After looking over the usages of the term, and some of the tools that claim to be implementing SDD, it seems to me that in reality, there are multiple implementation levels to it: Spec-first: A well thought-out spec is written first, and then used in the AI-assisted development workflow for the task at hand. Spec-anchored: The spec is kept even after the task is complete, to continue using it for evolution and maintenance of the respective feature. Spec-as-source: The spec is the main source file over time, and only the spec is edited by the human, the human never touches the code. All SDD approaches and definitions I’ve found are

Spec-Driven Development (SDD) revives the old idea of heavy documentation before coding — an echo of the Waterfall era. While it promises structure for AI-driven programming, it risks burying agility under layers of Markdown. This post explores why a more iterative, natural-language approach may better fit modern development. Source: Spec-Driven Development: The Waterfall Strikes Back

With AI becoming a more widely adopted interface to the web, the principles of transparency, accountability, and respect for user agency are critical to keeping it free, open, and accessible to all. As an independent browser, we are well positioned to uphold these principles. While others are building AI experiences that keep you locked in a conversational loop, we see a different path — one where AI serves as a trusted companion, enhancing your browsing experience and guiding you outward to the broader web.We believe standing still while technology moves forward doesn’t benefit the web or humanity. That’s why we see it as our responsibility to shape how AI integrates

What are the ways to persist data in the browser? Source: Storage in the browser | Volodymyr’s website

I’ve narrowed this down to three concepts that feel foundational – the ones I keep coming back to when I’m trying to understand how AI systems actually work, or when I’m explaining MCP to someone, or when I’m making decisions about how to build something. These three form a kind of progression: understanding how AI represents meaning, then how you customize it, then how you make customization practical. The patterns between these concepts interest me as much as the concepts themselves. How embeddings enable RAG, how LoRA makes fine-tuning accessible, how choosing between RAG and fine-tuning depends on whether you’re teaching facts or behavior. These connections make the whole landscape

This got me thinking: how often do we, as frontend engineers, overlook the URL as a state management tool? We reach for all sorts of abstractions to manage state such as global stores, contexts, and caches while ignoring one of the web’s most elegant and oldest features: the humble URL. Source: Your URL Is Your State

Web Monetization gives publishers more revenue options and audiences more ways to sustain the content they love. Support can take many forms: from a one-time contribution to a continuous, pay-as-you-browse model. It all flows seamlessly while people engage with the content they love. Publishers earn the moment someone engages, while audiences contribute in real time, using a balance they control.I encourage you all to give it a try! Install the extension that polyfills the proposed Web standard, get a wallet (I went with GateHub, which works in US Dollars and Euros), and then connect it to the extension. Source: Using the Web Monetization API for fun and profit

“Many of us became software engineers because we found our identity in building things. Not managing things. Not overseeing things. Building things. With our own hands, our own minds, our own code.But that identity is being challenged,” wrote Annie in March 2025 in her blog post, The Software Engineering Identity Crisis, which has since been read by tens of thousands of engineers and got them thinking about this (re)defining moment in what their role means. In this conversation, Annie dives deep into the software engineer’s identity crisis, the rise of AI agents, and how engineers can prepare for a rapidly evolving future. Source: How AI Is Redefining Software Engineering with

Source: Context Engineering for Non Engineers – Eleganthack

I’m a simple boy, so I like simple things. Agents can run Bash and write code well. Bash and code are composable. So what’s simpler than having your agent just invoke CLI tools and write code? This is nothing new. We’ve all been doing this since the beginning. I’d just like to convince you that in many situations, you don’t need or even want an MCP server. Let me illustrate this with a common MCP server use case: browser dev tools. Source: What if you don’t need MCP at all?

## Creating a good CLAUDE.md file The following section provides a number of recommendations on how to write a good CLAUDE.md file following context engineering best practices. Your mileage may vary. Not all of these rules are necessarily optimal for every setup. Like anything else, feel free to break the rules once…you understand when & why it’s okay to break themyou have a good reason to do so Source: Writing a good CLAUDE.md | HumanLayer Blog

In this entertaining and relatable video, two brothers experience the frustrations of downloading new apps and the consequences of not having them. They discuss the convenience and usability of apps, the abundance of apps on their phones, and the growing trend of relying on apps for everyday tasks. They also explore alternative solutions and find a balance between technology and simplicity. #appstruggle #fustratedwithapps #alternativesolutions #newtech Source: Instagram

TL;DR: Building agents is still messy. SDK abstractions break once you hit real tool use. Caching works better when you manage it yourself, but differs between models. Reinforcement ends up doing more heavy lifting than expected, and failures need strict isolation to avoid derailing the loop. Shared state via a file-system-like layer is an important building block. Output tooling is surprisingly tricky, and model choice still depends on the task. Source: Agent Design Is Still Hard | Armin Ronacher’s Thoughts and Writings

In this RedMonk conversation, Alex Russell, Partner Product Architect at Microsoft, discusses the state of mobile development, focusing on JavaScript performance, the state of Progressive Web Apps (PWAs), and the impact of major players like Apple (iOS) and Google (Android). They explore the importance of management in addressing web performance issues, the role of web standards in shaping the future, and the implications of AI on web development. Alex emphasizes the need for restraint in JavaScript usage and the importance of creating user-friendly web experiences, particularly on mobile devices. Source: Alex Russell on PWAs, App Stores, and Mobile Performance – RedMonk

