Author: Baha

I bring over 15 years of consulting experience across various industries, including banking/finance, government, software solutions, aviation, retail, and creative agencies. My expertise in Human-Computer Interaction (HCI), usability, service design and AI application design has enabled me to lead numerous successful projects in consulting roles.

Cultivating Optimism: A Skill for Success

Optimism is a remarkable and transformative belief that invites us to view our circumstances through a lens of potential and hope. It asserts that improvement is not just a distant dream but a reality within our grasp, even in the face of complex challenges and significant constraints. Instead of waiting for absolute certainty to take action, we are encouraged to trust that clarity and solutions will emerge through our engagement with the world around us.

This perspective extends far beyond a mere positive attitude; it fundamentally shapes our approach to life’s obstacles. By allowing us to let go of fear and embrace new possibilities, optimism empowers us to move forward, even when the path ahead seems uncertain. It prevents us from being immobilized by the risks and potential failures that often overshadow our ambitions.

Where fear may narrow our focus and amplify doubts, optimism broadens our horizon, revealing opportunities alongside risks. It fosters creativity, bolsters innovative thinking, and instills the confidence needed to confront difficulties. Setbacks transform from mere failures into invaluable learning experiences that guide our next steps. By adopting this optimistic mindset, we pave the way for decisive action amid uncertainty, driven by the belief that our efforts will ultimately yield positive outcomes. Over time, this approach diminishes the hold of fear and fortifies our confidence in the pursuit of success.

The Art of Navigating Uncertainty

In professional environments, optimism shows up when we share ideas, ask for feedback, and see pushback as helpful instead of negative. In our personal lives, it means making progress even when we don’t know the outcome, trusting that moving forward will make things clearer.

People who expect success and move forward with confidence stay engaged longer. Instead of viewing setbacks as reasons to give up, they see them as signs to change their approach. This attitude promotes ongoing improvement in our ideas. Rather than asking, “What if this fails?” optimism leads us to think, “What if this helps me grow and teaches me something important?”

Research shows that optimism is more than just feeling good; it can lead to real success. A well-known study found that optimistic workers performed better than those who weren’t as hopeful, not just because they worked hard, but because they believed success was possible, even when challenges appeared [1]. By focusing on our ideas’ potential for success rather than fears of failure, we can turn setbacks into chances to learn and adopt a mindset where anything seems possible, even with tough problems.

Stories of Growth in Design

When faced with criticism or obstacles, an optimistic designer doesn’t back down – instead, they listen carefully, rethink their approach, and make improvements. Take, for example, a designer presenting ideas to stakeholders who seem doubtful; rather than viewing skepticism as rejection, optimism encourages open dialogue and teamwork, which can lead to better outcomes. This collaborative atmosphere can foster creative solutions that might not have been considered otherwise.

Additionally, the influence of optimism on problem solving is profound. An optimistic designer approaches challenges with a solution-oriented mindset, exploring multiple angles and possibilities. They become adept at adjusting their strategies in real-time, allowing them to pivot when necessary. This flexibility not only enhances the design process but also builds resilience, enabling designers to bounce back from setbacks with renewed vigor.

This positive mindset helps designers stay focused on what works, learn from setbacks, and see every challenge as something that can be overcome, even when the problems are tough. It nurtures a culture of innovation, where experimentation and risk-taking are encouraged. This can lead to groundbreaking ideas that elevate design projects. When designers embrace an optimistic view, they are more likely to inspire those around them, fostering an environment where creativity thrives.

Furthermore, optimism extends beyond design into everyday life and long-term goals. It shapes how we interact with colleagues, clients, and even family, promoting stronger relationships built on trust and mutual respect. Instead of worrying about being judged or failing, optimism encourages us to engage with the world in meaningful ways. This perspective allows us to approach uncertainty with confidence, viewing our efforts, big or small, as essential steps in our journey toward success. It empowers individuals to take initiative, volunteer for new projects, and seek out opportunities for growth, ultimately contributing to both personal and professional development.

Embracing the Power of Optimism

Optimism is not a magical gift; it’s a skill you can nurture through purposeful habits:

