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As a product builder over too many years to mention, I’ve lost count of the number of times I’ve seen promising ideas go from zero to hero in a few weeks, only to fizzle out within months.

Financial products, which is the field I work in, are no exception. With people’s real hard-earned money on the line, user expectations running high, and a crowded market, it’s tempting to throw as many features at the wall as possible and hope something sticks. But this approach is a recipe for disaster. Here’s why:

The pitfalls of feature-first development

When you start building a financial product from the ground up, or are migrating existing customer journeys from paper or telephony channels onto online banking or mobile apps, it’s easy to get caught up in the excitement of creating new features. You might think, “If I can just add one more thing that solves this particular user problem, they’ll love me!” But what happens when you inevitably hit a roadblock because the narcs (your security team!) don’t like it? When a hard-fought feature isn’t as popular as you thought, or it breaks due to unforeseen complexity?

This is where the concept of Minimum Viable Product (MVP) comes in. Jason Fried’s book Getting Real and his podcast Rework often touch on this idea, even if he doesn’t always call it that. An MVP is a product that provides just enough value to your users to keep them engaged, but not so much that it becomes overwhelming or difficult to maintain. It sounds like an easy concept but it requires a razor sharp eye, a ruthless edge and having the courage to stick by your opinion because it is easy to be seduced by “the Columbo Effect”… when there’s always “just one more thing…” that someone wants to add.

The problem with most finance apps, however, is that they often become a reflection of the internal politics of the business rather than an experience solely designed around the customer. This means that the focus is on delivering as many features and functionalities as possible to satisfy the needs and desires of competing internal departments, rather than providing a clear value proposition that is focused on what the people out there in the real world want. As a result, these products can very easily bloat to become a mixed bag of confusing, unrelated and ultimately unlovable customer experiences—a feature salad, you might say.

The importance of bedrock

So what’s a better approach? How can we build products that are stable, user-friendly, and—most importantly—stick?

That’s where the concept of “bedrock” comes in. Bedrock is the core element of your product that truly matters to users. It’s the fundamental building block that provides value and stays relevant over time.

In the world of retail banking, which is where I work, the bedrock has got to be in and around the regular servicing journeys. People open their current account once in a blue moon but they look at it every day. They sign up for a credit card every year or two, but they check their balance and pay their bill at least once a month.

Identifying the core tasks that people want to do and then relentlessly striving to make them easy to do, dependable, and trustworthy is where the gravy’s at.

But how do you get to bedrock? By focusing on the “MVP” approach, prioritizing simplicity, and iterating towards a clear value proposition. This means cutting out unnecessary features and focusing on delivering real value to your users.

It also means having some guts, because your colleagues might not always instantly share your vision to start with. And controversially, sometimes it can even mean making it clear to customers that you’re not going to come to their house and make their dinner. The occasional “opinionated user interface design” (i.e. clunky workaround for edge cases) might sometimes be what you need to use to test a concept or buy you space to work on something more important.

Practical strategies for building financial products that stick

So what are the key strategies I’ve learned from my own experience and research?

1. Start with a clear “why”: What problem are you trying to solve? For whom? Make sure your mission is crystal clear before building anything. Make sure it aligns with your company’s objectives, too.
2. Focus on a single, core feature and obsess on getting that right before moving on to something else: Resist the temptation to add too many features at once. Instead, choose one that delivers real value and iterate from there.
3. Prioritize simplicity over complexity: Less is often more when it comes to financial products. Cut out unnecessary bells and whistles and keep the focus on what matters most.
4. Embrace continuous iteration: Bedrock isn’t a fixed destination—it’s a dynamic process. Continuously gather user feedback, refine your product, and iterate towards that bedrock state.
5. Stop, look and listen: Don’t just test your product as part of your delivery process—test it repeatedly in the field. Use it yourself. Run A/B tests. Gather user feedback. Talk to people who use it, and refine accordingly.

The bedrock paradox

There’s an interesting paradox at play here: building towards bedrock means sacrificing some short-term growth potential in favour of long-term stability. But the payoff is worth it—products built with a focus on bedrock will outlast and outperform their competitors, and deliver sustained value to users over time.

So, how do you start your journey towards bedrock? Take it one step at a time. Start by identifying those core elements that truly matter to your users. Focus on building and refining a single, powerful feature that delivers real value. And above all, test obsessively—for, in the words of Abraham Lincoln, Alan Kay, or Peter Drucker (whomever you believe!!), “The best way to predict the future is to create it.”

Picture this: You’re in a meeting room at your tech company, and two people are having what looks like the same conversation about the same design problem. One is talking about whether the team has the right skills to tackle it. The other is diving deep into whether the solution actually solves the user’s problem. Same room, same problem, completely different lenses.

This is the beautiful, sometimes messy reality of having both a Design Manager and a Lead Designer on the same team. And if you’re wondering how to make this work without creating confusion, overlap, or the dreaded “too many cooks” scenario, you’re asking the right question.

The traditional answer has been to draw clean lines on an org chart. The Design Manager handles people, the Lead Designer handles craft. Problem solved, right? Except clean org charts are fantasy. In reality, both roles care deeply about team health, design quality, and shipping great work. 

The magic happens when you embrace the overlap instead of fighting it—when you start thinking of your design org as a design organism.

The Anatomy of a Healthy Design Team

Here’s what I’ve learned from years of being on both sides of this equation: think of your design team as a living organism. The Design Manager tends to the mind (the psychological safety, the career growth, the team dynamics). The Lead Designer tends to the body (the craft skills, the design standards, the hands-on work that ships to users).

But just like mind and body aren’t completely separate systems, so, too, do these roles overlap in important ways. You can’t have a healthy person without both working in harmony. The trick is knowing where those overlaps are and how to navigate them gracefully.

When we look at how healthy teams actually function, three critical systems emerge. Each requires both roles to work together, but with one taking primary responsibility for keeping that system strong.

The Nervous System: People & Psychology

Primary caretaker: Design Manager
Supporting role: Lead Designer

The nervous system is all about signals, feedback, and psychological safety. When this system is healthy, information flows freely, people feel safe to take risks, and the team can adapt quickly to new challenges.

The Design Manager is the primary caretaker here. They’re monitoring the team’s psychological pulse, ensuring feedback loops are healthy, and creating the conditions for people to grow. They’re hosting career conversations, managing workload, and making sure no one burns out.

But the Lead Designer plays a crucial supporting role. They’re providing sensory input about craft development needs, spotting when someone’s design skills are stagnating, and helping identify growth opportunities that the Design Manager might miss.

Design Manager tends to:

• Career conversations and growth planning
• Team psychological safety and dynamics
• Workload management and resource allocation
• Performance reviews and feedback systems
• Creating learning opportunities

Lead Designer supports by:

• Providing craft-specific feedback on team member development
• Identifying design skill gaps and growth opportunities
• Offering design mentorship and guidance
• Signaling when team members are ready for more complex challenges

The Muscular System: Craft & Execution

Primary caretaker: Lead Designer
Supporting role: Design Manager

The muscular system is about strength, coordination, and skill development. When this system is healthy, the team can execute complex design work with precision, maintain consistent quality, and adapt their craft to new challenges.

The Lead Designer is the primary caretaker here. They’re setting design standards, providing craft coaching, and ensuring that shipping work meets the quality bar. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

But the Design Manager plays a crucial supporting role. They’re ensuring the team has the resources and support to do their best craft work, like proper nutrition and recovery time for an athlete.

