The HowDo Journey
Learn Product Innovation Powered by AI
After 20 years launching products at Amazon, PayPal, Target, Visa, and building my own startup (sold to a Fortune 50), I spent $2M and a decade trying to teach AI how to innovate.
What I discovered: when you systematize innovation for machines, you build a process for humans too.
All entrepreneurs need to master innovation fundamentals using AI as an accelerator. But all AI has biases toward whoever made it.
To keep algorithmic biases from hijacking your business decisions, I’m open-sourcing my innovation process.
“Hope this helps you.” – West Stringfellow
The Research Archive
Over a decade of systematic research, iteration, and testing has produced thousands of pages of innovation knowledge. These resources represent the distilled wisdom from hundreds of books, expert interviews, case studies, and real-world testing.
The Timeline
2015
Potintia incorporated to solve AI training data challenges
Bought hundreds of innovation books, cut spines, attempted mass scanning via OCR
OCR produced unreliable results, required extensive manual cleanup, abandoned approach
2016-2017
Hired professional researchers, students, and writers
Developed dual-summary process: two researchers per book, merged by professional writers
Process yielded insights but proved expensive and time-consuming
Quality assurance revealed many “obvious” rather than “insightful” findings
2018
Hired Sagence consulting firm
Extended research team with consultants and digital content specialists
Built structured web research process to identify and catalog innovation content
Developed rigorous documentation with full attribution, converted to structured data
Process quality improved but remained expensive without ML expertise
2019
Began building technology platform
Traveled globally to meet with development agencies
Traveled to Kyiv to define and scope platform requirements
Platform estimated at $500K+ for beta version
Realized need for market traction evidence before major investment
Pivoted to community-building for organic data generation
2020
Prepared V1 video content, experienced performance anxiety
Enrolled in The Second City to overcome filming challenges
Father killed in car accident en route to wedding
COVID pandemic began
Partner’s mother diagnosed with brain cancer
Partner underwent mastectomy and emergency surgeries
2021
Hired specialized consultants and MIT professors
Recruited students to test course materials
Grandmother (primary maternal figure) died of cancer
Took extended break due to accumulated trauma, work effectiveness declined
2022
Hired experienced product leaders as new research team
Purchased and analyzed Twitter (now X) data
Trademarked core philosophies: “There is no try. Only do” and “Learn How. Then do”
Established HowDo trademark
Launched “Big Problems” content series with investment bankers and Luis
Experimented with different content formats and production techniques
2023
OpenAI launched ChatGPT, invalidating original technical thesis
Microsoft invested $10B in OpenAI, signaling acceptance of IP-based training data
Larry Page confirmed AI industry’s IP appropriation strategy at Stanford
Realized original business model was no longer viable
Partnered with Microsoft and OpenAI engineers on RLHF and RAG experiments
Built full-stack AI experience, testing produced inconclusive results
VCs demanded revenue focus, decided to pivot to consulting
2024-2025
Synthesized decade of research into Business Evolution framework
Decision to open-source all innovation knowledge
Prepared final video series teaching systematic innovation
This knowledge represents a decade of systematic research into how humans innovate and build successful businesses. As AI becomes ubiquitous, these fundamentals become more critical, not less. Master these principles, use AI to accelerate your work, and maintain your independence as an innovator.
The future belongs to those who understand both human potential and technological possibility. There are trillions to be made in the space between human creativity and artificial intelligenceβbut only if you know how to navigate it.
Everyone can be an innovator. These are the tools to prove it.
The HowDo Journey
Learn Product Innovation Powered by AI
After 20 years launching products at Amazon, PayPal, Target, Visa, and building my own startup (sold to a Fortune 50), I spent $2M and a decade trying to teach AI how to innovate.
What I discovered: when you systematize innovation for machines, you build a process for humans too.
All entrepreneurs need to master innovation fundamentals using AI as an accelerator. But all AI has biases toward whoever made it.
To keep algorithmic biases from hijacking your business decisions, I’m open-sourcing my innovation process.
“Hope this helps you.” – West Stringfellow
The Research Archive
Over a decade of systematic research, iteration, and testing has produced thousands of pages of innovation knowledge. These resources represent the distilled wisdom from hundreds of books, expert interviews, case studies, and real-world testing.
The Timeline
2015
Potintia incorporated to solve AI training data challenges
Bought hundreds of innovation books, cut spines, attempted mass scanning via OCR
OCR produced unreliable results, required extensive manual cleanup, abandoned approach
2016-2017
Hired professional researchers, students, and writers
Developed dual-summary process: two researchers per book, merged by professional writers
Process yielded insights but proved expensive and time-consuming
Quality assurance revealed many “obvious” rather than “insightful” findings
2018
Hired Sagence consulting firm
Extended research team with consultants and digital content specialists
Built structured web research process to identify and catalog innovation content
Developed rigorous documentation with full attribution, converted to structured data
Process quality improved but remained expensive without ML expertise
2019
Began building technology platform
Traveled globally to meet with development agencies
Traveled to Kyiv to define and scope platform requirements
Platform estimated at $500K+ for beta version
Realized need for market traction evidence before major investment
Pivoted to community-building for organic data generation
2020
Prepared V1 video content, experienced performance anxiety
Enrolled in The Second City to overcome filming challenges
Father killed in car accident en route to wedding
COVID pandemic began
Partner’s mother diagnosed with brain cancer
Partner underwent mastectomy and emergency surgeries
2021
Hired specialized consultants and MIT professors
Recruited students to test course materials
Grandmother (primary maternal figure) died of cancer
Took extended break due to accumulated trauma, work effectiveness declined
2022
Hired experienced product leaders as new research team
Purchased and analyzed Twitter (now X) data
Trademarked core philosophies: “There is no try. Only do” and “Learn How. Then do”
Established HowDo trademark
Launched “Big Problems” content series with investment bankers and Luis
Experimented with different content formats and production techniques
2023
OpenAI launched ChatGPT, invalidating original technical thesis
Microsoft invested $10B in OpenAI, signaling acceptance of IP-based training data
Larry Page confirmed AI industry’s IP appropriation strategy at Stanford
Realized original business model was no longer viable
Partnered with Microsoft and OpenAI engineers on RLHF and RAG experiments
Built full-stack AI experience, testing produced inconclusive results
VCs demanded revenue focus, decided to pivot to consulting
2024-2025
Synthesized decade of research into Business Evolution framework
Decision to open-source all innovation knowledge
Prepared final video series teaching systematic innovation
This knowledge represents a decade of systematic research into how humans innovate and build successful businesses. As AI becomes ubiquitous, these fundamentals become more critical, not less. Master these principles, use AI to accelerate your work, and maintain your independence as an innovator.
The future belongs to those who understand both human potential and technological possibility. There are trillions to be made in the space between human creativity and artificial intelligenceβbut only if you know how to navigate it.
Everyone can be an innovator. These are the tools to prove it.