New music video about hedonic adaptation | AI better at some forms of knowledge work than at others | AI increasingly used for sensemaking among corporate users | Users want to approve certain autonomous actions | For exploratory creation, a branching UI beat the traditional linear chat interface to the AI backend model | Base-rate neglect: one vivid anecdote outweighs a thousand statistics | The ***** UI for user ratings | Experimental system connects specific words in the u

AI technical capabilities are exploding, but sophisticated use crawls | Synthetic personas exaggerate demographics | AI hurts education when used wrong | Professor Brad Myers is a UX hero | In the future, we’ll all be Agatha Christie | Mental accounting gives users separate budgets for separate expenses | Grok releases upgraded image model

Show a progress indicator when response time exceeds 10 seconds, preferably as a percent-done bar. It tells users two things: the system heard you, and here’s how long the ordeal will last. But never let the bar stall, lie, or reset. AI agents that work for hours have raised the stakes: progress indicators must now serve users who walked away. Follow the 12 design guidelines in this article.

Keep It Simple | AI uses fact flooding to overwhelm users and persuade them | Deep AI integration in business processes | 5 personas for adopting AI | Using AI to change the tone of voice of your writing | Timelines: a chrono-based UI | AI improves cybersecurity | Increasing use of AI agents for online shopping

AI is the biggest change to UX design in 60 years, yet we know embarrassingly little about how people actually use it. Here are 76 open research questions, organized into 7 lists sized for everyone from high school students to the big AI labs. Students who complete a research challenge gain the two qualities employers now screen for: agency and demonstrated AI experience.

Design guidelines held steady for 30 years but are shifting with AI | Users who are anxious about AI use it more, not less | A toggle is a light switch, not a form field | What are the Erdős problems and why are they relevant for AI? | An ambient monitoring interface with glanceable feedback on agent progress cut errors in hal

Agent-ready web design lifts AI task success | Shoppers now pick AI assistants over brand websites, 41% to 38% | Learn from reality: build and iterate | AI getting better at business strategy, but still not good enough to run your company | AI raised the floor but lowered the ceiling in children’s storytelling | Infinite canvas as a UI space for organizing and collaborating on unstructured information | My Hero: Scott McCloud, comic book artist and theorist | AI animates clas

Comparing GPT 5.6 Sol, Opus 5, Kimi K3 | How designers use a UI design agent | AI enhances users’ agency, and they like it | Breadcrumb navigation | UX Hero Doug Engelbart | The decoy effect in pricing plan comparison pages | The paradox of the Active User | Delhi High Court rules that AI training on copyrighted content is legal in India

Carousels are scanned in an L-pattern, not the F-pattern | Making AI-Native games playable | Bulk actions support flexibility and efficiency of use | AI film wins a bronze lion at the Cannes Festival | Use of AI applications doubled in one year

AI narrows skill gaps by helping weak performers the most. Employers are reacting: hiring in AI-exposed job categories now weights human capital 7.8% less and price 1.1% more than before ChatGPT and the demand premium for highly skilled workers is shrinking. Competence has become commodity, so sell judgment. Agentic AI will reverse the equalization and widen skill gaps again.

How AI “skills” are reused and other usability issues with skills | User research job listings for junior staff dry up, and senior staff need AI experience to be hired | Data comics generated with AI increase student learning | Quick view as a shortcut for seeing product info | The AI economy has $175 billion in revenue | AI use spreads from peers | Automatically creating advertisements based on a website

In 1993 and 1996, I predicted that user interfaces would abandon commands: computers would infer and execute user intent instead of obeying point-and-click orders. Modern AI delivered that paradigm, 30 years later. Scoring the papers’ 23 specific predictions against 2026 reality produces a decent grade: 71% correct. The biggest hit: language as the primary interface. The biggest miss: I predicted expert users, and AI instead became the great equalizer.

AI agents expand user tasks | Agentic AI makes expertise more valuable, not less | Users need control over the complexity of AI results | Constraints help users | Meta launched a new image model, Muse Image | ByteDance upgrades its image model to Seedream 5 Pro | Comparing the leading image models | GPT receives a major upgrade to v. 5.6 Sol

Progressive disclosure puts the few features that serve most tasks on the first screen and defers the rest to a clearly labeled second level. The pattern has 4 decades of evidence behind it: novices learn faster and err less, while experts pay 1 click. It’s about to matter more than ever, because AI answers and long-running agents need layered revealing even more than settings screens do.

UX benchmark for AI | Being mentioned in AI answers drives subsequent user behavior | Cheaper character design workflow for new video | AI maturity model | My hero: Dr. Stuart K. Card of Xerox PARC | Microsoft FDE

Halfway through 2026, AI is evolving faster than expected, but usability is struggling to keep pace. I graded my 18 predictions on autonomous agents, compute shortages, and interface design to separate the hype from reality.

Can humans remain in control with superintelligent AI (ASI)? | Dark design music video redone | What are normal people saying about AI? | My hero: Dr. John M. Carroll of IBM Research | Finally, a hotel room shower makes it easy to adjust temperature | How designers use AI vs. what they say about AI | Explosive growth in use of agentic AI among non-developers | Check whether major AI models know you

AI is too large to understand through a single analogy. The Internet explains early adoption, human history explains the next 30 years, biology frames longer-term speculation, and Norse mythology reminds us that tools are not gods.

DeepMind outlined 4 paths to superintelligence: scaling, paradigm shifts, recursive self-improvement, and multi agent collectives. I explained this dense 57-page report in a 31-page comic book, including a section on the UX implications.

Gen Alpha is not mini-Gen-Z | Personas as Packaged Software | Sentient Design is a new book about AI as a design material | My hero: Dr. Thomas K. Landauer of Bell Labs/Bellcore | YouTube’s Thumbnail Generator | Recommended AI short videos | Amazon changes the name of its AI shopping assistant from Rufus to Alexa | Claude Fable 5 released