Usability and User Experience (UX)
Topics: Human-centered design, usability engineering, accessibility, and interaction design
UX Skills for Business Strategy: Articulating Impact for Product, User, and Business Outcomes
Torrey Podmajersky, Maya Elise Joseph-Goteiner, and Kim Mats Mats. Santa Rosa, CA: O’Reilly Media. 2026. 494 pages, including index.
Index Terms — Business strategy, impact, organizational value, user experience, UX skills
Reviewed by Guiseppe Getto, IEEE Member, Professor at Mercer University, Macon, GA (getto_ga@mercer.edu)
Review posted Oct 1, 2026
UX Skills for Business Strategy: Articulating Impact for Product, User, and Business Outcomes, by Torrey Podmajersky, Maya Elise Joseph-Goteiner, and Kim Mats Mats, is a practical reference for user experience (UX) professionals who need to connect their work to business outcomes. The book’s central claim is straightforward: UX work is most valuable when practitioners can explain not only what they made, but what difference that work made for users, products, organizations, and the business. For readers of IEEE Transactions on Professional Communication, this is familiar territory. Technical communicators have long had to justify the value of work that is often essential but not always visible.
The book is written for UX professionals, UX managers, product leaders, founders, and others who make decisions about user experiences. It will be especially useful for practitioners who already know how to do UX work but struggle to explain its organizational value. This is not a how-to guide for conducting research, creating content models, or building design systems. Instead, it is a reference for choosing which UX skills to use, understanding the impacts those skills can make, and communicating those impacts in language that business stakeholders recognize.
The main contribution of the book is that it makes business strategy less abstract for UX practitioners. The authors argue that UX professionals often talk too much about process and deliverables when what organizations need to understand is impact. In other words, the value of UX is not the journey map, prototype, content audit, or research report by itself. The value is what those activities make possible: reduced support costs, increased user confidence, better product-market fit, reduced risk, improved alignment, and so on.
The book is built around a useful pairing: 41 business impacts and 99 UX skills. Readers can start with an impact they need to make and identify the UX skills that might help them make it. Or they can start with a skill they already use and identify the impacts that skill might create. This structure makes the book less like a textbook and more like a working reference.
The book is organized into four chapters, with Chapters 2 and 3 doing most of the work. Chapter 1 explains how to use the book. The authors are clear that this is not a “read once and done” book. It is an atlas or toolkit, meant to be entered through a problem, a skill, or an organizational goal. The opening chapter also introduces the core relationship between skills and impacts: UX skills are the means; impacts are the organizational effects those skills help create.
Chapter 2 defines impacts and organizes them into six categories: financial, user, product, risk, operational, and management. This taxonomy is one of the book’s strengths. It acknowledges that UX does not only produce “happy users.” UX can reduce support costs, improve emergency response, increase organizational alignment, reduce regulatory risk, and create more inclusive work environments. This broader framing matters because it gives practitioners a way to talk about UX without reducing it to aesthetics or customer satisfaction.
Chapter 3 is the bulk of the book and catalogues 99 UX skills. These skills range from familiar research and design practices, such as interviewing users, creating user journeys, prototyping experiences, and evaluating design solutions, to skills that are especially relevant to technical communication, such as auditing content, creating a content strategy, controlling terminology, editing for accuracy, creating how-to content, managing publishing channels, structuring content for reuse, and establishing content operations. The authors organize these skills across a practical lifecycle: solving the right problem, solving the problem right, realizing the solution, and continuous improvement.
Chapter 4 addresses attitudes that amplify success. This chapter is shorter but important because it recognizes that UX impact does not happen through methods alone. Skills require judgment, collaboration, diligence, adaptability, and the ability to understand organizational perspectives. This is a useful corrective to overly method-driven accounts of UX work.
For technical communication, the book’s value is that it makes visible how much of UX strategy depends on communication work. Many of the skills the authors identify are familiar to technical communicators: content strategy, terminology control, style guides, localization, how-to content, information architecture, taxonomy work, content management system adoption, content reuse, and content operations. The book also offers language for explaining why these activities matter beyond the documentation team. They can reduce support costs, increase user understanding, improve consistency, reduce risk, and enable organizational alignment. That makes the book useful not only for UX professionals, but also for technical communicators who need to advocate for their work in product-centered organizations.
The book’s structure is its major strength. The cross-referenced relationship between impacts and skills makes the book immediately usable. A UX manager could use it to plan team development. A practitioner could use it to write a performance review or portfolio case study. A product leader could use it to decide what kind of UX expertise to hire. This flexibility is one of the book’s best features.
