Reveal the key moments that matter in the user journey. 😌 Emotional State Awareness: Understand the emotional states of users and how they change as they progress through the journey. 📊 Data Collection and Analysis: Collect and analyze data to understand funnels, drop-off rates, attrition, etc. I’m also on the lookout for specific techniques on how the product leader builds high-performing product teams. Here are some of the practices to listen for: 🏆 Recognition and Rewards: Establish clear KPIs that define success, create accountability, and drive alignment. Implement a system for recognizing and rewarding team achievements and individual contributions. 🤝 Consistent 1-on-1s: Conduct regular one-on-one meetings to mentor and guide the career and development of the product management team. 👥 Team Collaboration: Allow teams to craft their process and evolve it over time. My favorite team performance ceremony is the retrospective, where the team can gather in a safe place and collectively define how they will improve. 🔄 Cross-Functional Alignment: Create alignment between product, engineering, sales, marketing, and leadership. This involves regular cross-functional meetings, transparent communication of goals and progress, and a unified vision that ties the efforts of all departments together. Ensuring that all teams are moving in the same direction is crucial for driving consistent and sustainable growth. Overall, there are many important items across both themes that define effective product leadership. By listening for a product leader who employs these structured methods, companies can make a better hire to turn insights into actionable strategies, ensuring that the user experience is not left to chance but meticulously crafted and continuously improved, while building and managing high-performing teams that drive success.

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Over on my blog (yep, I've never stopped blogging in all these years), I've begun a series of posts about what I've learned over the years about how systems work. The latest is on a key concept that has helped shape the way I think about systems problems: The purpose of a system is what it does. Sure, it matters what people intend, and it's important to consider the complexity that the real world always brings to organizations and communities, but ultimately we should judge a system by what it outputs consistently. Hope you'll take a look. https://lnkd.in/g4ZmV7Zb

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The grim realities of a PMM. Courtesy of Aatir Abdul Rauf 🙌 __ We can talk all day about how a product marketer SHOULD function. In some utopian world where PMMs deeply understand every new technical feature and cheeseburgers don’t make you fat. But the reality will be staggeringly different. It is those individuals that embrace the adversity of 👉 Being out of the loop of major decisions 👉 Customer research cuts 👉 Volatile product/feature launches That really move the needle. ___ Any other expectations vs reality that come to mind in the life of a product marketer?

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It's been a month since Write the Docs, and I can't stop thinking about this illuminating talk. As tech writers, we all intuitively know that organized, clear, and accurate docs are essential to a successful product but I loved seeing the data to support this! #writethedocs #technicalwriting

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Intuit’s headquarters holds a seemingly ordinary piece of history: a kitchen table. Founded in 1983, the story goes that Scott Cook, sitting at this very table, watched his wife struggle with finances. This sparked the idea for an easier solution, laying the groundwork for Intuit. It's just a table, one that might remind you of your grandma's. Yet, it holds a special place. Every visit, I find myself drawn there. It's a powerful reminder: great products aren't born from extravagance. They stem from identifying real customer problems and dedicating ourselves to crafting solutions. In the picture: My dev lead Nili Davidor and I brainstorming at the table, carrying on the legacy of innovation.

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*A shortcut for building confidence in my product opinion* As someone who often gets pulled into very different problems, one of the hardest parts of my job is to build confidence in my product opinion fast. Without conviction that I’m making the right decision, how can I lead? So it’s been key to learn how I learn — how I can quickly understand a domain and build confidence about what to build next. My personal hypothesis: everyone has different triggers that help them feel confident in their decisions. So figuring out what specific methods work for me gives me a shortcut to build confidence in a new space. We can all name a bunch of different ways that people tend to learn. I’ve seen people be successful by going deep into: 1. Qualitative customer info 2. Product experience 3. Internal data 4. External market trends 5. Financial modeling 6. Creating mocks or prototypes The key is that for most of us, *finding the one or two of these methods that match our strengths is a shortcut for learning fast*, rather than trying to go deep on all of them at once. There’s an overwhelming amount of information out there — enough that I can convince myself that I constantly need to do more research in order to find the perfect answer. But as I wrote in “Execution beats strategy every time” earlier in this series, we usually don’t need a perfect answer immediately. We need a good-enough answer that we can iterate quickly on over time. Getting to that good-enough answer gives me a little island of knowledge to stand on as I build a more complete map of the world. What normally unlocks my confidence? Feeling like I have unique insight on the customer. Maybe it’s through talking with enough customers that I can hear patterns in their stories, maybe it’s by using the product every day in the way a customer does, or maybe it’s by sitting in a customer’s store and just observing how they spend their day.  Your shortcut might be deeply understanding the dashboards, or analyzing industry trends to foresee the future. But I always notice that I can build a lot more conviction fast when I feel like I have a customer on my shoulder, whispering in my ear — and so I’ve learned to optimize for building that intuition as quickly as possible. Then I can fill out my perspective with more data and market trends to make sure everything fits together. Figuring out my own typical personalized learning plan has been a great time-saver, and has given me a lot more confidence in approaching new problems. (This is part of an ongoing series about product, leadership, and scaling! For regular updates, subscribe to amivora.substack.com)

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Alistair Gray gave a great talk at Write The Docs Portland, going into detail about our investment in Internal Docs at Stripe. He breaks down our thoughts about issues of fragmentation, discoverability, and document quality - and how we’ve tried to build great tools to improve the state of internal docs at Stripe across all of these axes. In Q&A, he touches on an important theme which is essentially “how do we convince engineers to use the tooling we build.” The answer really boils down to “ruthlessly build what engineers want” while maintaining our core primitives (eg, ownership, doc quality) that we know are vital to the health of Stripe’s knowledge base all-up. Let me know if y’all have any questions - happy to expand more on these themes! https://lnkd.in/em4QRFmH

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