Piers At some point in every product’s life, a familiar tension emerges: do you keep polishing what you have, or admit that the whole thing needs a deeper rethink? It’s rarely a clean decision. Incremental improvements promise continuity and low risk, but only until they don’t. And starting over can feel liberating in theory, yet terrifying … continue reading
I’ve come across a few really good resources for UX Designers getting into or involved in designing for complex apps and AI-enabled software. Let me know of other great links and I will add them to the list. Number one on my list is the Google People + AI Guidebook (aka PAIR). This is a huge and … continue reading
How they work, why they matter, and what you should know before building one AI agents are quickly becoming one of the most talked-about developments in applied AI. But despite the buzz, many people are still unsure what an “agent” actually is or how it differs from a standard large language model (LLM) prompt. This … continue reading
Every now and then a new technology arrives that completely breaks the assumptions of the world around it. Not gently. Not politely. Not in a way that leaves existing workflows intact. It shows up like an unexpected guest who kicks the furniture out of the way and sits down wherever it likes. That’s what GenAI … continue reading
As AI agents become more autonomous and take on increasingly complex tasks, adaptive learning becomes a core requirement. Adaptive learning is the ability to update behaviour based on new information. While model fine-tuning used to be the dominant mechanism for adaptation, modern agent architectures allow for more flexible and lightweight options that work in real … continue reading
I’ve recently been working on an agentic fraud alert review system for a bank, where our agent monitors transaction alerts and reviews the transaction against context of the bank account as well as any open source intelligence it can gather. The agent system started as a chat interface – where users could ask questions and … continue reading
“Enterprise AI strategy” is something you’d find on a consultant’s slide deck with lots of arrows, maybe a few buzzwords, and a roadmap that stretches into some hazy, futuristic quarter where everything just “works.” But in reality, the organisations making the most meaningful progress with AI aren’t following 100-slide strategies. They’re building small, scrappy, useful … continue reading
Sangeet Paul Choudary has written an interesting piece on The problem with agentic AI in 2025. The article argues that while agentic AI (systems that act autonomously rather than simply assist) holds great promise, many organisations are ill-prepared for its demands: governance, data quality, and clarity of purpose. He says they risk doing more harm … continue reading
I have reviewed about 100 product designer portfolios in the last couple of weeks for 2 open midweight product designer roles we have at Faculty. I want to help product designers get jobs. These 100 portfolios are after we have filtered out people who have applied who do not fit the criteria, i.e. the criteria … continue reading
In large consulting projects and enterprise AI programs, too many AI and data science projects follow the same unhelpful pattern. A team of data scientists works for months in notebooks, training and tuning models, carefully optimising precision, recall, and accuracy. Eventually, the results are presented: metrics are up, charts point in the right direction, and … continue reading