Startup Success — On Culture, Strategy, and Automation
How individuals and teams can make the most of scarce time and resources to achieve and scale extraordinary results

Culture eats strategy.
This bears repeating… Culture eats strategy.
When it comes to individuals, we accept that our mindset informs our success…
“ I’ve failed over and over and over again in my life and that is why I succeed.” — Michael Jordan
Why do we believe groups of individuals would be any different?
The most successful individuals are successful not in spite of their mindset, but because of it.
The most successful organizations are successful not in spite of their culture, but because of it.
Strategy must adapt.
No strategy fits every situation.
We acknowledge in the abstract that we are imperfect beings who will make mistakes…
“Failure is nothing more than a chance to revise your strategy” — Sissy Gavrilaki
Yet we fear openly admitting what everyone already knows- we screw up. When we ignore mistakes we forgo the chance to revise strategy, and doom ourselves to repeat the same failures.
Trying harder next time is not a strategy. You must change your approach.
The best strategists acknowledge their humanity and learn for their mistakes.
Automation requires prioritization.
We cannot do everything ourselves, at some point we must delegate.
Knowing what to spend time on ourselves, and what not to waste to, is vital to scaling success to the next level…
“It’s only by saying ‘no’ that you can concentrate on the things that are really important” — Steve Jobs
Automating work- whether with a machine or by delegating tasks to employees- is the only way successful individuals can create successful organizations.
Doing everything yourself limits your potential. Delegating everything risks scaling the wrong things.
The best leaders make smart decisions about what to work on, and are always looking for ways to automate tasks.
Scaled Success = Culture of Empiricism + Automation
Since culture is what fundamentally breeds success, and even the best strategies can and should frequently change, the greatest leaders invest their limited time and energy not on what to do (strategy) but on how ‘what to do’ is decided upon and done (culture).
Since strategies must change to be successful over time, the most effective cultures are those which enable rapid, informed adaptations to strategy- hypothesis testing, learning from mistakes, and risk taking.
Cultures dominated by politics, personal egos, or bureaucracy preclude adaptation because mistakes are hidden rather than celebrated. Organizations with these cultures become stagnant, doomed to repeat the same mistakes.
Success requires a culture which appreciates the hard truth that we are only human, not one which denies our very nature. A culture in which:
- Facts outweigh opinions
- Learning outweighs ego
- Outcomes outweigh appearances
I call this type of culture a ‘culture of empiricism.’ Only once a team has embraced a culture of empiricism can they truly scale with any measure of success. You can not delegate processes to machines or human employees if politics, corporate titles, or egos demand decisions be made on opinions rather than metrics and hard data.
Organizations seeking extraordinary success must build a culture of empiricism, meticulously adapt strategy, and carefully prioritize to fully scale to maximum potential. Each of the three pieces is necessary for success. Each on their own is insufficient.
As a developer, scrum master, entrepreneur, and flawed human being who is unabashedly always learning, my goal is to show you how to progress along this journey to a culture of empiricism and your own eventual success.
When I occasionally fail in this regard, I will adapt, and we will both improve.
Matt R O’Connor is a developer, scrum master, and co-founder of Reboot.ai. He writes on a variety of topics including Agile, coding, business leadership, and mindfulness, with a focus on unlocking humans’ potential through the use of technology. His professional experiences include managing teams of 30+ employees, overseeing algorithmic trading for the world’s largest hedge fund, and co-founding Hong Kong’s premier machine learning and artificial intelligence training provider.