Lead Designer tends to:

• Definition of design standards and system usage
• Feedback on what design work meets the standard
• Experience direction for the product
• Design decisions and product-wide alignment
• Innovation and craft advancement

Design Manager supports by:

• Ensuring design standards are understood and adopted across the team
• Confirming experience direction is being followed
• Supporting practices and systems that scale without bottlenecking
• Facilitating design alignment across teams
• Providing resources and removing obstacles to great craft work

The Circulatory System: Strategy & Flow

Shared caretakers: Both Design Manager and Lead Designer

The circulatory system is about how information, decisions, and energy flow through the team. When this system is healthy, strategic direction is clear, priorities are aligned, and the team can respond quickly to new opportunities or challenges.

This is where true partnership happens. Both roles are responsible for keeping the circulation strong, but they’re bringing different perspectives to the table.

Lead Designer contributes:

• User needs are met by the product
• Overall product quality and experience
• Strategic design initiatives
• Research-based user needs for each initiative

Design Manager contributes:

• Communication to team and stakeholders
• Stakeholder management and alignment
• Cross-functional team accountability
• Strategic business initiatives

Both collaborate on:

• Co-creation of strategy with leadership
• Team goals and prioritization approach
• Organizational structure decisions
• Success measures and frameworks

Keeping the Organism Healthy

The key to making this partnership sing is understanding that all three systems need to work together. A team with great craft skills but poor psychological safety will burn out. A team with great culture but weak craft execution will ship mediocre work. A team with both but poor strategic circulation will work hard on the wrong things.

Be Explicit About Which System You’re Tending

When you’re in a meeting about a design problem, it helps to acknowledge which system you’re primarily focused on. “I’m thinking about this from a team capacity perspective” (nervous system) or “I’m looking at this through the lens of user needs” (muscular system) gives everyone context for your input.

This isn’t about staying in your lane. It’s about being transparent as to which lens you’re using, so the other person knows how to best add their perspective.

Create Healthy Feedback Loops

The most successful partnerships I’ve seen establish clear feedback loops between the systems:

Nervous system signals to muscular system: “The team is struggling with confidence in their design skills” → Lead Designer provides more craft coaching and clearer standards.

Muscular system signals to nervous system: “The team’s craft skills are advancing faster than their project complexity” → Design Manager finds more challenging growth opportunities.

Both systems signal to circulatory system: “We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities.”

Handle Handoffs Gracefully

The most critical moments in this partnership are when something moves from one system to another. This might be when a design standard (muscular system) needs to be rolled out across the team (nervous system), or when a strategic initiative (circulatory system) needs specific craft execution (muscular system).

Make these transitions explicit. “I’ve defined the new component standards. Can you help me think through how to get the team up to speed?” or “We’ve agreed on this strategic direction. I’m going to focus on the specific user experience approach from here.”

Stay Curious, Not Territorial

The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both people to care about the whole organism, even when they’re not the primary caretaker.

This means asking questions rather than making assumptions. “What do you think about the team’s craft development in this area?” or “How do you see this impacting team morale and workload?” keeps both perspectives active in every decision.

When the Organism Gets Sick

Even with clear roles, this partnership can go sideways. Here are the most common failure modes I’ve seen:

System Isolation

The Design Manager focuses only on the nervous system and ignores craft development. The Lead Designer focuses only on the muscular system and ignores team dynamics. Both people retreat to their comfort zones and stop collaborating.

The symptoms: Team members get mixed messages, work quality suffers, morale drops.

The treatment: Reconnect around shared outcomes. What are you both trying to achieve? Usually it’s great design work that ships on time from a healthy team. Figure out how both systems serve that goal.

Poor Circulation

Strategic direction is unclear, priorities keep shifting, and neither role is taking responsibility for keeping information flowing.

The symptoms: Team members are confused about priorities, work gets duplicated or dropped, deadlines are missed.

The treatment: Explicitly assign responsibility for circulation. Who’s communicating what to whom? How often? What’s the feedback loop?

Autoimmune Response

One person feels threatened by the other’s expertise. The Design Manager thinks the Lead Designer is undermining their authority. The Lead Designer thinks the Design Manager doesn’t understand craft.

The symptoms: Defensive behavior, territorial disputes, team members caught in the middle.

The treatment: Remember that you’re both caretakers of the same organism. When one system fails, the whole team suffers. When both systems are healthy, the team thrives.

The Payoff

Yes, this model requires more communication. Yes, it requires both people to be secure enough to share responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

When both roles are healthy and working well together, you get the best of both worlds: deep craft expertise and strong people leadership. When one person is out sick, on vacation, or overwhelmed, the other can help maintain the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

Most importantly, the framework scales. As your team grows, you can apply the same system thinking to new challenges. Need to launch a design system? Lead Designer tends to the muscular system (standards and implementation), Design Manager tends to the nervous system (team adoption and change management), and both tend to circulation (communication and stakeholder alignment).

The Bottom Line

The relationship between a Design Manager and Lead Designer isn’t about dividing territories. It’s about multiplying impact. When both roles understand they’re tending to different aspects of the same healthy organism, magic happens.

The mind and body work together. The team gets both the strategic thinking and the craft excellence they need. And most importantly, the work that ships to users benefits from both perspectives.

So the next time you’re in that meeting room, wondering why two people are talking about the same problem from different angles, remember: you’re watching shared leadership in action. And if it’s working well, both the mind and body of your design team are getting stronger.

“Language is not merely a set of unrelated sounds, clauses, rules, and meanings; it is a totally coherent system bound to context and behavior.” — Kenneth L. Pike

The web has accents. So should our design systems.

Design Systems as Living Languages

Design systems aren’t component libraries—they’re living languages. Tokens are phonemes, components are words, patterns are phrases, layouts are sentences. The conversations we build with users become the stories our products tell.

But here’s what we’ve forgotten: the more fluently a language is spoken, the more accents it can support without losing meaning. English in Scotland differs from English in Sydney, yet both are unmistakably English. The language adapts to context while preserving core meaning. This couldn’t be more obvious to me, a Brazilian Portuguese speaker, who learned English with an American accent, and lives in Sydney.

Our design systems must work the same way. Rigid adherence to visual rules creates brittle systems that break under contextual pressure. Fluent systems bend without breaking.

Consistency becomes a prison

The promise of design systems was simple: consistent components would accelerate development and unify experiences. But as systems matured and products grew more complex, that promise has become a prison. Teams file “exception” requests by the hundreds. Products launch with workarounds instead of system components. Designers spend more time defending consistency than solving user problems.

Our design systems must learn to speak dialects.

A design dialect is a systematic adaptation of a design system that maintains core principles while developing new patterns for specific contexts. Unlike one-off customizations or brand themes, dialects preserve the system’s essential grammar while expanding its vocabulary to serve different users, environments, or constraints.

When Perfect Consistency Fails

At Booking.com, I learned this lesson the hard way. We A/B-tested everything—color, copy, button shapes, even logo colors. As a professional with a graphic design education and experience building brand style guides, I found this shocking. While everyone fell in love with Airbnb’s pristine design system, Booking grew into a giant without ever considering visual consistency.  

The chaos taught me something profound: consistency isn’t ROI; solved problems are.

At Shopify. Polaris () was our crown jewel—a mature design language perfect for merchants on laptops. As a product team, we were expected to adopt Polaris as-is. Then my fulfillment team hit an “Oh, Ship!” moment, as we faced the challenge of building an app for warehouse pickers using our interface on shared, battered Android scanners in dim aisles, wearing thick gloves, scanning dozens of items per minute, many with limited levels of English understanding.

