Most AI Developer Tools Are Not Worth Adopting Yet
The AI tooling landscape is exploding. Most of it adds complexity without removing real friction. Here is how I decide what earns a spot in the stack.
Opinion coverage in this archive spans 5 posts from Nov 2019 to Apr 2024 and treats opinion as a production discipline: evaluation loops, tool boundaries, escalation paths, and cost control. The strongest adjacent threads are ai, llm, and developer tools. Recurring title motifs include engineering, most, ai, and developer.
The AI tooling landscape is exploding. Most of it adds complexity without removing real friction. Here is how I decide what earns a spot in the stack.
LangChain promises to simplify LLM development. Instead it adds abstraction layers you will fight against the moment your use case gets real.
The term 'prompt engineering' oversells what is essentially clear writing. It is a useful skill, not a discipline.
The industry loves renaming things. Platform engineering is DevOps done properly — and most companies still won't do it right.
Edge computing is real, but most teams adopting it don't have an edge problem. They have an architecture problem they're solving with geography.