Does Agile Scale? Is it Time to Adopt the Lean Tech Manifesto?

Image Credit: Created with Gemini

For over two decades, I've championed working in an Agile way, and rightly so. The Agile Manifesto and its Principles revolutionized software development, empowering teams to be nimble, highly-collaborative, deliver customer value frequently, and continuously improve.   Yet here we stand at a crossroads: in today's world, having Agile software teams is no longer a differentiator—it's table stakes. The more provocative question lurks beneath the surface: many large organizations fail to remain “Agile” in large organizations.   This raises the question of whether the original Agile Manifesto scales to an organization level or whether we've reached the inherent limits of what the 2001 manifesto can accomplish within complex enterprise ecosystems.

The Promise of Agile: A Personal Journey

I recall my first exposure to working with an Agile team in 2004. I went from being a "resource" assigned to multiple projects concurrently—a cog in the machine of "maximum utilization"—to becoming a member of a highly collaborative cross-functional team aligned with the singular objective of building the best applications possible for our customers.

We ditched the 100+ page Business Requirement Documents and Functional Design Specifications in favor of a backlog of well-articulated and prioritized user stories, each delivering discrete value. Our interactions with business stakeholders and customers became frequent, quick, frictionless, and filled with ever-increasing trust, as opposed to contentious “negotiations” about requirements or meeting a fixed budget, timeline, and set of scope.

The transformation was profound. We compressed the time from concept to public production launch from 6-9 months to demonstrating "potentially shippable software" in two-week iterations and releasing every few iterations. We worked in lockstep with business stakeholders, adjusting our roadmap based on their feedback and early customer testing results. We leveraged Extreme Programming practices to build quality into our code while sharing knowledge and ownership across the team.

At the end of each iteration, we held retrospectives to identify ways to improve our collective work. We operated with discipline and focus, building trust with stakeholders by consistently delivering working software and incorporating their feedback. It was a joy—a more human and humane way of working that honored individual creativity and collective purpose.

The Scaling Challenge: When Team Agility Meets Organizational Complexity

As I progressed in my career, I led increasingly larger teams and helped numerous organizations adopt Agile and Lean practices. A pattern emerged: Agile practices worked beautifully at the team level, but they needed more robust scaffolding when scaling across multiple teams.

We implemented Scrum of Scrums to identify and resolve cross-team dependencies. We explored ways to merge code bases continuously, but these efforts were sometimes challenging when multiple teams were working against monolithic architectures. The fundamental question remained: Can the Agile principles that transform a team so effectively also work across the entire organization, or is more required.  

I remember attending an AgileNYC Agile Day event many years ago (not sure if this was 2011 or 2016) where Ken Schwaber, a co-founder of Scrum and signatory of the Agile Manifesto, gave the keynote. During Q&A, I asked whether the Manifesto would ever be updated or revised.  I wanted to know whether it would get updated to address the scaling challenges many organizations faced. His response was that he didn’t see the Agile Manifesto geting updated.  

Though I didn't press further, the question lingered for me. Would the same Agile principles suffice as organizations grew more extensive and more complex? Could organizational agility emerge simply by replicating team-level practices, or did scaling demand a fundamentally different mode of thinking?

This question wasn't new even then. Practitioners consistently found that while Agile practices thrived at the team level, their benefits diminished across entire organizations. Various frameworks emerged to address this gap—Scaled Agile Framework (SAFe), Large-Scale Scrum (LeSS), Disciplined Agile Delivery (DAD), and others—each with passionate advocates and critics.

The Lean Tech Manifesto: A Bridge Between Team Agility and Organizational Scale

Last week, I watched Jim Womack's keynote presentation, 'Lean Thinking: Past, Present & Future' at the UK Lean Summit 2024. Womack, a Lean thought leader whose seminal works "The Machine That Changed the World" and "Lean Thinking" explained how “Toyota's Production System” revolutionized manufacturing, and introduced its lessons to Western audiences.  He mentioned optimism about the future given creative engagement with Lean thinking and the tech world (20m50s).   This immediately captured my attention, especially when he mentioned the Lean Tech Manifesto as a powerful melding of the Agile Manifesto, modern tech world practices, and foundational Lean Thinking principles. Could this be the missing bridge that many organizations have been searching for?