Task completion with standard Polaris: 0%.

Every component that worked beautifully for merchants failed completely for pickers. White backgrounds created glare. 44px tap targets were invisible to gloved fingers. Sentence-case labels took too long to parse. Multi-step flows confused non-native speakers.

We faced a choice: abandon Polaris entirely, or teach it to speak warehouse.

The Birth of a Dialect

We chose evolution over revolution. Working within Polaris’s core principles—clarity, efficiency, consistency—we developed what we now call a design dialect:

Constraint	Fluent Move	Rationale
Glare & low light	Dark surfaces + light text	Reduce glare on low-DPI screens
Gloves & haste	90px tap targets (~2cm)	Accommodate thick gloves
Multilingual	Single-task screens, plain language	Reduce cognitive load

Result: Task completion jumped from 0% to 100%. Onboarding time dropped from three weeks to one shift.

This wasn’t customization or theming—this was a dialect: a systematic adaptation that maintained Polaris’s core grammar while developing new vocabulary for a specific context. Polaris hadn’t failed; it had learned to speak warehouse.

The Flexibility Framework

At Atlassian, working on the Jira platform—itself a system within the larger Atlassian system—I pushed for formalizing this insight. With dozens of products sharing a design language across different codebases, we needed systematic flexibility so we built directly into our ways of working. The old model—exception requests and special approvals—was failing at scale.

We developed the Flexibility Framework to help designers define how flexible they wanted their components to be:

Tier	Action	Ownership
Consistent	Adopt unchanged	Platform locks design + code
Opinionated	Adapt within bounds	Platform provides smart defaults, products customize
Flexible	Extend freely	Platform defines behavior, products own presentation

During a navigation redesign, we tiered every element. Logo and global search stayed Consistent. Breadcrumbs and contextual actions became Flexible. Product teams could immediately see where innovation was welcome and where consistency mattered.

The Decision Ladder

Flexibility needs boundaries. We created a simple ladder for evaluating when rules should bend:

Good: Ship with existing system components. Fast, consistent, proven.

Better: Stretch a component slightly. Document the change. Contribute improvements back to the system for all to use.

Best: Prototype the ideal experience first. If user testing validates the benefit, update the system to support it.

The key question: “Which option lets users succeed fastest?”

Rules are tools, not relics.

Unity Beats Uniformity

Gmail, Drive, and Maps are unmistakably Google—yet each speaks with its own accent. They achieve unity through shared principles, not cloned components. One extra week of debate over button color costs roughly $30K in engineer time.

Unity is a brand outcome; fluency is a user outcome. When the two clash, side with the user.

Governance Without Gates

How do you maintain coherence while enabling dialects? Treat your system like a living vocabulary:

Document every deviation – e.g., dialects/warehouse.md with before/after screenshots and rationale.

Promote shared patterns – when three teams adopt a dialect independently, review it for core inclusion.

Deprecate with context – retire old idioms via flags and migration notes, never a big-bang purge.

A living dictionary scales better than a frozen rulebook.

Start Small: Your First Dialect

Ready to introduce dialects? Start with one broken experience:

This week: Find one user flow where perfect consistency blocks task completion. Could be mobile users struggling with desktop-sized components, or accessibility needs your standard patterns don’t address.

Document the context: What makes standard patterns fail here? Environmental constraints? User capabilities? Task urgency?

Design one systematic change: Focus on behavior over aesthetics. If gloves are the problem, bigger targets aren’t “”breaking the system””—they’re serving the user. Earn the variations and make them intentional.

Test and measure: Does the change improve task completion? Time to productivity? User satisfaction?

Show the savings: If that dialect frees even half a sprint, fluency has paid for itself.

Beyond the Component Library

We’re not managing design systems anymore—we’re cultivating design languages. Languages that grow with their speakers. Languages that develop accents without losing meaning. Languages that serve human needs over aesthetic ideals.

The warehouse workers who went from 0% to 100% task completion didn’t care that our buttons broke the style guide. They cared that the buttons finally worked.

Your users feel the same way. Give your system permission to speak their language.

Today’s web is not always an amiable place. Sites greet you with a popover that demands assent to their cookie policy, and leave you with Taboola ads promising “One Weird Trick!” to cure your ailments. Social media sites are tuned for engagement, and few things are more engaging than a fight. Today it seems that people want to quarrel; I have seen flame wars among birders.  

These tensions are often at odds with a site’s goals. If we are providing support and advice to customers, we don’t want those customers to wrangle with each other. If we offer news about the latest research, we want readers to feel at ease; if we promote upcoming marches, we want our core supporters to feel comfortable and we want curious newcomers to feel welcome. 

In a study for a conference on the History of the Web, I looked to the origins of Computer Science in Vienna (1928-1934)  for a case study of the importance of amiability in a research community and the disastrous consequences of its loss. That story has interesting implications for web environments that promote amiable interaction among disparate, difficult (and sometimes disagreeable) people.

The Vienna Circle

Though people had been thinking about calculating engines and thinking machines from antiquity, Computing really got going in Depression-era Vienna.  The people who worked out the theory had no interest in building machines; they wanted to puzzle out the limits of reason in the absence of divine authority. If we could not rely on God or Aristotle to tell us how to think, could we instead build arguments that were self-contained and demonstrably correct? Can we be sure that mathematics is consistent? Are there things that are true but that cannot be expressed in language? 

The core ideas were worked out in the weekly meetings (Thursdays at 6) of a group remembered as the Vienna Circle. They got together in the office of Professor Moritz Schlick at the University of Vienna to discuss problems in philosophy, math, and language. The intersection of physics and philosophy had long been a specialty of this Vienna department, and this work had placed them among the world leaders.  Schlick’s colleague Hans Hahn was a central participant, and by 1928 Hahn brought along his graduate students Karl Menger and Kurt Gödel. Other frequent participants included philosopher Rudolf Carnap, psychologist Karl Popper, economist Ludwig von Mises (brought by his brother Frederick, a physicist),  graphic designer Otto Neurath (inventor of infographics), and architect Josef Frank (brought by his physicist brother, Phillip).  Out-of-town visitors often joined, including the young Johnny von Neumann, Alfred Tarski, and the irascible Ludwig Wittgenstein. 

When Schlick’s office grew too dim, participants adjourned to a nearby café for additional discussion with an even larger circle of participants.  This convivial circle was far from unique.  An intersecting circle–Neurath, von Mises, Oskar Morgenstern–established the Austrian School of free-market economics. There were theatrical circles (Peter Lorre, Hedy Lamarr, Max Reinhardt), and literary circles. The café was where things happened.

The interdisciplinarity of the group posed real challenges of temperament and understanding. Personalities were often a challenge. Gödel was convinced people were trying to poison him. Architect Josef Frank depended on contracts for public housing, which Mises opposed as wasteful. Wittgenstein’s temper had lost him his job as a secondary school teacher, and for some of these years he maintained a detailed list of whom he was willing to meet. Neurath was eager to detect muddled thinking and would interrupt a speaker with a shouted “Metaphysics!” The continuing amity of these meetings was facilitated by the personality of their leader, Moritz Schlick, who would be remembered as notably adept in keeping disagreements from becoming quarrels.

In the Café

The Viennese café of this era was long remembered as a particularly good place to argue with your friends, to read, and to write. Built to serve an imperial capital, the cafés found themselves with too much space and too few customers now that the Empire was gone. There was no need to turn tables: a café could only survive by coaxing customers to linger. Perhaps they would order another coffee, or one of their friends might drop by. One could play chess, or billiards, or read newspapers from abroad. Coffee was invariably served with a glass of purified spring water, still a novelty in an era in which most water was still unsafe to drink. That water glass would be refilled indefinitely. 