Another strength is the authors’ refusal to position business goals and human-centered values as opposites. They argue that business strategy can function as a valuable set of constraints. That framing is useful because it avoids the false choice between serving users and serving organizations. At the same time, the book does not pretend that every business goal is automatically good for users. Its emphasis on impact, conditions for success, and risks gives readers tools for thinking more carefully about where UX work can and should intervene.
The book’s main limitation is that it is broad by design. Readers looking for detailed instruction in any one UX skill will need other resources. The authors are explicit about this, but it still means the book works best for readers who already have some grounding in UX or technical communication. A second limitation is that the impact mappings are necessarily generalized. In actual organizations, the relationship between a UX activity and a business outcome is rarely clean. Readers will need to adapt the book’s language to their own contexts and gather evidence carefully.
Overall, UX Skills for Business Strategy is a strong resource for practitioners who need to connect UX work to organizational value. Its greatest contribution is not that it invents new UX methods, but that it helps practitioners explain the value of methods they may already use. For technical communicators, the book is especially useful because it validates many communication-centered practices as strategic UX skills. It also provides language for making the case that content, research, design, and operations are not peripheral to business strategy. They are often how strategy becomes usable.
UX Skills for Business Strategy is recommended for UX professionals, technical communicators, UX managers, product leaders, and instructors teaching UX or content strategy. Its greatest value is as a practical reference for articulating the impact of UX work in ways that connect user-centered practice to business outcomes.
Designing AI Interfaces: Design Principles for Creative and Autonomous AI
Louise Macfadyen. Santa Rosa, CA: O’Reilly Media, Inc. 2026. 210 pages, including index.
Index Terms — Agentic systems, human-computer interaction, interface design, large language models, user experience
Reviewed by Rohith Siddhartha Bheemreddy, IEEE Member and a Senior Machine Learning Engineer at webAI, Austin, TX (rohithsiddharthareddy@gmail.com)
Review posted Oct 1, 2026
In Designing AI Interfaces: Design Principles for Creative and Autonomous AI, Louise Macfadyen offers practitioners a working mental model of large language models (LLMs) and autonomous systems, together with a vocabulary for designing the interfaces built on top of them. Her premise is stated early and without inflation: “LLMs merely reflect the patterns and logic embedded in human language, not a greater understanding of the universe” (p. 2). The book delivers on that premise. It works best as a shared primer for cross-disciplinary teams, or as a course text in interaction design or data ethics, compressing into six chapters what otherwise takes sustained hands-on work. Its stated audience is product designers with limited technical background, and the resulting book sits less comfortably than that suggests. Technical passages assume more than a designer typically brings, while design passages assume less than a designer already knows, and the reader who fits both descriptions is most often someone building with LLMs rather than someone shaping their surfaces. The mismatch does not spoil the book, but different readers will find different halves useful.
Macfadyen organizes the material around three stages: input, computation, and output, introduced in the first chapter and used as the backbone for the three chapters at the center of the book. Inputs are where intention enters the system, whether typed or inferred from context. Computation is the interpretive middle, which she calls paradoxical for designers because it shapes the result most and is visible least. Outputs return, already formatted and filtered. Each chapter opens with a case drawn from computing history: T9 predictive text, Google Wave, the Multics command shell, the Apollo 11 program alarm, clinical decision support systems, and Clippy. Only two of those are outright failures; the more interesting cases are the ones that are not, such as the Apollo guidance computer that shed low-priority tasks exactly as designed and terrified its crew anyway.
The chapter on inputs contains the framework most likely to outlast the book. Macfadyen argues that user intent arrives through three simultaneous channels: implicit context that the system gathers unasked, explicit prompting, and direct manipulation through the selections and gestures inherited from graphical interfaces. Dan Saffer’s foreword calls this a diagnostic tool rather than a taxonomy, observing that a failed artificial intelligence (AI) feature is always traceable to a breakdown in one of the three, and that framing is what gives the model its practical value. The computation chapter then opens the middle stage, moving through tokenization, routing, and token-by-token generation before arriving at latency, which she treats as a design surface rather than an unavoidable cost. Her strongest argument concerns error. Conventional software failures are mechanical and detectable, which is why interfaces can offer messages and retries. Model failures often are not, and the consequence is that “the most dangerous errors often arrive wrapped in perfect grammar, formatted beautifully, and delivered with algorithmic confidence” (pp. 111–112). Fluency reads as reliability, and nothing in the interface contradicts it.