I immediately watched "The Lean Tech Manifesto with Fabrice Bernhard—Hands-on Agile #65, which intrigued me as I wondered whether my questions about scaling would be addressed.    

Image Credit: Screenshot from The Lean Tech Manifesto with Fabrice Bernhard—Hands-on Agile #65

The premise is compelling: the Agile Manifesto excels at the team level but doesn't adequately scale to large technology organizations. The most successful companies have intuitively applied Lean Thinking to achieve organizational agility. Rather than rejecting Agile, the Lean Tech Manifesto distills and scales its principles, infusing them with Lean Thinking for the digital age.

Four core tenets of the Lean Tech Manifesto resonated deeply with my experience: (Full Disclosure: I have ordered but not read the Lean Tech Manifesto, authored by Benoît Charles-Lavauzelle and Fabrice Bernhard, so the following are my take aways from the presentation by Fabrice Bernhard.)

1. ‘Value for the Customer’ 

"Value for the Customer should be the organizational North Star," the manifesto boldly declares. This isn't merely a slogan; it's an organizing principle for technology organizations seeking true scalable agility.

While the Agile Manifesto emphasizes "customer collaboration over contract negotiation," the Lean Tech Manifesto goes further, advocating that every decision and initiative must directly connect to delivering customer value. This represents a shift from team-level customer focus to embedding customer value in organizational DNA—from processes to architecture to performance metrics.

2. ‘A Tech-Enabled Network of Teams’

Scaling is fundamentally about flow, and flow requires reducing dependencies and enabling autonomy and self-service at the team level. The Lean Tech Manifesto champions reducing direct dependencies through modular design and creating truly autonomous teams.

Consider Amazon's transformation into one of the world's most Agile large enterprises. Their API-driven architecture and "two-pizza teams" philosophy weren't accidents—they were deliberate architectural and organizational choices that maximized autonomy while maintaining alignment. This modularity allows teams to innovate and move rapidly without constant bottlenecks or approvals, a critical factor in scaling value delivery.

3. ‘Right-First-Time and Just-In-Time’

The Lean Tech Manifesto draws directly from the Toyota Production System—the gold standard of large-scale, high-quality production—applying its principles to focus on Quality and creating Pull within technology organizations.  The presentation specifically mentioned:

• Jidoka: Automation with a human touch for quality, enabling systems to detect abnormalities and stop automatically

• Dantotsu: Systematic problem-solving to eliminate defects at their root

• Kanban: Visualizing workflow and limiting work in progress to optimize flow

These aren't theoretical concepts but proven, practical tools for achieving high-quality, continuous delivery at scale, extending beyond software development to the entire tech value stream.

4. ‘Building a Learning Organization’ 

The ultimate aim, as highlighted by the Lean Tech Manifesto, is to become a Learning Organization. Organizations that thrive are those that relentlessly focus on customer needs, build upon both successes and failures, and rapidly disseminate learning throughout their structure.

This requires cultivating a problem-solving culture, standardizing best practices, and embracing continuous, on-the-job learning at every level—a true embodiment of system-wide continuous improvement that goes beyond the team-level retrospectives of Agile.

Questions I Hope to Explore Further

Several questions remain that I'm eager to explore more deeply when I get to read  Charles-Lavauzelle and Bernhard's book.  I wonder if it helps to address:

1. Legacy Transformation: How do established companies with monolithic systems best transition to microservices with modular design and loosely-coupled architectures without disrupting current value delivery?

2. Remote/Distributed Implementation: In describing how to focus on "Value for the customer," the Lean Tech Manifesto advocates going to the gemba (where work happens), using product architecture to clarify value, and leveraging visual management. How are these practices best implemented in geographically distributed organizations with primarily remote workforces?

3. Integration with Existing Frameworks: How does the Lean Tech Manifesto complement or replace existing scaling frameworks like SAFe, LeSS, or DAD?

