#systems-design

#systems-design

Opus 4.7 is available across Claude products and its API, with a token cost of $5 per million input tokens and $25 per million output tokens.

"It would be really hard without this space to make good products, if not impossible," Axelsson says.

Aesthetic inspiration is social and collective, but aesthetic results are deeply personal. What works for one face, skin type, or bone structure won't always work for another.

All empires eventually fall, and it seems the creative software industry has collectively decided that Adobe's time has come. The Creative Cloud provider's suite of design tools have been considered the industry standard for decades.

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.

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.

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.

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.

Maybe this stake is more prominent in start-up environments, where new ideas surface every day and the opportunity for growth is potentially wider. Philosophies like "Build fast, fail fast" are at the core of an agile mindset, helping us determine whether an idea is viable in the early stages or whether a pivot is necessary to achieve the desired numbers and experience.

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

Something's been slowly shifting in the design zeitgeist. I've been watching my feed on X and the vibe has changed. More and more, I see designers sharing finished experiments or prototypes they coded themselves, rather than static Figma files. Moving from working on a canvas to talking to an LLM. The conversation isn't "here's a design I made" anymore... it's "here's something I shipped this afternoon."

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.