The output chapter builds on that insight. Macfadyen separates verifiability, meaning whether a claim can be checked, from grounding, meaning why the system produced it, and she is right to be skeptical of confidence indicators. A spell-checker’s percentage is legible and reproducible; a model’s is the product of billions of parameters in latent space and only looks like the same kind of number. Her prescription is to stop asking how confident the model is and start asking whether the user can independently validate the claim. The treatment of disclosure is current and specific, covering California’s bot disclosure statute, the EU AI Act, the C2PA standard, and the withdrawal of OpenAI’s own classifier at twenty-six accuracy.
The final chapter turns to agentic systems. Macfadyen surveys five implementation patterns: Reflection, Tool Use, Planning, Multiagent Collaboration, and ReAct, then does something more useful than cataloguing them: she concedes the patterns are invisible to the people using the product and shifts to the interface moments where they surface. That yields a practical vocabulary of decomposition, sequencing, delegation, checkpoints, rollback, permissions, and sources, along with three principles: reveal the plan before acting, prioritize what matters most, and design for shared control. The governing observation, that “independence without accountability creates anxiety” (p. 174), states the design problem of autonomous systems about as economically as it can be stated. Her point that an iterating agent cannot display step three of five, because no fixed number of steps exists, that shows engagement with the systems themselves rather than with the language used to sell them.
The technical primer that supports all of this is mostly sound, though a reader who works with these systems will find errors. TensorFlow is described as “one of Google’s first open source models” (p. 3) when it is a framework rather than a model. MT Bench is marked as a “Model Test Bench” and its prompts described as “evaluated by people, not machines” (p. 34), although the name refers to multi-turn evaluation and the benchmark is known precisely for using a model as the judge. Most awkwardly, Chapter 2 introduces the Model Context Protocol (MCP) correctly, and Chapter 5 then answers the question “How do I set up an MCP server?” (p. 118) with instructions for installing a Java Development Kit to run a Minecraft Coder Pack. The example is there to demonstrate output formatting, and the collision passes without comment. None of this damages the design argument, but it matters in a book whose stated purpose is to give designers reliable footing when they talk to engineers.
The book’s relevance for professional communicators lies with where it locates risk. Macfadyen treats the language of an interface as a primary surface on which trust is won or lost, and much of what she prescribes is a communication artifact: error copy, refusal wording, disclosure statements, progress language, and the labeling of provisional output. Her framework for organizational maturity extends the same argument, reading incoherent AI products as symptoms of broken information flow between design, engineering, and product rather than as defects in the model. Saffer, writing from Carnegie Mellon’s Human-Computer Interaction Institute, singles out that framework as the section most worth reading and least likely to be consulted. The book cites no professional or technical communication scholarship, drawing instead on Nielsen Norman Group and human-computer interaction research, so the reader has to make the connection which is worth making.
Two limitations deserve mention. The first is evidentiary. The book mixes real studies with scenarios explicitly framed as hypothetical, among them a sixty-seven percent reduction in proposal generation time offered as something an organization might achieve rather than something observed. In chapters arguing for verifiability, the asymmetry is conspicuous. Macfadyen can strengthen this in a second edition by separating documented results from illustrative ones. The book would also benefit from including a bibliography as sources are named inline but never collected, which makes them difficult to follow up on. The second limitation concerns evaluation. Macfadyen recommends many patterns without offering a method for testing whether any of them improved a given product. For the second edition, a short chapter on evaluating interface decisions would turn the book from a catalogue into a practice.
I recommend Designing AI Interfaces for two reasons. For practitioners, it assembles in one place a perspective that would otherwise be acquired piecemeal, by working across many AI products and noticing how their behavior shifts as the underlying models change. For academics, it supplies terminology precise enough to teach, at a moment when the field has more opinion than shared vocabulary. Readers who have already built and shipped these systems will find much of the book familiar and should come to it less for discovery than for language they can carry into conversations with colleagues who have not. The book’s most durable contribution may be its insistence, sustained across six chapters, that fluency is not accuracy, and that the interface is where the difference has to be made visible.
The Staff Designer: Grow, Influence, and Lead as an Individual Contributor
Catt Small. New York, NY: Rosenfeld Media. 2025. 245 pages; includes index.
Index Terms — Career development; design leadership; individual contributors; UX design
Reviewed by Lokesh Karanam, RR Donnelley (lokeshkaranam3@gmail.com)
Review published June 17, 2026
Catt Small’s The Staff Designer: Grow, Influence, and Lead as an Individual Contributor is written primarily for user experience (UX) practitioners navigating or aspiring to staff-level individual contributor roles in product organizations, especially those working in digital products and services. Design managers, product leaders, and professionals in related fields such as content design and UX research can also benefit from the book’s articulation of expectations, scope, and influence at “super-senior” levels. The book clarifies what the staff designer role is (and is not), provides tactics for operating effectively at this level, and helps readers make informed decisions about their career paths. Overall, the book achieves this purpose; it offers a clear, practical model to staff level work and provides a usable set of frameworks that organizations can apply directly in their settings.