Agile and Lean in Harmony

The Lean Tech Manifesto operates at a different level than the Agile Manifesto—not contradicting it but building upon it.  In my humble opinion, all organizations that build software should still value:

Individuals and interactions over processes and tools

Working software over comprehensive documentation

Customer collaboration over contract negotiation

Responding to change over following a plan

The Agile Software Manifesto and its principles remain every bit as relevant today as they did in 2001.  The Lean Tech Manifesto melds Lean Thinking and the Agile Manifesto together in a way that can help large tech organizations.   This shouldn’t be surprising given that similar origins inspire Lean and Agile, it makes sense that incorporating Lean Thinking into how organizations operate could deliver a lot of value. 

Similarly, organizations can't simply adopt team-level Agile practices and expect to achieve organizational agility. They need a holistic approach that addresses architecture, leadership, culture, and learning systems—the very elements the Lean Tech Manifesto emphasizes.

From Agile Teams to Lean Organizations: A Call to Action

It's time to move beyond simply "scaling Agile practices." The real goal is to cultivate a Lean-Agile organization—one that embodies a Lean-Agile mindset at every level, from the boardroom to the individual contributor.

The Agile Manifesto ignited a crucial shift in how we build software. But to achieve true organizational agility in today's complex, fast-paced world, we must embrace the systems thinking of Lean. The Lean Tech Manifesto offers practical advice for large tech organizations.

This isn't just about adopting new processes; it's about a fundamental shift in organizational culture, focused on people, relentless value delivery, and continuous improvement. It's about building organizations that are not just fast but truly adaptable, deeply customer-centric, and constantly learning. Is your organization ready to evolve our thinking beyond team-level agility to embrace organizational flow, system-level quality, and enterprise-wide learning?

Let's move beyond just "doing Agile" to being Lean-Agile, at scale. 

From Science Fiction to Reality: How AI is Reshaping Education

I love reading Science Fiction because it provides a view into what might be possible, and the best stories show how these new technologies solve complex societal issues.  One of my favorite books is Neal Stephenson's Diamond Age, written over 30 years ago, where the author tackles the insidious grip of social inequity with a bold vision for the future of education.  Stephenson introduces us to Nell, a young girl caught in the harsh realities of a stratified society where opportunity is a distant dream. She obtains a Primer -- an adaptive learning tool usually only available to the ultra-wealthy. The Primer enables Nell to transcend from a young girl from a lower socioeconomic standing into a thriving, self-reliant, intellectually formidable, and morally grounded individual—where she overcomes entrenched social hierarchies because of the radically personalized education she receives.

Image Credit: Gemini

What struck me about the Primer when I first read the story wasn't just its technological sophistication but its revolutionary premise: that the most effective educational tool would be one that adapts not just to a child's academic abilities but to their entire life context—their preferences, their environment, their unique potential. The profound power of Primer is eerily prescient to what is possible in our Digital Age with AI. 

Stephenson's Diamond Age dares to suggest that the most potent tool for social change might not be political revolution but educational evolution. It paints a picture of a future where education and technology are not a facilitator of information but a creator of opportunity that can level the playing field and redefine what's possible for everyone. 

Join me in a thought exercise where I explore whether building a learning tool like the Primer is possible and whether it could be the key to addressing today's social inequities worldwide.

NOTE: The Primer is the central educational force in Nell's life, but I firmly believe that the best learning platforms will help augment and support educators, not replace them.  Also, it's been many years since I last read the Diamond Age, so forgive if I miss any details. 

