#field-testing

#field-testing

I got a degree from Douglas College in programming and business management. I understood the business side more and was better at that than at being a coder.

Lydia noticed the machine's battery was running low and told two other team members. The more senior went to fetch the backup battery, while the junior team member suggested a quicker method that Lydia firmly rejected.

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.

Capacity Planning is the process of right-sizing the 'Total Project Demand' with the forecasted Team Capacity. Most UX teams have no idea what their capacity is. Fewer still have a process for calculating it and using it during quarterly planning activities with their counterparts in Product Management & Engineering to ensure teams don't commit to more work than they can handle.

It's been almost 20 years since I started my career in product design, and, as you might imagine, many things have changed dramatically since then. One of the main characteristics of the technology industry is the constant evolution of its dynamics, roles, processes, technologies, experiences, and even business models. Those changes are inevitable and will continue. In retrospect, I see that there is one reality that has not changed much over the last 20 years and remains a constant issue to this day: building technology products can sometimes be a discouraging and exhausting process, from junior positions to senior management levels. Why do we suffer every time we need to build something? Why is there so much burnout among today's tech professionals? Why is it that, regardless of the industry, company, or technology, we always hear the exact phrases: "I'm exhausted, I feel drained by this job."? Well, those are valid questions that still haunt me 20 years after my first web design job. It seems like there's no choice in this environment but to suffer.

Her payment form wasn't connecting to the payment processor, and every attempt ended in an error message that made no sense. I understood her frustration. As a founder myself, I was acutely aware of the pain of trying to run a business and feeling like nothing was going your way. When I dug into her form, I found the problem a few minutes later: a mismatch between test mode and live credentials.

Hello, I am about to launch a website which offers an analytic tool which will enable traders in the financial market to analyze their performance. I will post on a few selected forums an offer of free full use of the tool. CHat GPT claims that a period of 30 days will be enough as by then users will be well familiarized with the system and a longer period will be unnecessary.

The normative form for interacting with what we think of as "AI" is something like this: there's a chat you type a question you wait for a few seconds you start seeing an answer. you start reading it you read or scan some more tens of seconds longer, while the rest of the response appears you maybe study the response in more detail you respond the loop continues

Model Context Protocol (MCP) is a technology that enables AI models to connect with external tools and data sources (such as GitHub, Slack, databases, and documentation systems). In this article, I want to explore my top 7 favorite MCPs you can use in your design process. I will cover not only benefits but also limitations of the each MCP so you will have a clear idea about what you can & cannot do with it.

To find the typical example, just observe an average stand-up meeting. The ones who talk more get all the attention. In her article, software engineer Priyanka Jain tells the story of two colleagues assigned the same task. One posted updates, asked questions, and collaborated loudly. The other stayed silent and shipped clean code. Both delivered. Yet only one was praised as a "great team player."

Hast mentioned that they trust their unit tests and integration tests individually, and all of them together as a whole. They have no end-to-end tests: We achieved this by using good separation of concerns, modularity, abstraction, low coupling, and high cohesion. These mechanisms go hand in hand with TDD and pair programming. The result is a better domain-driven design with high code quality. Previously, they had more HTTP application integration tests that tested the whole app, but they have moved away from this (or just have some happy cases) to more focused tests that have shorter feedback loops, Hast mentioned.

During my eight years working in agile product development, I have watched sprints move quickly while real understanding of user problems lagged. Backlogs fill with paraphrased feedback. Interview notes sit in shared folders collecting dust. Teams make decisions based on partial memories of what users actually said. Even when the code is clean, those habits slow delivery and make it harder to build software that genuinely helps people.

AI is disrupting more than the software industry, and is doing so at a breakneck speed. Not long ago, designers were deep in Figma variables and pixel-perfect mockups. Now, tools like v0, Lovable, and Cursor are enabling instant, vibe-based prototyping that makes old methods feel almost quaint. What's coming into sharper focus isn't fidelity, it's foresight. Part of the work of Product Design today is conceptual: sensing trends, building future-proof systems, and thinking years ahead.

AI design tools are everywhere right now. But here's the question every designer is asking: Do they actually solve real UI problems - or just generate pretty mockups? To find out, I ran a simple experiment with one rule: no cherry-picking, no reruns - just raw, first-attempt results. I fed 10 common UI design prompts - from accessibility and error handling to minimalist layouts - into 5 different AI tools. The goal? To see which AI came closest to solving real design challenges, unfiltered.