In the early chapters, Small makes several claims about the staff role: Staff designers are a distinct group from senior designers and managers; their work is defined by scope, ambiguity, and impact, not just by title; and they lead primarily through systems thinking, strategic influence, and mentorship, without direct reports. These claims are supported by a combination of conceptual framing, example projects, and scenarios that illustrate differences in scope, responsibilities, and partnering patterns across roles. The introduction of archetypes such as architect, tastemaker, visionary, and platformer offers a useful method for understanding the different ways staff designers can create value. These archetypes also show that advanced roles often demand a mindful balancing of message, medium, and organizational context, rather than an exclusive focus on output.
Methodologically, the book is grounded in lived experience and practitioner narratives rather than formal empirical research. Small draws examples from her own career trajectory and stories from other designers and design leaders. This approach positions the book firmly within the genre of practice-oriented professional guidance rather than academic theory, which aligns well with the needs of many readers who seek immediately applicable insights in organizational settings. Its focus on expectation-setting, relationship-building, and influence strategies situates it within the broader domain of professional communication: staff designers are routinely engaged in framing problems, pitching visions, facilitating cross-functional collaboration, and communicating impact upward and across teams.
The book is particularly strong when addressing ambiguity and influence. Chapters on organizational design, time and capacity management, relationship-building, and product vision translate vague expectations about being more strategic, building influence, and demonstrating impact into concrete practices. By detailing how to structure a vision, gather qualitative and quantitative evidence, craft a persuasive case, and communicate outcomes, Small offers a practical toolkit that can inform both classroom exercises and professional development workshops focused on leadership communication and stakeholder engagement.
This book has some limitations that are important for readers to understand. Small tightly anchors the examples, language, and career structures in UX and product design. While many of the underlying principles, such as managing ambiguity, building influence without authority, and communicating value, are broadly transferable, readers in fields far from digital product development may need to do some translation to map the cases to their contexts. Also, since the book leans more towards narrative and frameworks than toward rigorous empirical verification, scholars may find it more helpful as a rich source of practice-based insight than as a theory-building text. These are not so much flaws as they are scope boundaries; the book is most powerful when read as a practitioner’s guide aimed at a well-defined community.
The Staff Designer offers a well-organized, accessible, and candid account of what it means to grow beyond senior-level roles while remaining an individual contributor. One practical suggestion for improvement could be to provide more explicit mapping from its frameworks to adjacent professions (such as software engineering, technical communication, or data roles) to make the guidance easier for readers outside of UX to apply. Another improvement would be to include brief reflective prompts or discussion questions at the end of each chapter that would make the book even more handy for use in graduate seminars or professional training programs. The book may serve as a useful supplementary text for academics who want to familiarize students with realistic accounts of leadership, influence, and communication in design-intensive organizations. Senior designers, staff designers, and design managers will appreciate its clear articulation of expectations, concrete tactics for building influence and communicating impact, and honest treatment of the tradeoffs involved in staying on the individual contributor path.
Purposeful Evaluation: A Practical Guide to Design, Development and Delivery
David Parsons. Bristol, UK: Policy Press. 2026. 348 pages, including index.
Index Terms — Evaluation methods, evidence use, impact evaluation, policy communication, stakeholder engagement
Reviewed by Prasad Maderamitla, IEEE Senior Member (prasad.madera@gmail.com)
Review published June 17, 2026
Purposeful Evaluation: A Practical Guide to Design, Development and Delivery is written for evaluators, evaluation commissioners, policy professionals, and researchers who need evaluation evidence to matter after a report is delivered. Professional communication scholars and practitioners will also find this book useful because it treats evaluation not only as a methodological exercise, but as an act of purposeful evidence design, stakeholder negotiation, reporting, and influence. David Parsons’s purpose is practical: to help readers choose, plan, deliver, and communicate evaluations that are technically sound and more likely to be used. The book’s strongest contribution is the steady insistence that good evaluation depends on fit: methods must fit the decision context, the “evaluand,” stakeholder expectations, available resources, and the communication work needed to move evidence into action (p. 3).
Part I, Starting points, establishes Parsons’s central argument with unusual clarity. He resists a narrow view in which evaluation begins with a method and ends with a report. Instead, he argues that purposeful evaluation requires a balance between technical choices and the political, organizational, and human conditions in which evidence will be interpreted. This framing is especially helpful for readers who come to evaluation from research backgrounds. The distinction among research, monitoring, and evaluation is not presented as a turf boundary, but as a way to clarify intent. Research seeks knowledge; monitoring tracks activity and performance; evaluation judges merit, worth, value, or significance related to a particular intervention and decision need. This discussion sets a strong foundation for the rest of the book.