  • Shift your self-talk: See setbacks as valuable lessons rather than proof of shortcomings, without being consumed by how the setback made you feel. Our self-talk drives our actions, and the more we focus on cultivating positive self-talk, the more we will see that reflect in our actions and the outcomes we see, whether at work or in everyday life. This process requires intentional effort and mindfulness; we can start by recognizing negative patterns in our self-talk and consciously replacing them with affirming statements. Over time, by continuously reinforcing positive narratives, we establish a healthier mindset, which not only benefits our personal growth but also enhances our relationships and overall well-being.
  • Acknowledge progress: Small achievements build confidence, making bigger goals seem within reach and more attainable. Achieving what might seem like the smallest task can significantly impress our subconscious mind, fostering a positive feedback loop that encourages us to continue pushing ourselves to achieve even more every day. This recognition not only propels our motivation but also reinforces our belief in our capabilities, allowing us to set and pursue increasingly ambitious objectives with a sense of purpose and enthusiasm.
  • Connect with supportive people: Our choices in company and environment shape our mindset and actions. Surrounding ourselves with individuals who uplift, encourage, and inspire can significantly influence our personal growth and overall well-being. Seeking out a community that shares similar values, aspirations, and interests can foster a sense of belonging and motivation, enhancing our ability to navigate life’s challenges and achieve our goals.
  • Express gratitude: Pay attention to what you have and what matters now, instead of dwelling on what’s absent. Practicing gratitude can have a profound impact on your overall well-being and happiness. It helps you appreciate the positive aspects of your life, leading to a clearer perspective. Gratitude changes our mindset to one of opportunity and abundance rather than one of lack. This shift in focus is essential, as it trains our subconscious mind to find the opportunities that surround us, ultimately fostering a more fulfilling and enriched life rather than concentrating solely on what’s lacking. By regularly acknowledging and valuing the good in your life, you can create a positive feedback loop that enhances your emotional resilience and overall life satisfaction.

Conclusion

Building optimism enriches both our personal and professional lives, enabling us to approach uncertainty with curiosity rather than apprehension. When we examine design, careers, relationships, and ambitions through an optimistic lens, we empower ourselves as a collective: fear no longer constrains our choices or actions. Instead, we learn to identify new possibilities, viewing setbacks as stepping stones toward success because we trust in our collective capacity to take constructive action.

By replacing fear with optimism, we unlock a wealth of opportunities that the universe has to offer. An optimistic perspective allows us to see the abundance that surrounds us, revealing resources and connections that we might have previously overlooked. As we cultivate an optimistic outlook together, we align ourselves with the flow of life, inviting growth and prosperity into our shared experiences.

In essence, optimism acts as a magnifying glass that amplifies our awareness of possibilities, encouraging us to reach for what is available and achievable. As we embrace this powerful mindset collectively, we not only enhance our potential as individuals but also inspire those around us to recognize the vast opportunities that lie ahead. This shift towards optimism nurtures a culture of collaboration and support, where everyone is empowered to explore their unique paths while contributing to the abundance available in the universe.

[1] Seligman, M. E. P. (2006). Learned optimism: How to change your mind and your life (2nd ed.). Vintage Books.

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Quantum Revolution: How Max Planck Tapped Into the Universe’s Zero-Point Mysteries

Unveiling the Ever-Vibrant Fabric of Reality

Introduction

At the dawn of the twentieth century, Max Planck embarked on a quest to unravel how energy is absorbed and emitted by the filaments within light bulbs, aiming to maximize their efficiency and illuminate more while consuming less power. In doing so, Planck not only resolved practical engineering challenges, but also ignited a scientific revolution that fundamentally reshaped our comprehension of physics and the universe itself.

Planck’s investigations shattered the classical notion that energy flows in a seamless, continuous stream. Instead, he revealed that energy is exchanged in tiny, indivisible packets known as quanta. This radical insight gave birth to quantum theory, a new framework that challenged long-held assumptions and transformed our understanding of the physical world, from the behaviour of the smallest particles to the structure of the cosmos.

The significance of Planck’s discovery extends far beyond theoretical physics. By demonstrating that energy exchanges are quantized, he opened the door to a wave of scientific breakthroughs, paving the way for technologies such as semiconductors, lasers, and quantum computing. Moreover, subsequent research based on Planck’s work uncovered the existence of zero-point energy: even in the coldest conceivable state, where classical theory predicted absolute stillness, quantum systems retain a subtle but unceasing vibrancy. This revelation overturned the classical thermodynamic belief that all motion ceases at absolute zero, unveiling a universe in perpetual motion at its most fundamental level.

Planck’s legacy is profound, not only did he lay the foundations for quantum mechanics, but his insights continue to inspire new discoveries that help us probe the mysteries of existence. By deepening our grasp of reality’s underlying fabric, Planck’s work has transformed how we see our place in the universe, inviting us to explore how the strange and wonderful quantum world shapes everything from the nature of matter to the emergence of life itself.

The Black Body Problem and Ultraviolet Catastrophe

As the nineteenth century turned, new technologies such as the light bulb drove increased interest in the interaction between materials and radiation. Efficient engineering of light bulbs demanded a deeper understanding of how materials absorb and emit energy, especially the filaments inside the bulbs. In the early 1890s, the German Bureau of Standards commissioned Planck to optimize light bulb efficiency by identifying the temperature at which bulbs would radiate mainly in the visible spectrum while minimizing energy loss in the ultraviolet and infrared regions [1].