One of the concepts that are gaining lots of discussion is the “MCP” which stands for Model Context Protocol. Anytime I’d ask what an MCP is, I’d usually hear it described as an API. So then, why isn’t it just called an API? Because it’s not really an API. Sound confusing? You bet! Just like how I learned to code from actually building something. I decided if I was going to truly learn what this thing was, I’d have to build one. So I did and this is how that went. Source: Minefield Context Protocol

Meanwhile, sites are ballooning. The median mobile page is now 2.6 MiB, blowing past the size of DOOM (2.48 MiB) in April. The 75th percentile site is now larger than two copies of DOOM, and P90+ sites are more than 4.5x larger, and sizes at each point have doubled over the past decade. Put another way, the median mobile page is now 70 times larger than the total storage of the computer that landed men on the moon. Source: The Performance Inequality Gap, 2026 – Infrequently Noted

I am so tired of hearing about AI. Unfortunately, this is a talk about AI. I’m trying to figure out how to use generative AI as a designer without feeling like shit. I am fascinated with what it can do, impressed and repulsed by what it makes, and distrustful of its owners. I am deeply ambivalent about it all. The believers demand devotion, the critics demand abstinence, and to see AI as just another technology is to be a heretic twice over. Today, I’d like to try to open things up a bit. I want to frame the technology more like an instrument, and get away from GenAI as an

A shift is happening in Design… New tools. New workflows. New capabilities. Because… → As production gets automated → Thinking becomes more valuable → Creativity becomes the new premium That’s why I’m speaking to Shamus Scott Grubb on The Design of Everyday People Livestream. We’re diving deep into: 1. How AI separates design from production 2. What skills actually matter in this new reality 3. How to position yourself on the right side

Every technology with real staying power goes through waves of adoption. The first wave attracts the early experimenters – the ones who can sense the future before it’s evenly distributed. The second picks up the enterprises that’ve felt enough pain to seek out something better. The third comes when the rest of the world catches up, usually because the ground itself has shifted and the old tools can no longer do the job. GraphQL is now entering that third wave. Most people still describe GraphQL as an alternative to REST. That was true in 2015. What’s happening today is different. In the era of LLMs and autonomous agents, GraphQL isn’t

AI has changed the texture of design. We’re not designing for people alone anymore, we’re designing with/for intelligence. That changes everything. I’m obviously not the only person thinking about how Design frameworks evolve. Recent research has started reframing what this looks like. Adam Fard calls it “AI-First Design Thinking.” Weisz, He, and Muller (2024) propose six design principles for generative AI that move beyond the empathy-prototype-test loop: Source: Design Thinking for AI: The 5-Stage Framework Every Builder Needs

I recently attended the Enterprise UX conference in Amersfoort. The presentations made it very clear that successful AI integration requires big changes in how companies work and how we build systems. The main message was: AI is not just a new tool; it forces us to change our basic rules for design and data. Source: New Rules for Enterprise UX and AI — jasha.eu

Generative UI and the Ephemeral Interface This week, Google debuted their Gemini 3 AI model to great fanfare and reviews. Specs-wise, it tops the benchmarks. This horserace has seen Google, Anthropic, and OpenAI trade leads each time a new model is released, so I’m not really surprised there. The interesting bit for us designers isn’t the model itself, but the upgraded Gemini app that can create user interfaces on the fly. Say hello to generative UI. I will admit that I’ve been skeptical of the notion of generative user interfaces. I was imagining an app for work, like a design app, that would rearrange itself depending on the task at

In one of the most popular episodes yet, Vitaly Friedman talked about what’s next for AI design patterns (https://www.dive.club/deep-dives/vita…) . In that episode he frequently referenced Shape of AI (https://www.shapeof.ai/) which is an incredible database of AI design patterns.So I wanted to get to the source and go deep with the creator [Emily Campbell]( / emmiecampbell ) to learn how to design great AI experiences. Because she’s studied AI products more than just about anyone I’ve ever seen 👀

I find it’s always important to examine why you made a mistake. The worst mistake I ever made was reading “Bitcoin: A Peer-to-Peer Electronic Cash System” in January of 2009, thinking “cool math toy, maybe someone will turn it into something useful someday” and moving on. My most recent mistake, however, was not realizing that software development would be the first field to be transformed by agentic AI. I always assumed it would be the last. Let’s examine why that was. Source: Why Software Development Fell to AI First

A Month of Chat-Oriented ProgrammingOr when did you last change your mind about something?Nick Radcliffe. 12th November 2025. TL;DR: I spent a solid month “pair programming” with Claude Code, trying to suspend disbelief and adopt a this-will-be-productive mindset. More specifically, I got Claude to write well over 99% of the code produced during the month. I found the experience infuriating, unpleasant, and stressful before even worrying about its energy impact. Ideally, I would prefer not to do it again for at least a year out two. The only problem with that is that it “worked”. It’s hard to know exactly how well, but I (“we”) definitely produced far more than