There is a recurring fantasy in AI discourse that goes something like this: once the model is good enough, you will not need a human in the loop …
The CTO role was already evolving before AI. Cloud infrastructure reduced the need for deep operations expertise. Platform engineering abstracted away …
Every organization has a knowledge graph. They just do not know it. The information about who owns what system, which team depends on which service, …
Every team building an AI application faces the same architectural question early on: should we fine-tune a model, build a RAG system, or create an …
The Integrated Development Environment has been the center of software engineering for four decades. From Turbo Pascal to Visual Studio to VS Code, …
The compliance team says no. That is usually where the AI conversation ends in regulated industries. Healthcare, finance, insurance, and government …
Every new project starts the same way. Not with the interesting part, not with the problem the client hired you to solve, but with 40 hours of setup. …
Single-agent systems are simple to reason about. One agent, one task, one output. But most real-world problems are not single-agent problems. They …
Long-running AI pipelines fail. This is not a possibility to plan for; it is a certainty to design around. API rate limits hit. Provider outages …
Most engineering organizations approach observability like this: deploy Datadog (or Grafana, or New Relic), instrument services, create some …
The way we define work in software engineering has not kept pace with how we execute it. We are asking AI agents to implement features from user …
The hiring freeze memo arrives on a Tuesday. Your roadmap does not change. Your headcount does. This is not a hypothetical. We have watched this play …