Prior attempts to explain the behaviour of heated materials, notably the Raleigh-Jeans law, predicted infinite energy emission at short wavelengths – the so-called ultraviolet catastrophe. These models often relied on the concept of an ideal material that perfectly absorbs all wavelengths, termed a black body. The ultraviolet catastrophe led directly to the “black body problem,” as experimental results contradicted the notion that materials like lightbulb filaments would emit infinite energy at high temperatures.

Planck addressed this issue by conducting experiments with electrically charged oscillators in cavities filled with black body radiation. He discovered that the oscillator could only change its energy in minimal increments, later quantified as h (Planck’s constant). The energy exchanged was proportional to the frequency of the electromagnetic wave and occurred in discrete quantities, or quanta. This finding gave rise to quantum theory and revealed a deeper truth: energy remains with the oscillator (or the atoms in the material) even at absolute zero temperature.

Zero-Point Energy and Its Implications

By solving the ultraviolet catastrophe through his black body absorption equation, Planck discovered zero-point energy (ZPE). Unlike the catastrophe, the existence of zero-point energy was verified experimentally, overturning classical thermodynamics’ expectation that all molecular motion would cease at absolute zero.

Zero-point energy accounts for phenomena such as vacuum-state fluctuations, where even an electromagnetic field with no photons is not truly empty but exhibits constant fluctuations due to ZPE. One of the most fascinating examples is the Gecko – a lizard capable of traversing walls and ceilings on nearly any material. The Gecko exploits quantum vacuum fluctuations present in the zero-point energy of the electromagnetic field. Its feet are covered with millions of microscopic hairs that interact with the quantum vacuum fluctuations of any nearby surface, resulting in an attractive force known as van der Waals force, a microscopic form of the Casimir effect. Through this process, the Gecko draws energy from the vacuum field, demonstrating nature’s ability to harness zero-point energy.

Experimental Advances in Harnessing Zero-Point Energy

Research teams from Purdue University and the University of Colorado Boulder have shown that energy from the vacuum state can be accessed through the Casimir force, which acts on micro-sized plates in experimental setups. Although the effect is small and produces limited energy, more efficient methods may be possible using quantum vacuum density and spin. The impact of spin is visible in fluid systems like hurricanes and tornadoes. By inducing high angular momentum vortices with plasma coupled to the quantum vacuum, researchers can create energy gradients much larger than those observed with simple non-conductive plates in the Casimir effect.

These pioneering investigations illuminate how quantum phenomena, once confined to abstract theory, are now being harnessed in the laboratory to extract measurable effects from the very fabric of space. While the practical application of zero-point energy remains in its infancy, the ongoing refinement of experimental techniques – such as manipulating spin and plasma interactions – offers glimpses of a future where the subtle energy fields underlying all matter could become a resource for technological innovation. Each advance deepens our appreciation for the intricate interplay between quantum mechanics and the observable world, suggesting that the restless energy pervading the vacuum is not merely a curiosity, but a potential wellspring of discovery and transformation that may one day reshape our understanding of both energy and existence.

Conclusion

Max Planck’s pursuit to optimize the humble light bulb did far more than revolutionize technology, it opened a window into the deepest workings of the universe. By questioning how filaments absorb and emit energy, Planck uncovered the quantum nature of reality, revealing that energy is exchanged in discrete packets, or quanta, rather than in a continuous flow. This insight not only solved the black body problem and the ultraviolet catastrophe but also led to the discovery of zero-point energy, the realization that even at absolute zero, particles never truly rest, and the universe itself is in perpetual motion. 

Zero-point energy shows us that nothing in the cosmos is permanent. Particles continuously move, shift, and even appear and disappear, embodying a universe that is dynamic and ever-changing. As humans, we are inseparable from this cosmic dance. Our bodies, thoughts, and lives are woven from the same quantum fabric, always in flux, always evolving. Planck’s work reminds us that change is not just inevitable, it is fundamental to existence itself. In understanding zero-point energy, we come to see that reality is not a static backdrop, but a vibrant, restless sea of possibility, where both matter and meaning are constantly being created and transformed.

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Transformative Discovery: Integrating Coaching Principles for Project Success

The Human-Centered Approach to Discovery

At the core of effective discovery work lies the importance of coaching when gathering requirements. Over time, I’ve realized that meaningful insights rarely emerge from rigid templates or formal interviews; instead, they arise through genuine conversations where people feel supported enough to pause, think deeply, and express what they need.

Often, an initial request such as “We need a dashboard,” or “Can you shorten this workflow?” uncovers more fundamental issues like decision-making, team alignment, confidence, or communication barriers. By approaching discovery with a coaching mindset, we can reveal these underlying concerns rather than just addressing superficial symptoms. If you’ve ever experienced a discovery session that seemed more like coaching than interviewing, you’ll recognize the value of intentionally cultivating this dynamic.