The Primer as a Mirror: Reflecting and Shaping Human Behavior

The Primer's brilliance lies in its ability to understand and adapt teaching to an individual’s context and learning style. It doesn't just impart information; it fosters critical thinking, problem-solving, and emotional intelligence. It does this through:

• Engaging Storytelling: The Primer uses narrative as its primary tool, crafting personalized stories that resonate with Nell's experiences. These stories are not mere entertainment; they are allegories, parables, and simulations designed to teach her valuable life lessons. The stories are designed to pull Nell into them, making her an active participant.
• Adaptive Learning: The Primer constantly monitors Nell's progress, adjusting its content and delivery to match her learning pace and cognitive development. It recognizes that every individual learns differently and tailors its approach accordingly.
• Motivation Through Interaction: The Primer is a conversational partner, a confidante, and a source of constant encouragement. It gives Nell the emotional support to overcome adversity and pursue her goals.
• Ethical Guidance: The Primer doesn't simply impose a set of rules on Nell. Instead, it guides Nell to develop her worldview and personal philosophy through interactive scenarios and thought-provoking questions. It encourages her to consider different perspectives, weigh potential consequences, and understand the complexities of ethical decision-making in a nuanced way.

Education must engage with the whole person.  The Primer succeeds in helping Nell transcend her circumstances because cognitive development cannot be separated from emotional growth, and ethics cannot be taught abstractly but must be lived through narrative and relationship. 

Rising Above Circumstance: The Power of Self-Actualization

The Primer's impact on Nell is profound. It transforms her from a vulnerable and marginalized child into a confident, resourceful, and intellectually independent young woman. It does this by:

• Fostering Critical Thinking: The Primer encourages Nell to question assumptions, challenge authority, and develop informed opinions. This critical thinking enables her to navigate her world's complexities and make informed decisions.

• Building Resilience: The Primer prepares Nell for the challenges she will face, teaching her to persevere in the face of adversity and to learn from her mistakes.

• Cultivating Accountability and Self-Reliance: The Primer empowers Nell to control her destiny. It teaches her to take accountability for things she can change and influence to change her circumstances through the abilities she has gained through her education.

Nell's journey is a testament to the power of education to transform lives. The Primer is not just a tool; it's a catalyst for change, a force that empowers individuals to break free from their circumstances' constraints and realize their full potential.

The Future of Education: A World Transformed

The future of education is no longer a distant vision; it is unfolding before our eyes, driven by the convergence of AI and emerging technologies. These advancements are not merely enhancing existing educational practices; they are fundamentally transforming the learning landscape, making the personalized and empowering experience of the Primer a tangible reality.

The future of education augmented by AI and emerging technologies is one where:

• Learning is personalized and adaptive, catering to each student's unique needs and preferences.

• Assessments are dynamic and provide real-time feedback that guides students toward deeper understanding.

• Learning environments are immersive and interactive, blurring the lines between the physical and digital worlds.

• Educators are empowered to focus on human-centered activities, fostering meaningful relationships with students.

• Ethical considerations and digital equity are prioritized to ensure that AI benefits all learners.

Bringing the Primer to Life: AI and Emerging Technologies

The Primer, once a figment of science fiction, is now becoming a tangible possibility due to the convergence of AI and other emerging technologies.  Consider the early emerging prototypes: AI tutoring systems that detect when a student gives a wrong answer and why they might be making specific errors, and ask questions to help the student find the correct answer. Learning Platforms can adjust examples and reading material to match a student's comprehension level and personal interests, driving student engagement and learning outcomes. 

Imagine moving beyond reactive measures and envision an educational ecosystem powered by foresight.  AI analytics offers more than just descriptive reports; it provides a predictive lens capable of anticipating learning challenges, identifying hidden talents, and revealing systemic patterns across classrooms and institutions.  By harnessing the power of AI to analyze data – from student interactions to performance metrics – we can equip educators, administrators, parents, and students with a shared, data-rich understanding of the learning landscape. This isn't just about improving individual outcomes; it’s about building a truly intelligent learning system, one that proactively adapts, optimizes, and ensures that every student at every level has the data-driven support they need to thrive in a rapidly evolving world.

Let's dare to design an educational system where human expertise is strategically amplified, not diluted by administrative demands.  Imagine AI helping educators seamlessly handling the flood of mundane, yet essential tasks: automatically grading quizzes and tests, generating initial drafts of personalized learning plans based on actual class performance, providing instant answers to frequently asked questions, freeing up educators from these cognitive bottlenecks. This isn't simply streamlining workflows; it’s a systemic shift towards human-centered education, recognizing that the true leverage point for transformation lies not in bureaucratic efficiency but in allowing educators to dedicate their full human potential to fostering deep learning, sparking curiosity, and nurturing the next generation of thinkers and creators.

