ENGINEERING CREATIVITY WITH AI

ENGINEERING CREATIVITY WITH AI treats creativity as an engineered search-and-validation process rather than a mysterious gift or a one-prompt trick. The book begins by separating novelty from usefulness and by asking what generative AI can actually contribute to creative work. Early chapters examine the cognitive architecture of creative thinking, the strengths and limits of generative models, the division of responsibility between human judgment and machine generation, and the habits required to escape entrenched patterns without mistaking novelty for evidence. At the center of the book is AI-CE9, a proposed nine-stage creativity-engineering workflow. The sequence moves from discovering the real opportunity and mapping the existing solution space to reframing the problem, generating functionally diverse candidates, transferring ideas across domains, evaluating alternatives, building a minimum viable prototype, validating originality and real-world value, and iterating from evidence. AI-CE9 is presented as an integrative method to be tested, not as a scientifically proven universal law or a guarantee of breakthrough innovation. The middle chapters expand the creative toolbox beyond ordinary brainstorming. TRIZ, SCAMPER, Systematic Inventive Thinking, morphological analysis, analogical reasoning, inversion, paradox, systems thinking and transformational creativity are used to manipulate problem structure deliberately. These methods are connected to prompt engineering, controlled divergence, multi-agent creative collaboration and constructive dissent so that AI output becomes a structured exploration space rather than a stream of plausible but unexamined suggestions. Research-grounded creativity receives its own engineering treatment. The book explains how…

For researchers, inventors, software engineers, designers, artists, educators, entrepreneurs, students and curious professionals who want a structured way to use AI for original thinking, prototyping and innovation while preserving human judgment, evidence standards, intellectual-property awareness and responsible decision-making.