Reflecting on my recent years of interviews, I’ve noticed a shift, they increasingly resemble coaching sessions. Initially, I thought I was merely “collecting requirements,” but over time, it became clear I was guiding people in clarifying their actual needs. Rather than just recording their requests, I was facilitating their thinking.

In early design meetings, users typically begin with basic asks: “We want a dashboard,” “Can you make this workflow shorter,” “Can we have a button that does X?” These are useful starting points, but they seldom tell the whole story. When I consciously adopt a coaching approach, slowing down, listening attentively, and posing thoughtful questions, the dialogue changes dramatically. At that moment, our focus shifts beyond the user interface into deeper topics: friction, decision-making processes, confidence, accountability, ambiguity, and the human elements hidden beneath feature requests.

Many professionals who have spent decades in their roles rarely get the chance to reflect on the patterns shaping their daily work. So, when I ask something as straightforward as, “What’s the hardest part about planning next season?” the answer often reveals gaps and bottlenecks behind the scenes, rather than issues with the software itself. These stories simply don’t surface during standard meetings.

Uncovering Deeper Insights through Curiosity and Coaching

Curiosity allows us to explore areas untouched by process charts and requirement documents. Prioritizing the individual over the process exposes context that’s invisible on paper, like emotional burden, workplace politics, quiet worries, workarounds, and shared tribal knowledge. Coaching fosters an environment where all these factors come to light, transforming them into valuable material for design decisions.

I used to think the better I got at systems, the less I’d need to do this. But it turned out the opposite is true. The better the system, the more human the conversations become. Coaching is almost like a bridge, helping people cross from “I think I need this feature” to “Here’s what I’m actually trying to solve.”

Active Listening and Guided Curiosity

Active listening forms the core of my approach, ensuring I deeply understand not just participants’ words but the meaning behind them. I reflect statements back — such as, “So it sounds like the challenge isn’t entering the data, it’s aligning on which data to trust, right?” — to confirm genuine understanding. This often transforms technical discussions into conversations about alignment, ownership, or governance.

A key tool is the “Five Whys” technique, which I use as a guide for curiosity rather than a rigid checklist. If someone requests better notifications, I’ll probe: “Why is that important?” and follow with questions like, “Why is it hard to notice things right now?” or, “What happens when you miss something?” By the fourth or fifth ‘why,’ the conversation surfaces underlying factors such as workload, confidence, or fear of missing out, revealing emotional and operational triggers beneath the initial request.

In workplaces, these deeper issues often connect to organizational culture. For example, a request for faster workflows sometimes indicates a real need for predictability or reduced chaos, rooted in communication or authority structures rather than the system itself. Recognizing these patterns enables more effective design decisions by addressing root causes instead of just symptoms.

Intentional silence is another valuable technique. After asking a question, I resist filling the pause, giving participants space to think and speak freely. This silence often prompts unfiltered insights, especially when someone is on the verge of articulating something new. Allowing this space helps participants trust and own their insights, leading to more meaningful outcomes.

Future-Focused Exploration and Empowering Language

I also employ future-anchoring questions like, “Imagine it’s six months after launch — what does success look like for you?” or, “If the system made your job easier in one specific way, what would that be?” These help participants shift from immediate concerns to aspirational thinking, revealing priorities such as autonomy or coordination that guide design principles.

Tone and language are critical for psychological safety. I aim to make discovery feel inviting, often assuring participants, “There’s no wrong answer here,” or encouraging them to think out loud. When people use absolutes — “We always have to redo this,” “No one ever gives us the right information” — it signals where they feel stuck. I gently challenge these constraints by asking, “What might need to change for that to be different?” This opens possibilities and helps distinguish between real and internalized limitations. Coaching-based discovery is key to uncovering and addressing these constraints for lasting change.

Reflections and Takeaways

Coaching Tools as Foundational Practice

Initially, I viewed coaching tools as separate from implementation work, and more of an optional soft skill than a crucial element. Over time, my outlook changed: I saw these tools as fundamental to successful outcomes. I noticed that the best results happened when participants truly took ownership of the insights we discovered together. That sense of ownership was strongest when the understanding came from them, even with my guidance. Insights gained this way tend to last longer and have a greater impact.

My approach to discovery has evolved significantly over time. Initially, I viewed discovery as a process focused on extracting insights from users. More recently, it has transitioned into facilitating users’ own self-discovery, enabling them to articulate intuitions and knowledge that may have previously been unexpressed. This progression from a transactional checklist to a collaborative and transformative meaning-making practice has had a substantial impact on my design methodology.

Efficiency through Early Alignment and Clarity

Contrary to prevailing assumptions, coaching-based discovery does not impede project timelines. Although it demands greater initial investment of time, the resulting enhanced alignment and mutual understanding often expedite progress. Early engagement in substantive discussions enables teams to minimize rework, clarify decision-making processes, and avoid misinterpretations, which can ultimately result in projects being completed ahead of schedule due to unified objectives.

