Author Questions the Abstraction Layer of Software Engineering Agents
gerardsans · x · 2026-07-17
The core argument is that using natural language to define software engineering tasks in current agentic AI is fundamentally unreliable.
The author asserts that genuinely useful engineering abstractions must be testable, unambiguous, and traceable. To truly boost productivity, we should develop better specifications and tools—favoring programming language-like expressions rather than relying on low-level, unstable automation.
Related event: Community Discusses Best Practices for AI Agent Engineering(3 posts)→
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