The rise of immersive and experiential learning through Virtual Reality (VR)/Augmented Reality (AR) and gamification is another exciting development. These new learning modalities enhance learners' experiences by generating immersive content and experiences they can not get from books and may have infrequent access to in the real world. Imagine a classroom where the limitations of geography and resources vanish:  with VR/AR,  students can dissect a human heart without scalpels or traverse ancient ruins without leaving their desks.  This isn't mere simulation; it's democratizing transformative experiences, fueling a learner's intrinsic drive by offering information and the visceral understanding that only truly 'being there' can provide –  reshaping how we learn by redefining what's experientially possible.

As students progress toward graduation, AI can help support workforce development, enabling our students to prepare for their future careers.  It can provide competency-based learning and assessments for workers looking to upskill and find better opportunities.   By identifying skill gaps and facilitating competency-based learning, AI empowers individuals to acquire the skills necessary for success in the 21st century.  Generative AI systems can help students prepare for interviews and help corporations evaluate candidates beyond what's written in the job application and resume. 

The AI revolution also presents challenges that we must navigate thoughtfully in education.  The increasing prevalence of AI in education raises ethical considerations and concerns about digital equity. Issues such as data privacy, algorithmic bias, and access to technology aren't merely technical hurdles but moral imperatives that, if left unaddressed, could transform educational AI from a democratizing force into another mechanism of stratification. We face a profound choice: Will these technologies reinforce existing inequalities, accessible only to the privileged, or will we ensure they become universal tools for empowerment, reaching the countless "Nells" who need them most?

The true promise of AI in education isn't to make our current system more efficient—it's to make an entirely different approach to learning possible. Like the Primer, AI should not merely supplement traditional education but fundamentally transform how we conceive of teaching and learning. 

Looking Ahead: The Future of Education

The convergence of AI and emerging technologies could be ushering in a new era of education that mirrors the transformative vision of Stephenson's Primer. As we venture further into this uncharted territory, our collective responsibility is to ensure that these powerful tools are used to promote equity, inclusivity, and ethical practices. By embracing the transformative potential of AI while remaining vigilant about its challenges, we can shape a future where education empowers every individual to thrive in a rapidly changing world.

What Neal Stephenson imagined three decades ago as science fiction, we now face a real technological and moral crossroads. The question isn't whether we can build the Primer—we're already on that path. The question is whether we will utilize it with the same revolutionary intent: not merely as an advanced educational tool but as a mechanism for unlocking human potential regardless of circumstance.

As architects of this new educational landscape—whether technologists, educators, policymakers, or citizens—we confront a choice of profound significance: Will we deploy AI to simply optimize the existing educational paradigm, like installing faster engines on a ship heading in the wrong direction? Or will we harness these powerful tools to reimagine education, creating systems that adapt to each learner's unique context and potential?

We must choose the latter path. We must design AI educational tools for academic achievement and human flourishing. We must ensure that these tools reach those who need them most, not just those who can afford them. We must approach this work with both technological ambition and ethical humility, recognizing that we are not just building better educational software—we are shaping the future of human development itself.

The Primer is no longer science fiction—it's a technological horizon we're rapidly approaching. The question isn't whether it will materialize but whether it will serve the privileged few or catalyze opportunity for all. This isn't merely an educational technology challenge; it's the central equity question of our generation. It's our responsibility to bring it to life—not just as Stephenson imagined it, but as our world desperately needs it.

Beyond Features: Building a Product Culture That Thrives

Image Credit: CoPilot

 What separates companies that consistently deliver exceptional products from those that merely ship features? The answer lies not in their tech stack or talent pool, but in something far more fundamental: their product culture. In an era where every company claims to be "customer-centric," few truly embody this principle in their DNA.

In today's ever-evolving business landscape, having a strong product organization isn't just an advantage—it's a necessity. Most companies are stuck in the feature factory trap - shipping update after update while their core metrics barely budge. The harsh reality? Features alone don't guarantee success, and the old ways of simply churning out functionality are not just inefficient - they're dangerous to your company's survival.