Efficiency is driven by clarity. When users feel acknowledged and their perspectives are incorporated, their level of engagement and willingness to collaborate increases. The trust established during these interactions persists throughout testing, feedback, and rollout stages, mitigating many subsequent problems that typically occur when user requirements are not considered from the outset.

Strong Implementation Questions Are Strong Coaching Questions

At their core, effective implementation questions are essentially strong coaching questions. These are fuelled by curiosity, maintain a non-judgmental tone, and aim to empower others. Instead of guiding someone toward a set answer, such questions encourage individuals to uncover their own insights about the work.

Regardless of the type of discovery — be it design, implementation, or workflow — insight comes from those directly involved. Coaching goes beyond mere technique; it represents a mindset based on the belief that people already hold valuable wisdom. The coach’s job is to help draw out this knowledge, using thoughtful questions.

A key moment in coaching-based discovery happens when someone has a sudden realization, saying things like, “I’ve never thought about it that way,” or “Now I understand why this keeps happening.” These moments are where improvements in design and implementation begin.

Such realizations act as anchors throughout a project. When team members shift their understanding, these breakthroughs can be revisited during times of complexity or tough decisions, providing direction as a “north star” to keep teams aligned.

Coaching is not just a resource, it should be demonstrated in everyday interactions. As teams experience its benefits, they often adopt coaching practices with each other, leading to genuine transformation that extends past individual projects and influences wider workplace culture.

Ultimately, the real value of this work lies not just in the solutions themselves, but in the conversations that reshape how people engage with their work.

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Understanding Agentic AI: Key Insights for Retail Leaders

Introduction

The term “Agentic AI” is now commonly used in industry conversations, yet its meaning often ranges from simple automation tools to advanced digital workers. Retail leaders typically envision Agentic AI as a capable junior employee able to understand goals, reason, take action across platforms, and learn, setting high expectations for implementation.

This broad perception is close to the research-based definition: systems that pursue goals, understand context, plan, act, and collaborate with other agents. In practice, however, many solutions labeled as agentic simply combine automation, machine learning, language models, and APIs.

In this discussion:

  • Agentic AI means sophisticated, enterprise-level autonomous systems focused on defined objectives.
  • Autonomous Workflow Orchestration (AWO) reflects current retail tools: smart workflows still guided by human priorities.

Key questions covered:

  • What systems are in use today?
  • Which technologies are mislabeled as agentic?
  • What advancements are needed in tech, data, and processes to move from AWO to true agentic AI?

What People Think “Agentic AI” Is (And Why That Matters)

Many view an “agent” as more than a rule-based system. They expect it to handle complex tasks, strategize, and act independently. Technically, such agents should:

  • Understand goals rather than just react to inputs.
  • Make multi-step plans involving various systems.
  • Select and sequence tools or APIs appropriately.
  • Adapt when things go off course.

This distinction affects leadership expectations: if leaders think they’re getting fully capable agents, they may incorrectly assign responsibility. Confusing automation with autonomy can lead to inadequate oversight and accountability gaps. Accurate descriptions of “agentic AI” are crucial, as mislabeling advanced workflow automation may cause governance failures when organizations rely on abilities these systems don’t possess.

What AWO Really Is: Architectural Reality, Not Just Buzz

AWO is an integrated stack supporting autonomous workflows:

  • The Workflow/RPA layer manages tasks between systems.
  • Machine learning models assess risk, sort tickets, predict demand, and spot patterns.
  • LLMs process unstructured text, summarize, draft, and converse.
  • The integration fabric links retail and supply chain apps with APIs and queues.
  • Rules and policies set boundaries, manage thresholds, and handle approvals.

Compared to traditional automation, AWO uses machine learning to trigger workflows based on data, rather than fixed rules. LLMs interpret complex inputs, enabling routing by predictions or classifications instead of basic logic. While adaptable, these systems don’t independently pursue high-level goals; they follow designed workflows.

In retail, AWO can validate return requests, resolve delivery issues, and spot shelf gaps from images. Problems occur when model assumptions fail, rules conflict, or policies change. Because workflows drive actions, solutions often require process redesign, underscoring the gap to fully goal-driven, agentic systems.

The Spectrum of Automation and Agentic Behaviour in Retail

The spectrum of automation and agentic behaviour provides leaders with a framework to benchmark their current capabilities and chart a path for future development. Retail organizations typically progress through four distinct stages, each with its own strengths, weaknesses, and operational implications.

The spectrum: Automation → AWO → Narrow Agents → Agentic Ecosystems

Stage 1: Rules Automation

At this stage, automation is driven by macros, scripts, and Robotic Process Automation (RPA) bots. The primary advantage of this approach is its predictability and controllability. However, these systems are inherently brittle; any change in user interface or data format can cause the automation to break, leading to disruption in operations.

