Suggestions
Christian Ulstrup
Experienced professional with multiple certifications and awards
Christian Ulstrup is a seasoned CEO, Sr. Product Manager, and startup advisor with a decade of experience in helping innovators break into new markets and achieve rapid growth.
Christian's strategic approach to product development, strategy, and go-to-market strategies has proven effective in enabling distributed teams to focus intensely and gain traction with minimal resources.
He has a rich history of working with startups at various funding stages, ranging from Pre-Seed to Series C, across diverse sectors like B2B SaaS, MedTech, Health Tech, e-commerce, and tech-enabled services. Additionally, he has assisted small business owners in leveraging AI and digital media for success.
Christian's expertise in setting and managing OKRs (Objectives and Key Results) has earned him praise from colleagues and clients alike. He has significantly impacted companies like NuvoCargo, Strongest AI, and Arterys through his guidance on OKR processes.
Having studied Entrepreneurship & Innovation for his Master of Business Administration at Massachusetts Institute of Technology and Economics for his Bachelor of Science at Duke University, Christian possesses a strong academic foundation to complement his practical experience.
Currently, he serves as an advisor at GSD @ Work, having previously held positions such as CEO & Co-founder at Virgils, Senior Product Manager at Arterys, Head of Product & Technology at Iterative Scopes, and Product Manager at Red Bull Media House.
Christian Ulstrup's diverse background in business, product management, and technology equips him to offer valuable insights and guidance to organizations seeking lean growth strategies.
For personalized consultations on achieving rapid growth in a week or less, connect with Christian at https://gsdat.work.
Highlights
Starting to suspect that there is some positive correlation between complexity (entropy? varentropy??) and healthy team size, and then negative correlation between context window length limits and team size.
The bigger the context windows, the fewer layers of management you need; but, the more interesting and novel (and voluminous) the data you produce by serving customers, the more human intermediaries you need to get their hands around compressed representations and handle exceptions.
The most central node has the responsibility of handling the gnarliest anomalies at the greatest scope.
Compression (AI) begets expansion (of the lightcone), which yields a greater whole through unprecedented difference and all this is making me want to revisit de Chardin...
Hunch that evals won't even make sense for the most powerful ai applications
Location
People also viewed
Mutual Connections
People also viewed