Product Culture: The Heart of Innovation

A strong product culture is the beating heart of any successful product organization. It's not just a set of practices or principles written on office walls - it's the invisible force that shapes every decision, every meeting, and every line of code your team produces.

• Focus on Outcomes: Forget about simply shipping features. True success lies in achieving measurable results for your customers and your business. This means understanding the difference between output (what you build) and outcomes (the value it delivers). Imagine spending months perfecting a feature, only to watch it sit unused in your product - a digital monument to misaligned priorities. That's a classic example of prioritizing output over outcomes. A strong product culture shifts the conversation from "What should we build next?" to "What problems are worth solving?"  For example, a company that successfully shifted its focus from output to outcomes is Spotify. By focusing on the outcome of helping users discover new music, Spotify was able to develop innovative features like Discover Weekly, which provides users with personalized playlists of songs they might enjoy. This outcome-oriented approach has helped Spotify become one of the world's most popular music streaming services.

• Empowered Product Teams: Picture two scenarios: In the first, a team awaits approval for every minor decision, their creativity suffocated by bureaucracy. In the second, a team owns their decisions and their outcomes, moving with the speed and confidence of true product owners. Which team do you think builds better products? Give your teams the autonomy and ownership they need to solve problems and make decisions. When teams feel empowered, they become more innovative, engaged, and responsive to customer needs. However, empowerment without accountability is chaos. The key is creating a system where teams can innovate within clear strategic guardrails, measuring their success not by features shipped but by customer problems solved.

• Continuous Learning: In the fast-paced world of product development, comfort is the enemy of growth. A strong product culture embraces experimentation, learns from failures, and adapts quickly based on data and feedback. The most dangerous words in product development are "This is how we've always done it." Imagine a product team that's afraid to take risks and try new things. They might play it safe, but they'll miss out on opportunities for innovation and growth. A culture of continuous learning requires psychological safety - the shared belief that it's safe to take risks. When teams fear failure, they stop experimenting. When they stop experimenting, innovation dies.

Product Strategy: The Roadmap to Success

A product strategy isn't a document that sits in a drawer - it's a living framework that guides every decision your team makes. It's about making smart choices, prioritizing opportunities, and ensuring that everyone is rowing in the same direction.

• Identify Critical Problems: A doctor who prescribes medication without a diagnosis isn't just inefficient - they're dangerous. Yet countless product teams do exactly this, building solutions before truly understanding the problem. Before you can build great products, you need to understand the problems you're trying to solve. This means taking a deep dive into the needs and pain points of your customers. The most expensive mistake in product development isn't building the wrong solution - it's solving the wrong problem. To truly understand customer needs, product teams can employ a variety of lean techniques, such as conducting in-depth customer interviews, analyzing user data for patterns, and gathering feedback through surveys. But here's the crucial difference: don't just listen to what customers say - observe what they do. Human behavior often contradicts stated preferences.

• Prioritize Opportunities: The most successful product leaders aren't known for what they build - they're known for what they refuse to build. Every 'yes' to a mediocre opportunity is a 'no' to potentially game-changing ones. Not all problems are created equal. A strong product strategy involves making tough choices about which opportunities to pursue. This isn't about maintaining a bloated backlog of "someday" features - it's about having the courage to say no to good ideas in service of great ones. Think of it like a gardener deciding which plants to cultivate. They need to consider factors like the type of soil, the amount of sunlight, and the availability of water. Similarly, product teams need to use data, market analysis, and customer feedback to make informed decisions about which opportunities to prioritize.

• Align Metrics with Product Lifecycle: Judging an early-stage product by revenue is like measuring a toddler's success by their salary potential. Craig Strong, in "The Lean Product Lifecycle" emphasizes the importance of aligning metrics with the product's lifecycle stage. The metrics that matter for a nascent product exploring product-market fit are radically different from those that matter for a mature product optimizing for scale. He argues that using the same metrics throughout the product's life can lead to misaligned priorities and poor decision-making.
  