Stage 2: Adaptive Workflow Orchestration (AWO)

AWO systems can adapt within established workflows but lack the ability to modify the workflow structure itself. These systems remain workflow-centric but incorporate machine learning (ML) and large language models (LLMs) to make smarter decisions within the flow. The strength of AWO lies in its ability to handle greater variation and reduce manual handoffs. The limitation, however, is that goals are externally defined and the workflow logic is still hard-coded, constraining the system’s ability to respond to new or unexpected challenges.

Stage 3: Narrow Agents

Narrow agents introduce the capacity to make decisions based on trade-offs, not just rigid rules. These domain-specific agents can reason within a tightly defined scope. For example, a pricing agent can select among pre-approved strategies within established guardrails, while a disruption-management agent may propose and sometimes execute remediation steps. At this stage, the distinction between a “smart workflow” and an “agent” begins to blur, as the system starts to optimize rather than merely execute scripted actions.

Stage 4: Agentic Ecosystems

In this most advanced stage, agents operate under high-level goals and possess autonomy in selecting methods. Multiple agents with different roles and perspectives collaborate, sharing goals or negotiating trade-offs such as margin, service level, and inventory risk. These agents are empowered to choose their tools and may even propose new process variants, reflecting a dynamic and adaptive approach to retail operations.

Current State and Key Takeaway

Most retailers today find themselves between Stages 2 and 3, with Adaptive Workflow Orchestration present in several workflows and a few narrow agent-like pilots underway. Despite these advancements, governance, data foundations, and integration patterns remain rooted in traditional workflow-centric models, rather than in structures that support agents capable of initiating or reshaping work.

Importantly, progression through these stages cannot be achieved in a single leap. Each stage introduces new potential failure modes, ranging from simple bot breakdowns to workflows making poor decisions, to agents optimizing for objectives that may not align with organizational goals. Leaders must be deliberate and explicit about which stage they are designing for, ensuring that systems and processes are properly aligned with their intended capabilities.

Practical Examples: Where Automation Excels and Where It Falls Short

Automated Refunds and Returns: The Limits of Autonomy

Automated refund and return processes demonstrate how advanced orchestration systems streamline routine workflows. The standard – or “happy path” – scenario is handled efficiently: the system classifies the return reason, checks applicable policies, processes the refund, and notifies the customer. However, the process becomes more complex when exceptions arise. Critical questions include: Who is responsible for resolving edge cases such as suspected fraud, chronic returners, or policy conflicts? Is the automated system empowered to weigh cost against customer goodwill, or does that authority remain with humans?

Typically, automation is permitted only within a defined risk band. For instance: if the risk score is below a certain threshold (X), the system approves the refund automatically; if the score falls between X and Y, the case is escalated; if above Y, the refund is blocked. This illustrates classic Adaptive Workflow Orchestration (AWO) – the system applies a business’s predetermined risk appetite on a larger scale but does not set or adjust that appetite itself.

Computer Vision in Planogram Checks: From Task Generation to Strategic Action

In another example, computer-vision-powered systems conduct planogram checks, detecting gaps on shelves and prompting the workflow to generate corrective tasks. The deeper, strategic questions are: Can the system reprioritize these tasks based on factors such as sales impact or labour constraints? Is it able to propose alternative merchandising layouts in response to local store behaviour?

At present, the answer is generally no. The system continues to follow a linear process: detect an issue, then raise a task. True agentic behaviour would involve the system analyzing a store’s unique traffic patterns and sales profile, proposing a new display layout, simulating the impact, and rolling out the change as a test.

The Analytical Gap in Current Automation

A common pattern emerges across these scenarios. The “sense” and “act” phases of automation are becoming more intelligent and hands-off. Yet, determining the broader objectives – deciding what trade-offs are acceptable and which “game” to play – remains mostly a human-driven and static process.

This highlights a key analytical gap. While much is said about “autonomous AI,” closer examination reveals that most autonomy is local and tactical, not global and strategic. As a result, Adaptive Workflow Orchestration delivers strong return on investment (ROI) but does not fundamentally transform the underlying operating model.

A More Rigorous Look at Future Agentic Scenarios

Let’s revisit the future supply chain scenario in a more structured way. When an agent spots a disruption, it goes through several processes: monitoring data continuously, maintaining contextual awareness of business-critical variables, and communicating efficiently with other agents to coordinate responses.

The replenishment agent, in turn, considers constraints like supplier lead times and contractual limits, understands service levels and margin goals, and prioritizes options that best fit business objectives.

As more agents are added, covering margins, stores, and customer interactions, the challenges shift from simply integrating systems to ensuring all agents share accurate information, resolve conflicts, and know when to involve humans.

