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

Reviving the UX goal of empowering users | Writing in marketese kills marketing | Supposed impulse buying is often the result of months of building consideration | Honoring a human factors pioneer, Dr. John D. Gould of IBM | Prompting tip for small text fields: use Chinese

Advanced AI work is not a simple prompt-response loop. Users discover their goals through experimentation, interpret machine output through boundary objects, and refine intent over time. The future of AI-UX is not chat, but structured discovery.

The two most conversion-killing ecommerce usability fails | Social media use remains strong but the platforms are becoming less about connecting with other people | The usability of overseeing AI agents | Team-building image idea: design video game characters | Professor Ben Shneiderman was one of the greatest early pioneers of user experience | Seedance 2 as PC software concept

Forward Deployed Engineers (FDE) can build powerful AI systems, but enterprise transformation requires more than technical deployment. Organizations need Forward Deployed Designers (FDD) who can map business outcomes, redesign decision rights, and convert AI capability into operational change.

Video about scope creep | Demis Hassabis on the present and future of AI | Humans and AI have different interpretations of words to denote probabilities | Very different reasons why people use AI versus the Internet | Google’s disappointing AI announcements

AI is not merely making designers faster at producing screens, prototypes, and research summaries. It is changing the object of design itself. The UX profession’s most valuable contribution stops being UI production and becomes the design of intent itself: defining what good means, encoding judgment into live systems, setting boundaries for agentic behavior, maintaining coherence across many parallel outputs, and preserving human purpose when software starts to act.

Case study of redesigning workflows for AI in computer game studios | Can you live 4 days without AI? | AI increases learning when used as a tutor and hurts when doing the exercises for the students | A streaming media platform for your job | DeepMind demos integration between voice input and pointing

Humans have been dreaming of thinking machines for more than 2,700 years, but real work on building them started in 1943 with the first neural networks. Progress during the following 80 years was slow, with many disappointments and “AI Winters,” but advances built up over time as compute scaled. Themes seen during this long history persist to this day.

New music video based on Moby-Dick | AI expands users’ tasks compared with traditional search, but provides narrower information results | AI dashboard visualizations help therapists spot trends hidden in session notes | How to elicit tacit knowledge to build AI workflows | A16Z awarding fellowships to design engineers

User researchers as role-playing game classes | AI posture recommendation feature in Huawei Pura 90 phones | AI helps teaching assistants provide better feedback to students | AI as a metacognitive coach | Recommending an entertaining short AI film | SpaceX’s plan for 100 TW orbital compute | New Chinese video model Happy Horse from Alibaba

Claude Design | AI Does User Testing | AI Use Crosses 50% | GPT-Images-2 | GPT 5.5 | DeepSeek 4 Summary: Claude Design should be used differently than canvas-based design tools | AI conducts user testing and can now see what’s happening on the screen | For the first time, more than 50% of employed Americans use AI at work | OpenAI recaptures leadership in AI image generation with new, highly accurate model | Two upgraded AI models, GPT 5.5 and DeepSeek 4