Part II, Setting the foundations, is among the most valuable sections for professional communicators. Parsons shows that the most consequential communication problems often appear before data collection begins. Purpose has to be clarified, expectations have to be managed, and ethical commitments have to be translated into ordinary project decisions. The chapter on objectives is particularly useful because it demonstrates how vague wants can be converted into realistic evidence needs and research questions. The ethics discussion goes beyond compliance language and considers fairness, inclusion, participant briefing, and the responsibilities involved in making judgments. These chapters would serve well in a graduate course on program evaluation, public policy communication, or applied research design.
The middle portion of the book gives readers a broad, grounded tour of evaluation methods. Parsons covers process evaluation, economic evaluation, experimental and quasi-experimental impact evaluation, theory-based impact evaluation, and meta-evaluation. The approach is not a recipe book. Instead, each chapter explains the circumstances where a method is likely to be useful, the assumptions it requires, and the risks of using it mechanically. This is a welcome strength. For example, the chapters on experimental and quasi-experimental impact evaluation make clear that counterfactual reasoning is powerful, but only when design, scale, timing, comparison groups, and implementation realities support it. The chapter on economic evaluation is similarly careful; it explains cost-description, cost-effectiveness, cost-utility, and cost-benefit approaches without pretending that monetizing benefits is simple. The result is a balanced account that respects methodological rigor while warning against method worship.
Purposeful Evaluation is also timely in its treatment of theory of change and generative artificial intelligence (AI). Parsons positions theory of change as a practical framework for surfacing assumptions, pathways, evidence needs, and complexity, not as a decorative diagram added to an evaluation plan. He discusses AI cautiously, noting its potential to support scoping, literature review, data processing, analysis, and communication while acknowledging concerns about accuracy, bias, transparency, intellectual property, and trust. This measured treatment makes the book more credible. Readers looking for dramatic claims about AI will not find them; readers looking for a sober account of where AI may help evaluators will.
One of the book’s best features is its attention to the whole evaluation journey. Parts IV and V move from planning and risk management to reporting, dissemination, and evidence influence. These chapters are directly relevant to IEEE Transactions on Professional Communication readers because they treat reports, briefs, presentations, visualizations, and stakeholder interactions as part of the evidence system rather than as afterthoughts. Parsons persuasively explains that evidence does not speak for itself. Reports need structure, substantiation, plain language, and an awareness of how decision-makers will use, resist, or misunderstand findings. His emphasis on mobilizing evidence is especially important in professional communication, where the usability of information is often as consequential as its accuracy.
The book’s five-part structure moves from conceptual foundations to methods, delivery, and influence. Tables, figures, and examples help readers navigate a large amount of material. The twenty evaluation examples are especially effective: changing objectives, stakeholder demands, flawed comparators, small samples, risk foresight, and synthesis reporting. These examples make the book feel rooted in practice rather than in abstract methodological preference. The book clearly reflects Parsons’s professional experience while maintaining an instructional rather than self-promotional tone.
There are areas where the book could be improved. First, because it aims to guide newer evaluators as well as experienced practitioners, a few chapters would benefit from short end-of-chapter checklists or decision trees. Parsons already includes useful tables and purposeful tips, but a consistent closing tool would make it easier for readers to convert the advice into action. Second, the book could do more to address evaluation in highly digital or data-intensive environments outside public policy, such as platform governance, cybersecurity training, or technical product adoption. The framework applies to those settings, but readers from engineering and technology organizations may need to do some translation. Third, the evidence communication discussion is strong, but a fuller worked example of a reporting plan, from objective to data source to finding to recommendation to dissemination product, would strengthen the bridge between method and communication.
These suggestions do not diminish the book’s usefulness. Academics should read Purposeful Evaluation because it offers a strong teaching text for applied evaluation and because it frames evaluation as an interdisciplinary practice involving methods, ethics, organizational judgment, and communication. Practitioners should read it because it offers an honest account of the constraints under which evaluation occurs: imperfect timing, limited resources, shifting stakeholders, contested evidence, and decision windows that can close quickly. The book’s practical message is that evaluators cannot guarantee evidence use, but they can design and communicate evidence in ways that give it a better chance. That is a modest claim, and a valuable one. Purposeful Evaluation succeeds because it makes evaluation feel less like a technical ritual and more like disciplined, ethically aware work directed toward decisions that matter.