Loop engineering, a new phrase circulating among AI developers, is becoming a way to describe how software teams are trying to get more value from coding agents: not by writing better one-off prompts, ...

The discourse around AI often focuses on those who entirely embrace — or deeply despise — the tech. For engineers, the truth ...

Abstract: Large Language Models (LLMs), like those of the ChatGPT, Gemini, and Claude families, are increasingly being researched for their potential utilization in programming education. Traditional ...

Erik Steiger discusses the operational pain of legacy PDF generation in regulated banking and manufacturing. He explains how ...

A wave of recent product updates suggests the competition among AI coding tools is moving beyond autocomplete and chat toward long-running agents that can understand projects, invoke tools, and carry ...

Structured specifications help AI coding agents build what engineers actually need by capturing intent before code generation ...

The most efficient software no longer carries screens for people — it carries atomic commands that AI agents run while ...

Harness engineering is hot. This new field involves devising AI infrastructure and scaffolding. It is a necessity. An AI Insider analysis and scoop.

AI-assisted software development has evolved significantly over the last few years, moving from isolated code completion toward structured execution models that resemble automation levels seen in ...

Agentic AI is now a core part of the engineering process, driving massive execution leverage and helping us generate more code than ever before. Yet, a difficult question I’ve increasingly heard from ...

If you truly want to avoid drowning in ‘AI slop,’ you need experienced engineers who can supervise the observability, testing, and review of all that AI-generated code. The backlash was inevitable.