In the early years of building Ordaos, issues arose due to lack of clarity on the end user and success criteria.
A cross-functional team built a product without aligning on the actual end user, resulting in a product that didn't meet any real need.
The Scrum Master applied Agile Methodologies and Scrum to the machine learning team, but it didn't work well for building proteins from scratch with AI.
Introducing a Kanban board and daily stand-up led to improved teamwork and a shift towards focusing on 'good enough' rather than perfection.
A workshop focused on thorough planning and debriefing after each mission brought about a company-wide shift towards learning and reflection.
Building a high-safety, high-trust culture where honesty and learning are encouraged was seen as essential for a serious scientific organization.
Culture in startups is crucial for how people work, make decisions, and respond to challenges, and it impacts execution directly.
Execution and culture are intertwined, requiring clear priorities, shared language, and habits to keep a team aligned for effective delivery.
Scaling execution in science necessitates systems that accommodate uncertainty while fostering shared momentum and delivering meaningful outcomes.
Building a team that can deliver what is truly essential entails understanding the connection between execution and culture.