In the basement of one café, the poet Jura Soyfer staged “The End Of The World,” a musical comedy in which Professor Peep has discovered a comet heading for earth.

Prof. Peep: The comet is going to destroy everybody!

Hitler:  Destroying everybody is my business.

Of course, coffee can be prepared in many ways, and the Viennese café developed a broad vocabulary to represent precisely how one preferred to drink it: melange, Einspänner, Brauner, Schwarzer, Kapuziner. This extensive customization, with correspondingly esoteric conventions of service, established the café as a comfortable and personal third space, a neutral ground in which anyone who could afford a coffee would be welcome. Viennese of this era were fastidious in their use of personal titles, of which an abundance were in common use. Café waiters greeted regular customers with titles too, but were careful to address their patrons with titles a notch or two greater than they deserved. A graduate student would be Doktor, an unpaid postdoc Professor.  This assurance mattered all the more because so many members of the Circle (and so many other Viennese) came from elsewhere: Carnap from Wuppertal, Gödel from Brno, von Neumann from Budapest. No one was going to make fun of your clothes, mannerisms, or accent. Your friends wouldn’t be bothered by the pram in the hall. Everyone shared a Germanic Austrian literary and philosophical culture, not least those whose ancestors had been Eastern European Jews who knew that culture well, having read all about it in books.

The amiability of the café circle was enhanced by its openness. Because the circle sometimes extended to architects and actors, people could feel less constrained to admit shortfalls in their understanding. It was soon discovered that marble tabletops made a useful surface for pencil sketches, serving all as an improvised and accessible blackboard.

Comedies like “The End Of The World” and fictional newspaper sketches or feuilletons of writers like Joseph Roth and Stefan Zweig served as a second defense against disagreeable or churlish behavior. The knowledge that, if one got carried away, a parody of one’s remarks might shortly appear in Neue Freie Presse surely helped Professor Schlick keep matters in hand.

The End Of Red Vienna

Though Austria’s government drifted to the right after the War, Vienna’s city council had been Socialist, dedicated to public housing based on user-centered design, and embracing  ambitious programs of public outreach and adult education. In 1934 the Socialists lost a local election, and this era soon came to its end as the new administration focused on the imagined threat of the International Jewish Conspiracy. Most members of the Circle fled within months: von Neumann to Princeton, Neurath to Holland and Oxford, Popper to New Zealand, Carnap to Chicago. Prof. Schlick was murdered on the steps of the University by a student outraged by his former association with Jews.  Jura Soyfer, who wrote “The End Of The World,” died in Buchenwald.

In 1939, von Neumann finally convinced Gödel to accept a job in Princeton. Gödel was required to pay large fines to emigrate. The officer in charge of these fees would look back on this as the best posting of his career; his name was Eichmann.

Design for Amiability

An impressive literature recounts those discussions and the environment that facilitated the development of computing. How can we design for amiability?  This is not just a matter of choosing rounded typefaces and a cheerful pastel palette. I believe we may identify eight distinct issues that exert design forces in usefully amiable directions.

Seriousness: The Vienna Circle was wrestling with a notoriously difficult book—Wittgenstein’s Tractus Logico-Philosophicus—and a catalog of outstanding open questions in mathematics. They were concerned with consequential problems, not merely scoring points for debating. Constant reminders that the questions you are considering matter—not only that they are consequential or that those opposing you are scoundrels—help promote amity.

Empiricism: The characteristic approach of the Vienna Circle demanded that knowledge be grounded either in direct observation or in rigorous reasoning. Disagreement, when it arose, could be settled by observation or by proof. If neither seemed ready to hand, the matter could not be settled. On these terms, one can seldom if ever demolish an opposing argument, and trolling is pointless.

Abstraction: Disputes grow worse when losing the argument entails lost face or lost jobs. The Vienna Circle’s focus on theory—the limits of mathematics, the capability of language—promoted amity. Without seriousness, abstraction could have been merely academic, but the limits of reason and the consistency of mathematics were clearly serious.

Formality: The punctilious demeanor of waiters and the elaborated rituals of coffee service helped to establish orderly attitudes amongst the argumentative participants. This stands in contrast to the contemptuous sneer that now dominates social media.  

Schlamperei: Members of the Vienna Circle maintained a global correspondence, and they knew their work was at the frontier of research. Still, this was Vienna, at the margins of Europe: old-fashioned, frumpy, and dingy. Many participants came from even more obscure backwaters. Most or all harbored the suspicion that they were really schleppers, and a tinge of the ridiculous helped to moderate tempers. The director of “The End Of The World” had to pass the hat for money to purchase a moon for the set, and thought it was funny enough to write up for publication.

Openness: All sorts of people were involved in discussion, anyone might join in. Each week would bring different participants. Fluid borders reduce tension, and provide opportunities to broaden the range of discussion and the terms of engagement. Low entrance friction was characteristic of the café: anyone could come, and if you came twice you were virtually a regular. Permeable boundaries and café culture made it easier for moderating influences to draw in raconteurs and storytellers to defuse awkward moments, and Vienna’s cafés had no shortage of humorists. Openness counteracts the suspicion that promoters of amiability are exerting censorship.

Parody: The environs of the Circle—the university office and the café—were unmistakably public. There were writers about, some of them renowned humorists. The prospect that one’s bad taste or bad behavior might be ridiculed in print kept discussion within bounds. The sanction of public humiliation, however, was itself made mild by the veneer of fiction; even if you got a little carried away and a character based on you made a splash in some newspaper fiction, it wasn’t the end of the world.

Engagement: The subject matter was important to the participants, but it was esoteric: it did not matter very much to their mothers or their siblings. A small stumble or a minor humiliation could be shrugged off in ways that major media confrontations cannot.

I believe it is notable that this environment was designed to promote amiability through several different voices.  The café waiter flattered each newcomer and served everyone, and also kept out local pickpockets and drunks who would be mere disruptions. Schlick and other regulars kept discussion moving and on track. The fiction writers and raconteurs—perhaps the most peripheral of the participants—kept people in a good mood and reminded them that bad behavior could make anyone ridiculous.  Crucially, each of these voices were human: you could reason with them. Algorithmic or AI moderators, however clever, are seldom perceived as reasonable. The café circles had no central authority or Moderator against whom everyone’s resentments might be focused. Even after the disaster of 1934, what people remembered were those cheerful arguments.

I want to discuss accessibility because it is the most important thing for making websites. Other A List Apart articles give you innovation and insight. This article will give you homework. These are just my personal views, but they’re pretty good.

I want to start off with a couple of statements, and you will agree:

1. Designers are good people. I have never heard a designer say, “I don’t care if somebody can’t read this text”, “Not my fault if somebody can’t use this device”, or “Who cares if this is confusing?”
2. Some designs exclude people. You have seen people unable to read the text on a website or app that somebody designed. You’ve seen people unable to use a physical device that somebody has designed. You’ve seen people utterly bamboozled while trying to use a service that somebody designed.

So what?

The first question is, “Is this life-or-death stuff?” The answer is, “Yes.” In my favorite essay, This Is All There Is, Aral Balkan makes the point that pretty much everything that we design can affect life events and death events. Aral gives the example of how even a straightforward bus timetable app can affect life and death events, if we design it badly:

• somebody might miss a life event, such as their daughter’s fifth birthday party; or
• somebody might miss a death event, such as the chance to say goodbye to a dying grandmother.

