When AI Can Do the Physical Work
Matthew Rubin on why robotics and artificial intelligence belong together, what their progress could mean for everyday work, and what still needs to improve.
Standing Innovation
Posts
These opening notes describe how the founding team intends to approach technology, business strategy, and customer discovery. They are starting principles, not claims of completed client work.
Tesla, SpaceX, and the First Mars Work Crew
A conversation with Robert Morrison prompts Matthew Rubin to examine a Tesla–SpaceX merger, Optimus on Mars, and the work of keeping robots running far from Earth.
Matthew Rubin & Brendan Ahern · 
What Matters Must Be Measurable
Matthew Rubin and Brendan Ahern on using OKRs to turn Standing Innovation’s priorities into focused, aligned, trackable, and ambitious work.
The Room Is Part of the Message
A conversation between Matthew Rubin and Albert Santana on why good communication starts with the logistics of who is present, prepared, and responsible.
Matthew Rubin & Brendan Ahern ·
Law-Firm Intake Should Protect the First Conversation
A practical intake model for faster response, careful information collection, conflict preparation, and attorney control.
How Standing Innovation Approaches AI for Law Firms
An edited founder interview on our intended approach to law-firm workflow automation, attorney review, and practical AI adoption.
Digital Lawnmowing: The Making of a Relentless Technology Operator
How Matthew Rubin went from modding an original Xbox at twelve to building businesses, modernizing school technology, and bringing a lifetime of practical problem-solving to Standing Innovation.
Matthew Rubin & Brendan Ahern ·
Where Operations Meets Go to Market
A joint note from Matthew Rubin and Brendan Ahern on choosing early AI workflows that are both operationally workable and commercially worth pursuing.
Get the Right People in the Room
Why the first useful deliverable is a well-run strategy conversation with owners and deadlines.
Start With the Business Case, Not the Model
A strategy note on choosing a painful, valuable, and measurable first problem.