CHRIS MACPHERSON
ABOUT
- Entrepreuneur
- Design Strategist
- Technology Architect
- Operator
- Professor
- Speaker
- Musician
My career has focused on designing and building teams, products, and tools using innovative design and emerging technologies. Most recently, I led growth and strategy at Shift, an a16z backed startup, where I launched our federal business practice and built a best-in-class venture capital and startup industry immersion program for innovators in the military (the Defense Ventures Program).
I currently teach a course on creativity and design at Princeton University, and work on projects through my consultancy, Shadestream.
In past roles, I was a key architect in developing the applied data and intelligence systems go-to-market practice at Frog Design, built and led an internal talent research startup at Bridgewater Associates, oversaw counterterrorism and influence operations at the Pentagon, ran a team at the White House Situation Room, and was recruited out of college by the NSA. I am trained as a computer scientist and hold advanced degrees from Princeton University and National Intelligence University.
This portfolio is a sample of my work and interests. If you’d like to get in touch, send me a message at chris@shadestream.com or connect with me on Linkedin.
BUILD
To Reimagine
- Taxation
- Healthcare
- Hiring
- Public Service/Civic Participation
- Community
- Governance
- Higher Education
- Transfers of Wealth
- Labor Unions
Whys (Questioning assumptions)
- Is gaming the next large-scale form of human cooperation? (like money, religion, and nations)
- How capturing data about behavior actually changes behavior (are you shaping the data or is the data shaping you?)
- Why aren’t there new pricing models?
- Why do we hire individuals instead of teams?
- Why is hiring based on pattern matching?
- Why is college four years long?
Hows (New approaches)
- Thinking tech (Abductive reasoning technologies)
- Large scale simulations
- Affective computing
- Minimnum viable communities
- Pay for Value vs Pay for Service
- Sustainable investing (returns not based on debt that future populations have to pay back/into)
- Augmented intelligence platforms
- 21st century design
- Volumetric data & edge compute
- Synthetic media
- Layering digital intelligence into physical structures
Wheres (New markets)
- Rise of robots/autonomy
- Esports & gaming
- Cohort-based learning
- New frontiers of manufacturing (Syntheic biology, warehouse zero, and sustainibility)
- Non-permissive logistics
- Rethinking urban environments
- Blockchain governance
- Tech for aging populations
- Decision science
- Decentralizing national security operations
- Outer Space
- No code rapid prototyping
Whats (Problems to solve)
- Humans and robots working together
- Cameras/sensors that count things
- Understanding intent from imagery
- Insurance in space
- Consumer owned career experience records (apple health kit, but for work)
- Metaverse for learning
- Passwords from biometric data
- Human behavior simulators
- Mapping social networks
- Organizing businesses around decision making
- AI integration/AI design
- Making consumer data more actionable (vs reportable)
- Qualitative data extration and preprocessing
- Decision anticipation
- Diversity of thought and experience
- Professional Networking & Mentorship
- Expert Networks
- Loneliness
- Layoffs
- Ageism
- Getting rid of resumes
- Future of work (money, meaning, discretion, learning, and connection)
- Revitalizaing legacy cities
Futurist and Fun Ideas
- Dogs in Space (I’m not sure humans could have survived on earth without dogs, and I don’t believe we can in space either).
- Teach a Mars Colony Simulation Class
Back
TECH
Experiences
- Shift (2019-2022)
- NSA (2000-2003)
Skills
- Operation
- Product Management
- Pricing, Revenue Modeling
- Client Management, Sales, Pitching
- Recruiting
- Python, Java, SQL, Neo4J Graph Query, CMS/CS
- Modeling, Data Analysis & BI Tools
My father would bring IBM XT computer home from work on the weekends when I was a child. I’d spend hours breaking and rebuilding the MS-DOS operating system (it was the 80s), playing GWBasic floppy disk games, and exploring the local BBSes which predated the internet with a 14.4k modem.
During college, I worked front end web development at Skillview Technologies, a startup backed by Berkshire Capital Investors (which eventually became Village Ventures) in Western Massachusetts. After college, I joined the National Security Agency as a computer scientist. While I started out as a software engineer, I soon transitioned to a position that today would likely be called a data scientist. However, it was called something else back then because the term data scientist wasn't in use yet.
My intelligence career allowed me to investigate and model human behavior and decision making. I liked it more than pure coding, and because of advancements in computers, data storage and algorithms, much of my work since then touches on how data and intelligence can transform different industries and missions. I am more of a decision scientist than a data scientist, but I still enjoy coding and building products when I can.
Back