The next—and frustrating—question is, “Why do some designs still exclude people?” After all, we know that:

• not everybody can see perfectly;
• not everybody can hear perfectly;
• not everybody thinks the same way; and
• not everybody moves the same way.

I think the answer is that there’s too much to recall. Consider, if you will, the wide variety of topics that A List Apart articles cover. Designers are expected to remember all of that guidance, plus all of the accessibility guidance, plus so much more. It is too much.

Recognizing accessibility issues while designing

I’d like to point toward one possible solution, starting from Jakob Nielsen’s 10 Usability Heuristics for User Interface Design. These are from the mid-1990s, and—although there’s a good chance that you, gentle reader, are a lot younger than that—please bear with me. 

Seeing as the problem is that there’s too much to recall, I want to look at heuristic № 6, “Recognition rather than Recall.” Jakob Nielsen said that for users, information required to use the design should be visible or easily retrievable when needed. I suggest we tweak that to make life easier for designers. Let’s say that the information required to produce the design should be visible or easily retrievable when needed. In other words, let’s make it easier to recognise accessibility issues while we’re designing.

How are we going to do that? I really like the book A Web for Everyone—Designing Accessible User Experiences by Sarah Horton and Whitney Quesenbery. I really like this book not only because it includes a quote from me—actually two quotes, but I don’t like to boast—but because it includes personas that are perfect for helping us to recognise accessibility issues. That’s the good news. The even better news is that these personas are available now for free on the companion website to the book What Every Engineer Should Know About Digital Accessibility, again by Sarah Horton, with David Sloan this time.

Meet your users

I’m going to introduce you to these personas now:

• Vishnu, an engineer and global citizen with low vision says, “I want to be on the same level as everyone else”, “If I can adjust my screen, I can read comfortably”, and, “Translating in my head is easier with simpler sentences.”
• Trevor, a high school student with autism, says, “I like consistent, familiar places on the web”, “When I can learn the pattern, I can find my way”, and, “Reading is hard for me”.
• Steven, a deaf graphic artist and American Sign Language speaker, says, “My only disability is that everyone doesn’t sign”, and, “Without captions, it’s meaningless to me”.
• Maria, a bilingual community health worker, says, “I love this. It’s all here … when I can find it”, “When a site is confusing, I just leave”—fair enough, Maria!—and, “When I hear and see it, health information makes more sense”.
• Lea, an editor living with fatigue and pain, says, “No one gets that this really is a disability”, “Don’t make me work so hard”—please do not bombard this lady with drop-down lists—and, “Links at the top of the page make navigation easier for me”.
• Jacob, a blind paralegal and a bit of a geek, says, “The right technology lets me do anything”, and “This makes it possible to do my job”.
• Emily, who has cerebral palsy and is living independently, says, “I want to do everything for myself”, “Simpler screens are easier screens”—hell yeah, Emily!—and, “Tell me what I need in advance”.
• Carol, a grandmother with macular degeneration which affects her sight, says, “My grandkids are dragging me into the world of technology”, “I don’t understand what the screen is saying”, and, “Why can’t the text be just a little bit larger?”

I want to throw one more persona at you now, because, well, A List Apart readers are overachievers. One of my favorite authors, Cennydd Bowles—who literally wrote the book on Future Ethics—says to create Personas Non Grata. In other words, every time we design something, we have to think about what a bad guy could do with that thing, and whom that might affect.

To actually use these personas while designing, I like what Eric Meyer and Sara Wachter-Boettcher in Design for Real Life call the Designated Dissenter: for each project that you work on, one of your teams should be responsible for asking, “Will this work for Vishnu?”, “How’s Trevor going to get on with this?”, and so on. 

Then, once you’ve used the personas to recognise the accessibility issues, you can look up the guidelines for whichever platforms you’re designing for: 

• Web Content Accessibility Guidelines (WCAG) 2.2
• Accessibility designing — Material Design 3
• Accessibility — Windows apps
• Accessibility | Apple Developer Documentation
• Check your interface for accessibility (Ubuntu)

Your mission, should you choose to accept it

I told you in the introduction of this article that I would give you homework. You thought I was joking. So, here’s your homework: I want you to grab the personas from the Know About Accessibility website, and use them throughout every design project to help you recognise accessibility issues while you work—and reclaim design for everyone.

NOTE: This article is based on “Recognise,” my five-minute presentation from Interaction Design Association (IxDA) Dublin’s Defuse (Design for Use) event in 2025.

Marketing Strategy for Businesses That Have Outgrown More Tactics written by John Jantsch read more at Duct Tape Marketing

Marketing Strategy for Small Business: Why Clarity Beats More Tactics Every Time Most small businesses aren’t short on marketing activity. They’re short on the clarity that would let them do less of it. After working with hundreds of small businesses on their marketing strategy over 30 years, I’ve seen the same pattern: scattered tactics, inconsistent […]

Most Businesses Fail Because Founders Can’t Sell written by John Jantsch read more at Duct Tape Marketing

Catch the Full Episode

Episode Overview

In this episode of the Duct Tape Marketing Podcast, host John Jantsch sits down with serial entrepreneur Brian Will to unpack the real reasons most businesses fail and why it has little to do with product, market, or funding. Drawing from his experience building 10 companies worth over half a billion dollars, Brian explains how sales, not technical skill, is the true driver of business success.

The conversation explores practical sales psychology, common mistakes founders make, and actionable strategies to improve closing rates. Brian also shares his unconventional journey from high school dropout to successful entrepreneur and breaks down why mastering communication, negotiation, and human behavior is essential for any business owner.

Guest Bio

Brian Will is a serial entrepreneur who has built or co-built 10 companies across five industries, collectively valued at over $500 million at their peak. A high school dropout turned business leader, Brian specializes in sales systems, negotiation strategies, and business growth. He is the author of multiple books, including The Dropout Multi-Millionaire and The Psychology of Sales and Negotiations, where he shares proven frameworks for scaling businesses and improving sales performance.

Key Takeaways

1. Most Businesses Fail Because Founders Can’t Sell

• Failure is rarely about product or market. It is about lack of sales ability.
• Many founders are technicians who lack skills in selling and management.

2. The Biggest Sales Mistakes

• Talking too much
• Sounding like a stereotypical salesperson
• Overloading prospects with technical details

3. Sales Is a Conversation, Not a Pitch

• Asking the right questions is more powerful than presenting features.
• Customers will tell you how to close them if you listen carefully.

4. Simplicity Wins

• Communicate at a basic, clear level, around a fifth grade level.
• The more complex your explanation, the less your customer retains.

5. “No” Is the Most Powerful Word in Sales

• Every negotiation starts with “no.”
• Setting expectations and anchoring price ranges improves outcomes.

6. Never Ask for a Budget

• Customers will often mislead you.
• Instead, provide a price range and let them choose within it.

7. Match Your Sales Style to the Buyer

• Emotional buyers respond to feelings.
• Analytical buyers want data.
• Adjust your approach quickly based on cues.

8. Founders Must Build Around Their Weaknesses

• If you are not a salesperson, hire or partner with one.
• Success requires entrepreneur, technician, manager, and salesperson roles.

9. Listening Is a Competitive Advantage

• Knowing when to stop talking dramatically improves close rates.

10. Growth Comes From Letting Go of Control

• Brian’s biggest lesson is that success accelerated when he stopped trying to do everything himself and trusted more experienced partners.

Great Moments

00:02 – Why Businesses Really Fail
Brian explains that failure is usually due to lack of sales skills, not product or funding.