Think of your product like a child growing up. In infancy, you measure different things than you do during adolescence or adulthood. In your product's early stages, celebrate learning and discovery. As it matures, shift your focus to growth and efficiency. But never forget - even mature products need room to experiment and evolve.

• Align Teams with Strategy: A brilliant strategy trapped in PowerPoint slides is worthless. The magic happens when every team member understands not just what to do, but why it matters. A great strategy is only as good as its execution. Picture an orchestra where each musician plays their favorite song - the individual performances might be excellent, but the result is chaos. Your product organization needs to play the same symphony, even if different sections have different parts. Ideally you want your product teams to be "loosely coupled" so they create products quickly, but you want them to be "tightly aligned" to the product strategy and corporate objectives.

Product Teams: The Engine of Execution

Your product teams are the engine that drives your product organization forward. To build a high-performing engine, you need the right parts, the right fuel, and the right maintenance.

• Cross-Functional Composition: Build teams with a diverse range of skills, including product management, UX design, and engineering. This allows teams to tackle problems holistically, bringing together different perspectives and expertise. Imagine a car without a steering wheel. It might have a powerful engine, but it won't get very far. Similarly, a product team that lacks key skills will struggle to navigate the complex landscape of product development.

• Durable Teams: Keeping teams together for longer periods allows them to build trust, improve communication, and develop a deep understanding of the problem space. Think of it like a well-oiled machine. The more the parts work together, the smoother and more efficient the operation becomes. Durable or “long-standing teams”are able to anticipate each other's moves, communicate effectively, and solve problems quickly. Think of it like a championship sports team - they don't shuffle the roster after every game. They give the team time to learn each other's strengths, develop shared intuition, and build collective excellence. However, it's important to acknowledge that keeping teams together for long periods doesn’t mean they will work on the same thing for the entire duration that they are working together.   Instead you can shift what the teams work on and provide opportunities for growth and learning.

• Empowerment and Accountability: Give your teams the authority to make decisions and hold them accountable for the outcomes. This creates a sense of ownership and encourages teams to take responsibility for their work. Imagine a ship with no captain. It might have a skilled crew, but it will drift aimlessly without direction. Similarly, product teams that lack empowerment and accountability are less likely to take initiative or drive for results.

Product Discovery: The Art of Finding the Right Path

Product discovery isn't about finding the right answers - it's about asking the right questions. In a world obsessed with solutions, the real competitive advantage lies in deeply understanding the problem. It's about minimizing waste, assessing risks, and experimenting rapidly to find the best solutions.

• Minimize Waste: The most expensive waste in product development isn't building things wrong - it's building the wrong things. Don't waste time and resources building features nobody wants. Every line of code is a liability until it creates value for users. Use techniques like prototyping, user research, and A/B testing to quickly validate your assumptions and avoid costly mistakes. Think of each feature as an investment - would you invest your life savings without due diligence? Then why invest your team's time and energy without proper validation?

• Assess Risks: Every product decision comes with risks. It's important to evaluate these risks early in the process, considering factors like value, usability, feasibility, and viability. Think of it like a mountain climber assessing a route before starting the ascent. They need to consider the terrain, the weather, and their own skills and experience. Similarly, product teams need to carefully assess the risks associated with each product decision to avoid potential pitfalls.  These risks can be categorized as market risks (e.g., lack of demand), technical risks (e.g., feasibility challenges), and financial risks (e.g., cost overruns).

• Rapid Experimentation: In product development, being wrong isn't the problem - staying wrong is. The best way to learn is by doing. Your first idea is rarely your best idea - it's just the starting point for learning. Use prototypes and experiments to gather feedback and iterate on your solutions. Each experiment is a conversation with reality, and reality always has the final vote. Imagine a scientist conducting experiments to test a hypothesis. They don't expect to get it right the first time. Instead, they use each experiment to learn and refine their approach.

Product Delivery: The Science of Bringing Value to Life

Delivery isn't the end of the product development process - it's the beginning of learning how your assumptions hold up in the real world. It's about getting your product into the hands of your customers quickly, efficiently, and continuously.

