Data science
fromMedium
1 day agoContext matters... A lot
Large language models excel at tasks but struggle with context, leading to potentially misleading answers despite their capabilities.
Santa Cruz de Tenerife is one of the most idyllic cities in the Canary Islands. At its heart stands the jewel - the Auditorio. It's a place where talent from both worlds, New and Old, comes together. A theatre, opera, dance, and music heaven.
When I moved in here it truly was my last resort. Since living here I feel like I have the same independent life that my friends have and I just don't want to lose that. The guide dog run is probably the most important thing for me. It's a safe and confined area where I feel comfortable taking my dog out, especially at night.
If you ask Claude to generate a web page for you, there is a high chance you will get a very generic output. The page serves a functional purpose, but it's not very appealing. You can see that this design clearly serves the functional purpose, but doesn't look very appealing.
Instructions I created. Instructions I am continuing to hone - instructions that required me to study my own old essays, identifying what I do when I write. The sentence rhythms. The way I move between timescales. The zooming in and out from concept to detail. The instructions tell Claude how I would like ideas composed. I pull together concepts and experiences from my lived expertise to formulate a point of view - in this case, on this new AI technology.
Performance is a critical factor in user engagement, where even minor delays in loading can deter users. A clean and simple user interface also contributes significantly to user retention.
In 2003, when plumbing fixtures industry veteran Rob Buete first encountered the "walk-in tub" made by a startup called Safety Tub, he burst out laughing. A bathtub with a door? It seemed like a joke, or at best a clunky contraption for frail seniors who couldn't step over a regular tub. Kinya Seto is the CEO of LIXIL, the global manufacturer of pioneering water and housing products, including brands such as GROHE, American Standard, INAX, and Tostem.
Ana proposed the following: Is this enough in 2026? As an occasional purveyor of the visually-hidden class myself, the question wriggled its way into my brain. I felt compelled to investigate the whole ordeal. Spoiler: I do not have a satisfactory yes-or-no answer, but I do have a wall of text!
Everything you need to know in development & design this week, rounded up for you (Week 4, 2026). You'll find the most essential things right now: JavaScript & CSS libraries, useful code snippets, crucial web dev news & resources, curated AI tools, free design assets, and plenty of other good stuff we found! Highlights: 2026 Tech Stack Refresh! Dive into updated "Top 10" lists for Off-canvas menus, responsive dropdowns, fullscreen navs, and more to get your projects ready for the year ahead.
My role was straightforward: write queries (prompts and tasks) that would train AI agents to engage meaningfully with users. But as a UXer, one question immediately stood out - who are these users? Without a clear understanding of who the agent is interacting with, it's nearly impossible to create realistic queries that reflect how people engage with an agent. That's when I discovered a glitch in the task flow. There were no defined user archetypes guiding the query creation process. Team members were essentially reverse-engineering the work: you think of a task, write a query to help the agent execute it, and cross your fingers that it aligns with the needs of a hypothetical "ideal" user - one who might not even exist.
My role was straightforward: write queries (prompts and tasks) that would train AI agents to engage meaningfully with users. But as a UXer, one question immediately stood out - who are these users? Without a clear understanding of who the agent is interacting with, it's nearly impossible to create realistic queries that reflect how people engage with an agent. That's when I discovered a glitch in the task flow.
Progressive disclosure is a well-known principle in UX design. This principle is about showing users only what they need right now, and revealing more options or information gradually as they interact or gain context. The goal is to reduce cognitive load, keep interfaces clean and approachable, and still support advanced use cases when needed. The principle of progressive disclosure can be applied not only to the user interfaces we design, but also AI tools we use.