00:54 – Discovering a Natural Talent for Sales
Brian shares how he accidentally discovered his ability to sell insurance.

03:52 – The Three Core Sales Mistakes
Talking too much, sounding like a salesperson, and being overly technical.

05:35 – Talking Yourself Out of the Sale
A story illustrating how over explaining can lose deals.

07:04 – The Power of “No” in Negotiation
Why every negotiation starts with rejection.

09:57 – Why Technicians Fail as Business Owners
The Joe the plumber example highlights missing business skills.

12:29 – Ask Questions, Don’t Pitch
How questions reveal exactly how to close a deal.

14:47 – Practical Sales Example (Windows)
A real world walkthrough of effective sales questioning and pricing.

16:40 – Why You Should Never Ask for a Budget
Customers will mislead. Set ranges instead.

18:13 – The Lesson Brian Wishes He Learned Earlier
Success came when he stopped trying to do everything himself.

Memorable Quotes

“Most salespeople fail for exactly the same reasons. They talk too much and act like a salesperson.”

“If I can get you to have a conversation instead of selling, your closing rates will go through the roof.”

“Every single negotiation starts with no.”

“If your business fails, it won’t be because you’re bad at your craft. It will be because you can’t sell or manage.”

“The more you talk, the less they hear.”

This article contains light spoilers for Hokum. Early in the Irish horror movie Hokum, American author Ohm Bauman loses what little patience he had with the staff of the rustic hotel he’s visiting. When bellboy Alby (Will O’Connell) fails to comprehend his blunt and rude rejection, Ohm places a spoon over a candle, lets it […]

The post Hokum Cements Adam Scott as One of Our Great Everyman Actors appeared first on Den of Geek.

Age has never fully limited a screen career, and some performers remained active far longer than anyone expected. Across film history, several actors continued appearing in movies well into their nineties and even past one hundred, bringing decades of experience to the screen. These appearances were not always leading roles, but they carried a unique presence shaped by extraordinary longevity. In many cases, simply seeing them perform at that age became memorable in itself. Here are fifteen of the oldest movie stars ever to grace our screens, based on the age they reached while still appearing in films.

Mel Brooks – 98

Mel Brooks remained visible through acting and voice work in his late nineties. His continued creativity made him stand apart even among legends.

Mickey Rooney – 93

Rooney worked in films into his nineties after spending nearly his entire life in show business. Few actors sustained that kind of multi era career.

Norman Lloyd – 100

Norman Lloyd appeared in screen projects after reaching 100, extending a career that began in the 1930s. His longevity made him one of the clearest examples of a performer active across nearly an entire century of entertainment.

Olivia de Havilland – 101

Olivia de Havilland participated in filmed appearances after turning 100. Her later visibility added another chapter to a career already tied to the golden age of Hollywood.

Angela Lansbury – 96

Angela Lansbury continued acting in film projects into her nineties. Her consistency across stage, television, and cinema was exceptional.

Betty White – 99

Betty White continued film and voice appearances into her late nineties. Her popularity only grew stronger during her final decades.

Christopher Lee – 93

Christopher Lee remained active in movies well into his nineties. His late career included major franchises and continued proof of his lasting screen presence.

Dick Van D – 98

Dick Van D stayed active on screen near age 100, maintaining the charm and energy that made him famous generations earlier.

Eli Wallach – 98

Eli Wallach continued appearing in films close to age 100. His later work showed how character actors can remain valuable far beyond traditional retirement years.

Ernest Borgnine – 95

Borgnine kept acting into his mid nineties, bringing the same energy that defined his earlier decades. His work ethic became legendary.

George Burns – 98

George Burns made film appearances deep into his nineties and stayed sharp as a comic performer. Audiences continued responding to his timing and personality.

Gloria Stuart – 94

Gloria Stuart returned to major public attention late in life and continued appearing on screen in her nineties. Her later career became one of cinema’s most remarkable comebacks.

Harry Morgan – 96

Harry Morgan continued appearing on screen into advanced age after a career spanning film and television classics. His reliability lasted for decades.

June Squibb – 95

June Squibb remains a modern example of late career success, continuing to land film roles in her nineties. She proved that age does not limit audience appeal.

Kirk Douglas – 94

Kirk Douglas made later screen appearances after most stars had long retired. His continued presence reflected extraordinary stamina and cultural relevance.

The post The 15 Oldest Movie Stars to Ever Grace Our Screens appeared first on Den of Geek.

It was a different world The Devil Wears Prada opened in 20 years ago, as indicated by the fact that you could open a summer hit like The Devil Wears Prada without it being a sequel, remake, or reimagining. To be sure, the 2006 original—which also netted Meryl Streep an Oscar nod—was still based on […]

The post The Devil Wears Prada 2 Eulogizes Journalism, Movie Stardom and Last Gasps of Creativity appeared first on Den of Geek.

Age has never fully limited a screen career, and some performers remained active far longer than anyone expected. Across film history, several actors continued appearing in movies well into their nineties and even past one hundred, bringing decades of experience to the screen. These appearances were not always leading roles, but they carried a unique presence shaped by extraordinary longevity. In many cases, simply seeing them perform at that age became memorable in itself. Here are fifteen of the oldest movie stars ever to grace our screens, based on the age they reached while still appearing in films.

Mel Brooks – 98

Mel Brooks remained visible through acting and voice work in his late nineties. His continued creativity made him stand apart even among legends.

Mickey Rooney – 93

Rooney worked in films into his nineties after spending nearly his entire life in show business. Few actors sustained that kind of multi era career.

Norman Lloyd – 100

Norman Lloyd appeared in screen projects after reaching 100, extending a career that began in the 1930s. His longevity made him one of the clearest examples of a performer active across nearly an entire century of entertainment.

Olivia de Havilland – 101

Olivia de Havilland participated in filmed appearances after turning 100. Her later visibility added another chapter to a career already tied to the golden age of Hollywood.

Angela Lansbury – 96

Angela Lansbury continued acting in film projects into her nineties. Her consistency across stage, television, and cinema was exceptional.

Betty White – 99

Betty White continued film and voice appearances into her late nineties. Her popularity only grew stronger during her final decades.

Christopher Lee – 93

Christopher Lee remained active in movies well into his nineties. His late career included major franchises and continued proof of his lasting screen presence.

Dick Van D – 98

Dick Van D stayed active on screen near age 100, maintaining the charm and energy that made him famous generations earlier.

Eli Wallach – 98

Eli Wallach continued appearing in films close to age 100. His later work showed how character actors can remain valuable far beyond traditional retirement years.

Ernest Borgnine – 95

Borgnine kept acting into his mid nineties, bringing the same energy that defined his earlier decades. His work ethic became legendary.

George Burns – 98

George Burns made film appearances deep into his nineties and stayed sharp as a comic performer. Audiences continued responding to his timing and personality.

Gloria Stuart – 94

Gloria Stuart returned to major public attention late in life and continued appearing on screen in her nineties. Her later career became one of cinema’s most remarkable comebacks.

Harry Morgan – 96

Harry Morgan continued appearing on screen into advanced age after a career spanning film and television classics. His reliability lasted for decades.

June Squibb – 95

June Squibb remains a modern example of late career success, continuing to land film roles in her nineties. She proved that age does not limit audience appeal.

Kirk Douglas – 94

Kirk Douglas made later screen appearances after most stars had long retired. His continued presence reflected extraordinary stamina and cultural relevance.

The post The 15 Oldest Movie Stars to Ever Grace Our Screens appeared first on Den of Geek.