• Small, Frequent Releases: Big releases are like holding your breath underwater - the longer you wait, the riskier it becomes. Deliver value to your customers in small, frequent increments. Each release should be small enough to be low-risk but valuable enough to be worth deploying. Think of it like building a house brick by brick. Each brick adds value and contributes to the overall structure.

• Instrumentation and Monitoring: Flying blind in product development isn't just risky - it's irresponsible. Keep a close eye on your product's performance. Data without insight is just noise. The goal isn't to collect metrics - it's to drive decisions. Track key metrics, identify issues, and use data-driven insights to inform your decisions.

• Deployment Infrastructure: Invest in tools and processes that enable continuous integration and delivery. This allows you to automate your workflows, reduce time to market, and deliver value to your customers faster. Think of it like a well-maintained highway system. The smoother the roads and the clearer the signs, the faster and more efficient the flow of traffic. Similarly, a robust deployment infrastructure allows your product to reach your customers quickly and reliably.

Product Leadership: The Guiding Light

Product leadership isn't about having all the answers - it's about creating an environment where the right answers can emerge. Strong product leadership illuminates the path for your product organization through direction, support, and inspiration.

The art of product leadership is knowing when to provide answers and when to ask questions. When to set direction and when to step back. When to prescribe solutions and when to let teams discover their own path.

• Coaching and Mentorship: Invest in the growth and development of your product teams. Provide guidance, support, and opportunities for learning. Think of it like a gardener tending to their plants. They provide water, nutrients, and support to help the plants grow and thrive. Similarly, product leaders need to nurture their teams, providing them with the resources and guidance they need to succeed.  This can be done through various methods, such as bringing in thought leaders, one-on-one meetings, group workshops, and online resources.

• Strategic Context: Ensure your teams have the information and understanding they need to make informed decisions. This means clear communication, transparent decision-making, and access to data. Imagine a soldier on the battlefield without a clear understanding of the mission. They might be brave and skilled, but they won't be effective without proper direction. Similarly, product teams need to understand the strategic context of their work to make decisions that align with the overall goals.  Creating a culture of transparency and open communication is essential, where teams feel comfortable asking questions and sharing their concerns.

• Continuous Improvement: Never stop seeking ways to improve your product operating model. Adapt to changing needs, embrace new ideas, and foster a culture of continuous learning. Think of it like a ship navigating a changing sea. The captain needs to constantly adjust the course, considering the wind, the waves, and the currents. Similarly, product leaders must be adaptable and responsive to change, ensuring that their product organization stays ahead of the curve.

Product Organizations Need to Continually Evolve

Building a strong product organization is a journey, not a destination. It requires a customer-centric mindset, a culture of continuous learning, and a commitment to empowering product teams. By embracing these principles and investing in strong product leadership, you can create a product powerhouse that thrives on innovation, customer satisfaction, and sustainable growth.  In today's dynamic business environment, continuous improvement and adaptation are more critical than ever. By staying ahead of the curve and responding to changing customer needs, you can ensure that your product organization remains competitive and successful.  While these principles might seem straightforward, implementing them requires courage, persistence, and a willingness to challenge conventional wisdom.

Call to Action: The gap between mediocre and exceptional product organizations isn't in their tools or processes - it's in their mindset and culture. Take a moment to reflect:

• Are you building what's easy, or what matters?

• Is your team empowered to solve problems, or just follow orders?

• Are you learning from failure, or just trying to avoid it?

• Is your product strategy guiding decisions, or just decorating walls?

The choice between building a feature factory and a product powerhouse isn't made once - it's made every day, in every decision, by every member of your team. Which choice will you make today?

Note: The thoughts expressed in this blog post are not unique ideas that I came up with myself.  They are informed by amazing lean and agile product thought leaders such as: Marty Cagan, Jeff Patton, Jeff Gothelf & Josh Seiden, Craig Strong, Teresa Torres, Eric Ries, Nir Eyal, Roman Pichler, Melissa Perri, Dan Olsen, and others.