Practical takes on software, hardware, and AI — what actually changes for users and builders, minus the hype.
As AI moves from hype to pragmatism in 2026, designing the agent loop—the orchestration logic that governs how LLMs perceive, reason, act, and observe—becomes the key differentiator, ensuring coherence and reliability beyond model choice.
Integrating AI code assistants in large, legacy codebases requires careful context management and security review to avoid breaking changes. Drawing from pragmatic AI trends, this article outlines key practices for safe and effective use.
As AI shifts from hype to pragmatism, hardware design is embracing AI as a normal co-pilot—augmenting engineers through templates, contextual edits, and roadmap alignment, rather than replacing them.
Adopting a 'normal technology' perspective on AI—viewing it as a human-controlled tool subject to slow institutional adoption—offers a more realistic path for users and builders. Hardware design exemplifies this pragmatic shift, with AI acting as a practical co-pilot for engineers.
