Eating My Own Dog Food: How I Used the Framework to Write the Post About the Framework

Writing code has always been the most time- and resource-intensive task in software development. AI is changing that, and faster than most engineering organizations are prepared for. Tools like Claude Code and Cursor are already handling significant parts of code construction, freeing developers to spend more time on requirements, architecture, and design. But that shift creates a new challenge nobody is talking about enough. As AI takes on the heavy lifting, the skills that matter most are moving upstream: how to provide the right context for a prompt, how to evaluate what the model produces, and how to understand a problem deeply enough that you can’t be fooled by a confident but wrong answer. This piece explores those three skills and why developers who master them will have a significant edge over those who don’t. Beyond coding: Mastering the art of the prompt Software translation tools such as compilers and assemblers map a high-level description of code to a lower-level represent

In “Don’t Automate Your Moat,” I argue that engineering organizations should match AI autonomy to two independent dimensions: business risk and competitive differentiation. I used AI Gateway cost controls as a worked example throughout the piece because a single feature touches all four quadrants depending on which piece you’re building. A piece making that argument […]

Remember when Framework made the first laptop where you can easily upgrade its entire internal video card in three minutes flat? The company's getting into the external graphics game, too. As promised last August, you'll be able to turn the Framework Laptop 16's GPU modules into external ones instead. Or, you can plug in a desktop graphics card (or network card, or other PCIe cards) for more power than most laptops ever dream of having, with eight lanes of PCI-Express bandwidth. Framework's calling it the OCuLink Dev Kit, because it uses the OCuLink standard to transmit data between your CPU and the external GPU, and because the company wa … Read the full story at The Verge.

Training powerful AI models depends on one resource that is quietly running out: specialized data. While the internet provided a seemingly infinite supply of text and images to train today’s generalist models, the next wave of AI breakthroughs — in cybersecurity, legal reasoning, healthcare, and other niche domains — requires data that simply doesn’t exist […] The post Google Introduces Simula: A Reasoning-First Framework for Generating Controllable, Scalable Synthetic Datasets Across Specialized AI Domains appeared first on MarkTechPost.