Designing loops, not paths

"Imagine driving across town during rush hour. You might have a planned route, but traffic jams, roadwork, or weather force you to adapt - taking detours, checking traffic apps, looping back, or even stopping for coffee until things clear up. That's because our interactions with reality rarely follow a script; they're a series of adjustments and feedback loops. As the technology landscape continues to evolve, established practices are giving way to innovative solutions."

"Software design has historically relied on workflow-based methodologies, breaking down objectives - often described as jobs-to-be-done - into individual tasks needed to accomplish those goals. This was largely due to the constraints of deterministic software, which limited flexibility. However, recent advancements in AI are expanding the range of design possibilities. In this article, we'll share some principles & mental models we're using to guide the design of AI agents for business applications while keeping humans in the loop."

Driving across town during rush hour requires continuous adaptations: detours, checking traffic, looping back, or waiting when conditions change. Human interactions with reality rarely follow linear scripts and instead rely on adjustments and feedback loops. Software design historically used workflow-based methodologies that decompose goals into discrete tasks because deterministic systems constrained flexibility. Generative AI expands design possibilities and reveals workflow shortcomings. Workflows can be rigid, overcomplicated, and limiting for adaptive, intelligent agents. AI agent design for business applications should prioritize adaptability, human-in-the-loop controls, and new principles and mental models that accommodate messy, non-linear human behavior.

Read at Medium