Minimum Viable Agent: Difference between revisions

[[Minimum Viable Agent]] or '''MVA''' is a streamlined, initial version of an [[AI agent]] designed to solve a single, specific problem with minimal features while delivering significant value to users. Inspired by the concepts of [[Minimum Viable Product]] (MVP) and Minimum Viable Service, the MVA approach emphasizes simplicity, rapid development, and real-world testing over complex, feature-heavy designs. The goal is to create an agent functional enough to gather feedback, demonstrate utility, and evolve based on user needs—without the pitfalls of over-engineering or scope creep.

==Philosophy and Broader Impact==

The MVA approach mirrors broader trends in tech: ship fast, learn from users, and adapt. It rejects the notion that AI must be flawless out of the gate, a mindset fueling successes like [[Google]]'s evolving algorithms and [[OpenAI]]'s iterative models. By keeping humans involved and updates frequent, MVAs stay relevant in a field where stagnation means obsolescence. It’s about momentum over perfection, a pragmatic way for developers, startups, and businesses to explore AI without drowning in complexity.