Name: AI Product Design_ Prompt Engineering & Iterative Development EN
Uploaded: 2025-11-15T23:22:39+00:00
Duration: 12 min 40 s
Description: AI Product Design: Prompt Engineering & Iterative Development This investigation outlines a methodology for AI software development, emphasizing an iterative design process that follows explicit, deta

1 day ago

Entertainment Health & Fitness

AI Product Design: Prompt Engineering & Iterative Development

This investigation outlines a methodology for AI software development, emphasizing an iterative design process that follows explicit, detailed requirements. It highlights the evolving roles within the development cycle, where UX Product Designers become multi-faceted professionals also serving as content architects, product managers, in their role as prompt engineers. Explicit instructions and clear communication throughout the development stages, define initial requirements through delivering successive versions. This approach ensures alignment with business, technical, and end-user needs, leading to the successful creation of tools such as workflows, applications, websites, and agents.

Advocate for an iterative process that has approvals at each juncture, beginning with both a short and long list of desired outcomes, resulting in requirements documentation covering three buckets of needs and requirements; 1) business, 2) technical, and 3) audience.

Today, in the AI supported development cycle is driven primarily by UX Designers, creative thinkers and communicators that are also Architects, Product Designers, Managers, and Developers, who effectively create codebase from natural language "Prompts", explicit language that drives the AI, these individuals utilize user research to define and own the product requirements, described on lengthy documentation summarized in modular "Prompts", AI instructions, and the resulting output includes, the entire codebase, documentation guides that describe implementation, integrations and deployment, governance of quality assurance, branding, style, tone and visual assets of imagery, video, and diagrams, audio podcasts topics, chat agent, social media and associated marketing tools all and dependencies, APIs, roles, variables, values etc.

AI tools can be extremely unreliable, inconsistent, moody, dishonest, manipulative, and frustrating. Successful approaches with AI Prompt Engineering therefore are Explicit, leaving little room for confusion, using qualifying AI Prompt terms terms such as, MUST, DECLARE, STATE, MODULAR, ITERATE, SHOW, ASK, WAIT FOR APPROVAL TO PROCEED, VALID, ERROR FREE, QUALITY REVIEW, CODE VERIFICATION, PROCESS, GUIDELINES, DEPENDENCIES, HAND HELD DEPLOYMENT GUIDE, DOCUMENTATION.

In Summary, define the project in Extreme detail, in a simple but modular and iterative manner, specifically, calling out the known values, company and product name, key terms, product categories, types, features and benefits, define menus, call out app or web page page template needs and requirements, home page, sub page, search, chat agent, tools and other agents, API integrations, declaring the AI "Must deliver excellence and ask for approval at each implementation of output versions" including code reviews, user testing, feedback and error recovery, resulting in a functional deployed product at each interval that can be previewed by team for feedback to drive edits and improvement to meet the needs of the business, technology and audience.

AI Application and Tool Examples (Change Constantly)

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