Interface administrators, Administrators (Semantic MediaWiki), Curators (Semantic MediaWiki), Editors (Semantic MediaWiki), Suppressors, Administrators
7,979
edits
Minimum Viable Agent: Difference between revisions
no edit summary
No edit summary |
|||
| (4 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
{{stub}} | |||
{{see also|Artificial intelligence terms}} | |||
[[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. | [[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. | ||
| Line 35: | Line 37: | ||
Building an MVA doesn’t require starting from scratch. Developers often rely on: | Building an MVA doesn’t require starting from scratch. Developers often rely on: | ||
* | *'''Frameworks''': [[N8N]], [[Flowise]], [[PydanticAI]], [[smolagents]], [[LangGraph]]—tools for rapid workflow assembly and integration. | ||
* | *'''Models''': [[Groq]], [[OpenAI]], [[Cline]], [[DeepSeek R1]], [[Qwen-Coder-2.5]]—popular choices for language and task-specific capabilities. | ||
* | *'''Coding Aids''': [[GitHub Copilot]], [[Windsurf]], [[Cursor]], [[Bolt.new]]—assistants that accelerate development with code suggestions. | ||
These tools | These tools enable quick prototyping, letting creators focus on the agent’s purpose rather than its technical underpinnings. | ||
==Advantages and Limitations== | ==Advantages and Limitations== | ||
| Line 53: | Line 55: | ||
==Business Potential== | ==Business Potential== | ||
An MVA isn't just a proof-of- | An MVA isn't just a proof-of-concept. It's a stepping stone to a viable business. Early adopters can refine the agent's value proposition, differentiate it in a crowded market, and tailor it to specific industries or clients. Testimonials from initial users bolster credibility, while customization options (e.g. integrating with a company's database) enhance appeal. The challenge is balancing simplicity with enough utility to justify a price tag, whether through subscriptions, pay-per-use, or premium tiers. | ||
==Philosophy and Broader Impact== | ==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 | 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. | ||
{{stub}} | |||
[[Category:Terms]] [[Category:Artificial intelligence terms]] | |||