We’ve been having conversations for thousands of years. Whether to convey information, conduct transactions, or simply to check in on one another, people have yammered away, chattering and gesticulating, through spoken conversation for countless generations. Only in the last few millennia have we begun to commit our conversations to writing, and only in the last few decades have we begun to outsource them to the computer, a machine that shows much more affinity for written correspondence than for the slangy vagaries of spoken language.

Computers have trouble because between spoken and written language, speech is more primordial. To have successful conversations with us, machines must grapple with the messiness of human speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that can stymie even the most carefully crafted human-computer interaction. In the human-to-human scenario, spoken language also has the privilege of face-to-face contact, where we can readily interpret nonverbal social cues.

In contrast, written language immediately concretizes as we commit it to record and retains usages long after they become obsolete in spoken communication (the salutation “To whom it may concern,” for example), generating its own fossil record of outdated terms and phrases. Because it tends to be more consistent, polished, and formal, written text is fundamentally much easier for machines to parse and understand.

Spoken language has no such luxury. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Whether rapid-fire, low-pitched, or high-decibel, whether sarcastic, stilted, or sighing, our spoken language conveys much more than the written word could ever muster. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice Interactions

We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too (). Generally, we start up a conversation because:

• we need something done (such as a transaction),
• we want to know something (information of some sort), or
• we are social beings and want someone to talk to (conversation for conversation’s sake).

These three categories—which I call transactional, informational, and prosocial—also characterize essentially every voice interaction: a single conversation from beginning to end that realizes some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but a conversation is not necessarily a single voice interaction.

Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts seamlessly into other types. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users’ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ().

That leaves two genres of conversations we can have with one another that a voice interface can easily have with us, too: a transactional voice interaction realizing some outcome (“buy iced tea”) and an informational voice interaction teaching us something new (“discuss a musical”).

Transactional voice interactions

Unless you’re tapping buttons on a food delivery app, you’re generally having a conversation—and therefore a voice interaction—when you order a Hawaiian pizza with extra pineapple. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza (generously topped with pineapple, as it should be).

Alison: Hey, how’s it going?

Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

Alison: Can I get a Hawaiian pizza with extra pineapple?

Burhan: Sure, what size?

Alison: Large.

Burhan: Anything else?

Alison: No thanks, that’s it.

Burhan: Something to drink?

Alison: I’ll have a bottle of Coke.

Burhan: You got it. That’ll be $13.55 and about fifteen minutes.

Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Transactional conversations have certain key traits: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Here, though we again have a prosocial mini-conversation at the beginning to establish politeness, we’re after much more.

Alison: Hey, how’s it going?

Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

Alison: Do you have any halal options on the menu?

Burhan: Absolutely! We can make any pie halal by request. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you thinking about any other dietary restrictions?

Alison: What about gluten-free pizzas?

Burhan: We can definitely do a gluten-free crust for you, no problem, for both our deep-dish and thin-crust pizzas. Anything else I can answer for you?

Alison: That’s it for now. Good to know. Thanks!

Burhan: Anytime, come back soon!

This is a very different dialogue. Here, the goal is to get a certain set of facts. Informational conversations are investigative quests for the truth—research expeditions to gather data, news, or facts. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses tend to be lengthier, more informative, and carefully communicated so the customer understands the key takeaways.

Voice Interfaces

At their core, voice interfaces employ speech to support users in reaching their goals. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. Because multimodal voice interfaces can lean on visual components like screens as crutches, we’re most concerned in this book with pure voice interfaces, which depend entirely on spoken conversation, lack any visual component whatsoever, and are therefore much more nuanced and challenging to tackle.

Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

Interactive voice response (IVR) systems

Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech (TTS) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. With the advent of interactive voice response (IVR) systems, intended as an alternative to overburdened customer service representatives, we became acquainted with the first true voice interfaces that engaged in authentic conversation.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Commonplace in the corporate world, these systems were primarily designed as metaphorical switchboards to guide customers to a real phone agent (“Say Reservations to book a flight or check an itinerary”); chances are you will enter a conversation with one when you call an airline or hotel conglomerate. Despite their functional issues and users’ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

While IVR systems are great for highly repetitive, monotonous conversations that generally don’t veer from a single format, they have a reputation for less scintillating conversation than we’re used to in real life (or even in science fiction).

Screen readers

Parallel to the evolution of IVR systems was the invention of the screen reader, a tool that transcribes visual content into synthesized speech. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Screen readers represent perhaps the closest equivalent we have today to an out-of-the-box implementation of content delivered through voice.

Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 (). That same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, later recreated for computers with graphical user interfaces (GUIs) ().

With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Thanks to the introduction of semantic HTML and especially ARIA roles beginning in 2008, screen readers started facilitating speedy interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc.—into useful information,” writes Aaron Gustafson in A List Apart. “At least they do when documents are authored thoughtfully” ().

Though deeply instructive for voice interface designers, there’s one significant problem with screen readers: they’re difficult to use and unremittingly verbose. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

From the beginning, I hated the way that Screen Readers work. Why are they designed the way they are? It makes no sense to present information visually and then, and only then, translate that into audio. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. ()

In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, visual interface users have the benefit of darting around the viewport freely to find information, ignoring areas irrelevant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Disabled users who have long had no choice but to employ clunky screen readers may find that voice interfaces, particularly more modern voice assistants, offer a more streamlined experience.

Voice assistants

When we think of voice assistants (the subset of voice interfaces now commonplace in living rooms, smart homes, and offices), many of us immediately picture HAL from 2001: A Space Odyssey or hear Majel Barrett’s voice as the omniscient computer in Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And they’re rapidly gaining more attention from accessibility advocates for their assistive potential.

Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others formulated their vision for a Semantic Web “agent” that would perform typical errands like “checking calendars, making appointments, and finding locations” (, behind paywall). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others (Fig 1.1). At one extreme, everything except vendor-provided features is locked down; for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. Even today, it isn’t possible to program Siri to perform arbitrary functions, because there’s no means by which developers can interact with Siri at a low level, apart from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and certain others.

At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, programmable voice assistants that lend themselves to customization and extensibility are becoming increasingly popular for developers who feel stifled by the limitations of Siri and Cortana. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant ecosystems.

As corporations like Amazon, Apple, Microsoft, and Google continue to stake their territory, they’re also selling and open-sourcing an unprecedented array of tools and frameworks for designers and developers that aim to make building voice interfaces as easy as possible, even without code.

Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. By contrast, many development platforms like Google’s Dialogflow have introduced omnichannel capabilities so users can build a single conversational interface that then manifests as a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

Voice Content

Simply put, voice content is content delivered through voice. To preserve what makes human conversation so compelling in the first place, voice content needs to be free-flowing and organic, contextless and concise—everything written content isn’t.

Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. In this book, we’re most concerned with content delivered auditorily—not as an option, but as a necessity.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. So how do we make the content trapped on our websites more conversational? And how do we write new copy that lends itself to voice interactions?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many respects, colossal vaults of what I call macrocontent: lengthy prose that can extend for infinitely scrollable miles in a browser window, like microfilm viewers of newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

A day’s weather forcast [sic], the arrival and departure times for an airplane flight, an abstract from a long publication, or a single instant message can all be examples of microcontent. ()

I’d update Dash’s definition of microcontent to include all examples of bite-sized content that go well beyond written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. Microcontent offers the best opportunity to gauge how your content can be stretched to the very edges of its capabilities, informing delivery channels both established and novel.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can glance at a digital sign underground for an instant and know when the next train is arriving, but voice interfaces hold our attention captive for periods of time that we can’t easily escape or skip, something screen reader users are all too familiar with.

Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

Fundamentally, the legibility and discoverability of our voice content both have to do with how voice content manifests in perceived time and space.

In the 1950s, many in the elite running community had begun to believe it wasn’t possible to run a mile in less than four minutes. Runners had been attempting it since the late 19th century and were beginning to draw the conclusion that the human body simply wasn’t built for the task. 

But on May 6, 1956, Roger Bannister took everyone by surprise. It was a cold, wet day in Oxford, England—conditions no one expected to lend themselves to record-setting—and yet Bannister did just that, running a mile in 3:59.4 and becoming the first person in the record books to run a mile in under four minutes. 

This shift in the benchmark had profound effects; the world now knew that the four-minute mile was possible. Bannister’s record lasted only forty-six days, when it was snatched away by Australian runner John Landy. Then a year later, three runners all beat the four-minute barrier together in the same race. Since then, over 1,400 runners have officially run a mile in under four minutes; the current record is 3:43.13, held by Moroccan athlete Hicham El Guerrouj.

We achieve far more when we believe that something is possible, and we will believe it’s possible only when we see someone else has already done it—and as with human running speed, so it is with what we believe are the hard limits for how a website needs to perform.

Establishing standards for a sustainable web

In most major industries, the key metrics of environmental performance are fairly well established, such as miles per gallon for cars or energy per square meter for homes. The tools and methods for calculating those metrics are standardized as well, which keeps everyone on the same page when doing environmental assessments. In the world of websites and apps, however, we aren’t held to any particular environmental standards, and only recently have gained the tools and methods we need to even make an environmental assessment.

The primary goal in sustainable web design is to reduce carbon emissions. However, it’s almost impossible to actually measure the amount of CO₂ produced by a web product. We can’t measure the fumes coming out of the exhaust pipes on our laptops. The emissions of our websites are far away, out of sight and out of mind, coming out of power stations burning coal and gas. We have no way to trace the electrons from a website or app back to the power station where the electricity is being generated and actually know the exact amount of greenhouse gas produced. So what do we do? 

If we can’t measure the actual carbon emissions, then we need to find what we can measure. The primary factors that could be used as indicators of carbon emissions are:

1. Data transfer 
2. Carbon intensity of electricity

Let’s take a look at how we can use these metrics to quantify the energy consumption, and in turn the carbon footprint, of the websites and web apps we create.

Data transfer

Most researchers use kilowatt-hours per gigabyte (kWh/GB) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This provides a great reference point for energy consumption and carbon emissions. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.

For web pages, data transfer for a single visit can be most easily estimated by measuring the page weight, meaning the transfer size of the page in kilobytes the first time someone visits the page. It’s fairly easy to measure using the developer tools in any modern web browser. Often your web hosting account will include statistics for the total data transfer of any web application (Fig 2.1).

The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes. 

Reducing page weight requires a large scope. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile,” with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period (Fig 2.2). Roughly half of this data transfer is image files, making images the single biggest source of carbon emissions on the average website. 

History clearly shows us that our web pages can be smaller, if only we set our minds to it. While most technologies become ever more energy efficient, including the underlying technology of the web such as data centers and transmission networks, websites themselves are a technology that becomes less efficient as time goes on.

You might be familiar with the concept of performance budgeting as a way of focusing a project team on creating faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Much like speed limits while driving, performance budgets are upper limits rather than vague suggestions, so the goal should always be to come in under budget.

Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Web performance is often more about the subjective perception of load times than it is about the true efficiency of the underlying system, whereas page weight and transfer size are more objective measures and more reliable benchmarks for sustainable web design. 

We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also benchmark page weight against competitors or the old version of the website we’re replacing. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class. 

If we want to take it to the next level, then we could also start looking at the transfer size of our web pages for repeat visitors. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For example, visitors who load the same page multiple times will likely have a high percentage of the files cached in their browser, meaning they don’t need to transfer all of the files on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Measuring transfer size at this next level of detail can help us learn even more about how we can optimize efficiency for users who regularly visit our pages, and enable us to set page weight budgets for additional scenarios beyond the first visit.

Page weight budgets are easy to track throughout a design and development process. Although they don’t actually tell us carbon emission and energy consumption analytics directly, they give us a clear indication of efficiency relative to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, reduced data transfer translates to energy efficiency, a key factor to reducing carbon emissions of web products. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. But as we’ll see next, since all web products demand some power, it’s important to consider the source of that electricity, too.

Carbon intensity of electricity

Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. Carbon intensity is a term used to define the grams of CO₂ produced for every kilowatt-hour of electricity (gCO₂/kWh). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/kWh (even when factoring in their construction); whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO₂/kWh. 

Most electricity comes from national or state grids, where energy from a variety of different sources is mixed together with varying levels of carbon intensity. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously; a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

We don’t have control over the full energy supply of web services, but we do have some control over where we host our projects. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps this user-contributed data, and a glance at their map shows how, for example, choosing a data center in France will have significantly lower carbon emissions than a data center in the Netherlands (Fig 2.3).

That said, we don’t want to locate our servers too far away from our users; it takes energy to transmit data through the telecom’s networks, and the further the data travels, the more energy is consumed. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles”—and we want it to be as small as possible.

Using the distance itself as a benchmark, we can use website analytics to identify the country, state, or even city where our core user group is located and measure the distance from that location to the data center used by our hosting company. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea. 

For example, if a website is hosted in London but the primary user base is on the West Coast of the USA, then we could look up the distance from London to San Francisco, which is 5,300 miles. That’s a long way! We can see that hosting it somewhere in North America, ideally on the West Coast, would significantly reduce the distance and thus the energy used to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Converting it back to carbon emissions

If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. A tool my team created does this by measuring the data transfer over the wire when loading a web page, calculating the amount of electricity associated, and then converting that into a figure for CO₂ (Fig 2.4). It also factors in whether or not the web hosting is powered by renewable energy.

If you want to take it to the next level and tailor the data more accurately to the unique aspects of your project, the Energy and Emissions Worksheet accompanying this book shows you how.

With the ability to calculate carbon emissions for our projects, we could actually take a page weight budget one step further and set carbon budgets as well. CO₂ is not a metric commonly used in web projects; we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Translating that into carbon adds a layer of abstraction that isn’t as intuitive—but carbon budgets do focus our minds on the primary thing we’re trying to reduce, and support the core objective of sustainable web design: reducing carbon emissions.

Browser Energy

Data transfer might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

One part of the system we can look at in more detail is the energy used by end users’ devices. As front-end web technologies become more advanced, the computational load is increasingly moving from the data center to users’ devices, whether they be phones, tablets, laptops, desktops, or even smart TVs. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Furthermore, JavaScript libraries such as Angular and React allow us to create applications where the “thinking” work is done partly or entirely in the browser. 

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more computation in the user’s web browser means more energy used by their devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a heavy processing load on the user’s device can inadvertently exclude users with older, slower devices and cause batteries on phones and laptops to drain faster. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This isn’t just bad for the environment, but it puts a disproportionate financial burden on the poorest in society.

In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users’ devices. One tool we do currently have is the Energy Impact monitor inside the developer console of the Safari browser (Fig 2.5).

You know when you load a website and your computer’s cooling fans start spinning so frantically you think it might actually take off? That’s essentially what this tool is measuring. 

It shows us the percentage of CPU used and the duration of CPU usage when loading the web page, and uses these figures to generate an energy impact rating. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.