Most senior developers are embarrassed by their tech stack
Bill Doerrfeld | June 17, 2025
My
latest for LeadDev looks at en eye-opening report from Storyblok.
86% of developers are embarrassed by their tech stack. And, it's causing them to quit.
73% of developers surveyed know at least one peer who quit over this. 58% are considering leaving themselves.
I wrote up a brief blurb about this for LeadDev, including some expert takes.
Going forward, developers expect a clearer modernization roadmap and better leadership.
If you don't have a budget line item for "developer morale," they may just start a' walkin'...
Featured photo by Julia Taubitz via Unsplash
The majority of enterprises are now multicloud. I compared six of the leading multicloud management solutions for InfoWorld.
AI researchers are calling the next class of models large action models (LAMs). For The New Stack, I explored what LAMs are, what examples are emerging in the market, and what experts think.
My article for LeadDev explores specific prompting techniques proven to sharpen your AI-assisted software development.
Nordic APIs, the API-specific blog I edit, was recently ranked the top API blog online by FeedSpot. After ten years managing this presence, I reflect a bit on the journey thus far.
Developers are realizing that being productive with AI coding assistants takes a lot more than just asking nicely. There's real craft to it.
AI coding is the easy part. Now it's time to focus on DevOps to get it into production. In a recent interview for LeadDev's DirectorPlus, Honeycomb's CTO, Charity Majors, shares expert tips on how to accomplish this.
My latest for The New Stack explores new research from Ai2, DataDecide, which helps LLM developers make better decisions around training data.
My APISEC|CON talk covers the hype around agentic AI and MCP, and delves into inherent flaws in MCP architectures and suggests mitigations.
AI coding assistants are a productivity dream in some cases — and a debugging nightmare in others. So, where’s the line?
Semantic caching is like typical caching, but for AI. It could eliminate a lot of redundant API calls to LLMs, reducing costs and improving performance.