These issues mean automation is not just about upgrading technology. Key concerns include who defines agent goals, how often they’re reviewed, and what oversight exists for agent decisions. As a result, agentic pilots tend to focus on narrow tasks, such as dynamic pricing or local optimization, rather than handling entire supply chains. The primary hurdles relate to governance, data quality, and accountability, not just technical sophistication.

The Leadership Imperative: Why the AWO vs. Agentic AI Distinction Matters

Mischaracterizing Automated Workflow Orchestration (AWO) as fully agentic artificial intelligence can lead to notable repercussions for leadership and organizational effectiveness. When this distinction is not explicitly acknowledged, three primary challenges frequently emerge: architecture drift, risk blind spots, and talent misalignment.

1. Architecture Drift

Integrating agents into a workflow-centric environment without comprehensive planning often results in their function being limited to advanced decision points rather than serving as fundamental system components. Such an approach neglects critical design considerations including shared memory, a unified goal repository, and event-driven architecture, each essential for enabling agents to operate as integral contributors within the broader ecosystem.

2. Risk Blind Spots

The presumption that “the agent knows what it’s doing” may result in inadequate investment in vital safety and governance controls. These include:

  • Observability: Mechanisms enabling tracing and explanation of agent decisions.
  • Kill Switches: Capabilities to quickly intervene and suspend agent actions when necessary.
  • Sandboxes: Controlled environments for safely testing new agent behaviours prior to deployment.
3. Talent Mismatch

Prioritizing recruitment of only prompt engineers overlooks the comprehensive skills required for effective agentic AI implementation. Beyond technical expertise, organizations benefit from engaging:

  • Professionals skilled in designing robust machine–human workflows.
  • Individuals capable of defining agent objectives, constraints, and developing meaningful evaluation frameworks.
Retail-Specific Sequencing Challenges

Within the retail sector, misconstruing “buying agents” may result in omitting foundational activities such as:

  • Data cleansing and standardization for products, locations, and customers.
  • Streamlining process variants to minimize operational complexity.
  • Establishing standardized integrations across Order Management Systems (OMS), Warehouse Management Systems (WMS), Enterprise Resource Planning (ERP), and e-commerce platforms.

Neglecting these prerequisites often causes agentic initiatives to stagnate or devolve into isolated, non-scalable solutions. This may foster the erroneous belief that agents are inadequate, when in fact, the organization was insufficiently prepared for adoption.

Importance of Distinguishing AWO from Agentic Ecosystems

Differentiating between AWO and agentic ecosystems is imperative, as it significantly influences leadership approaches and talent requirements. While workflow enhancements primarily necessitate expertise in workflow engineering and machine learning/large language models (ML/LLM), transitioning to agentic systems demands reimagining organizational decision-making structures and recruiting individuals adept at architecting resilient socio-technical systems.

Practical Steps for Leaders: Navigating Agentic AI in Retail

If you are a CIO, COO, or Head of Digital responding to board-level questions about “agentic AI,” the following structured approach outlines what you should focus on over the next 12 to 18 months.

1. Maximize the Value of Automated Workflow Orchestration (AWO)
  • Identify five to ten high-volume, rules-based processes. Typical examples include returns management, handling order exceptions, vendor queries, and store-level tasks.
  • Redesign these processes explicitly as AWO, ensuring each has defined inputs, outputs, and key performance indicators (KPIs). Carefully consider where machine learning or large language models (ML/LLMs) can add measurable value.
  • Implement instrumentation for these flows to track and measure improvements such as reduced cycle times, lower error rates, and customer impact.
2. Develop Targeted Agent Pilot Projects
  • Deliberately design one or two narrow agent pilot initiatives. Select domains with clear objectives and manageable risks, such as dynamic pricing within set ranges, markdown optimization, or tuning localized assortments.
  • Allow agents to propose actions within predetermined guardrails. Initially, keep humans in the approval loop, gradually shifting to exception-only review as confidence in the system grows.
  • Treat these pilots as experiments in operational autonomy, not just as new digital tools. Document and analyze any challenges encountered, including data quality issues, policy conflicts, or trust barriers.
3. Lay the Foundation for “Agent Readiness”
  • Data: Clearly define what data agents will need to operate cross-functionally across the organization.
  • Events: Transition from nightly data batches to real-time event streams for key operational signals.
  • Governance: Establish an “autonomy matrix” to clarify which decisions can be fully automated, which require human review, and which should remain exclusively human-driven for the time being.

By systematically following these three steps, you will be building the necessary infrastructure and capabilities to progress from today’s orchestrated copilot models to tomorrow’s more autonomous agentic ecosystems, without exposing your organization to undue risk or succumbing to industry buzzwords.

Reframing “Progress” in Retail AI

The core message is not that “Agentic AI is years away, so wait,” but rather: “Retail is currently experiencing an AWO phase that offers notable value, and the approach taken to AWO will either position businesses for agentic ecosystems in the future or pose significant challenges later.”

If AWO implementations are opaque, rigid, and confined to singular applications, they limit long-term progress. Conversely, instrumented, integrated, and well-governed AWOs serve as foundational platforms for developing agent-based systems. While the underlying technologies may be similar, the resulting strategic trajectories differ substantially.

For organizational leaders, the critical consideration is not simply whether agents have been adopted, but whether today’s automation strategies are being designed to enable greater autonomy in the future, should that become desirable. Affirmative action in this regard ensures that organizations are leveraging current capabilities to strategically prepare for a transition toward autonomous retail operations.

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Human-Centered Public Service: Making Government Work for Everyone

Design in the public sector has a unique power: one improvement can positively affect millions without requiring downloads, purchases, or even drawing attention to itself.

Introduction

Government digital services have a huge impact on our daily lives, much more than most private-sector products. Yet, many of these digital experiences are frustrating, they’re often difficult to use, with hard-to-find information, forms that aren’t accessible, confusing processes, outdated designs, and systems that cater more to internal needs than to people’s real-world problems.

However, things can change. When governments apply human-centered design, the results are significant. Accessible and user-friendly online government resources help strengthen relationships with citizens by providing better, more direct services that truly address public needs.

Design with Constraints, Not Against Them

Government projects must navigate an array of constraints, including legislation, privacy requirements, security protocols, and rigorous accessibility standards such as WCAG 2.1 AA or AODA. Unlike private organizations that serve specific user groups or customer bases, government services are required to address the needs of the entire population. The complexity of user requirements and the diversity of stakeholders can vary significantly according to the nature of the service provided.

These limitations are frequently perceived as obstacles; however, they function as essential guardrails. Highly inclusive, stable, and usable public services result from integrating these restrictions into the design process rather than resisting them.

Government transformation is often envisioned as dramatic system-wide change, yet substantive progress typically stems from targeted efforts to reduce friction at crucial points within the service delivery process. For example, at Ontario’s Ministry of Transportation (MTO), optimizing the completion time of a high-volume digital form by 40% led to immediate and measurable improvements for thousands of residents. Meaningful advancements in public service delivery are achieved through incremental, focused enhancements.

Collaborate Directly With Those Most Affected

In successful project execution, valuable insights that drive innovation are seldom derived from requirements documents alone. Rather, they emerge through engagement with individuals who utilize tools routinely, as well as those assisting citizens in navigating these resources. Their firsthand experiences represent the most significant source of user experience research.

For this reason, it is imperative to conduct comprehensive user research prior to initiating any project, ensuring that all relevant stakeholders are involved in this process. While this approach may require considerable effort and coordination, and must address privacy, regulatory, and other considerations before reaching out to stakeholders, it remains a crucial step. Properly conducting user research ensures digital solutions are designed and developed to fully meet the needs of all identified stakeholders.

Accessibility Comes First

Meeting accessibility standards is fundamental to effective public service design, not just a task to complete. Genuine accessibility involves planning from the outset for users with varied needs, abilities, technologies, and circumstances.

It goes beyond legal and regulatory compliance; it is an essential principle that governments must uphold to guarantee inclusion and equal access to digital services for everyone.

For example, accessible design may include using clear language, providing alternative text for images, ensuring keyboard navigation is possible, adapting content for screen readers, and considering colour contrast for users with visual impairments.

By integrating these considerations early in development, governments can better serve people with disabilities, older adults, and others who might face barriers in accessing online resources.

Clarity Drives Government Success

Government services don’t have to be showy; they should be:

  • Predictable, citizens should know what to expect at every stage, such as consistent wait times for processing applications or renewals.
  • Consistent, procedures and outcomes need to remain the same regardless of region or department, so everyone receives equal treatment and support.
  • Accessible, services should be usable by people with different abilities, languages, and technology access – think forms that work on mobile devices or support screen readers.
  • Understandable, instructions must be clear and available in multiple languages to help users avoid confusion and reduce mistakes or delays.
  • Resilient, systems should continue working in emergencies or high demand, ensuring people can get help even during natural disasters or network outages.

Whether people are renewing a license, applying for benefits, or filing a report, clear and straightforward processes are far more important than creating “delightful interactions.” For example, an easily navigable online portal and step-by-step checklists matter more to most users than flashy graphics or animations.

Effective Government Design Is Unseen

Effective design is often invisible, not because it lacks importance, but because it eliminates obstacles that once seemed unavoidable. For instance, automatic data validation can prevent common entry errors, and pre-populated fields can make long forms easier to complete, quietly streamlining tasks that would otherwise frustrate users.

Design in the public sector has a unique power: one improvement can positively affect millions without requiring downloads, purchases, or even drawing attention to itself. Updating a government website to simplify navigation or making forms shorter could save citizens countless hours collectively, all without any need to advertise the change.

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