Stars Aligned and Software Development Adrift - Why Can We Predict Planets but Not Deadlines?
summary
Argues that projects with unknowns are intrinsically different from linear work and that 20% of onboards at one talent-management vendor forced platform rewrites that derailed multiple teams; proposes swapping predictive plans for empirical, people‑centric practices, trial‑and‑error feedback loops, buffers and contingency plans, and tactics to amplify dissonant voices and spot blind spots early. Cites practical precedents (Toyota, Olivetti, Christopher Alexander) and a Ferrari vehicle‑performance leader whose methods delivered 14 championships, claiming the approach reduces failed estimates and improves resilience under uncertainty.
AI-written summary · about
chapters (8)
- 0:00Projects feel like manholes
- 4:26Intractable problems and opportunities
- 12:53Organizations ready for uncertainty
- 19:36Why philosophy matters now
- 24:40New vs mechanistic paradigms
- 32:31Leading teams through change
- 37:06Transformed organizations
- 39:15Reflections and Q&A
related talks
51mNavigating Uncertainty in Software Development: Effective Planning Techniques
41mWhy Promising Nothing Delivers More and Planing Always Fails
53mThe Human Side of AI: Unlocking Opportunity in the New Bottlenecks of Software Development
26m2024 09 21 34 PAULINA CHOJNOWSKA -The Illusion of Success: When Delivering on Time is not Everything
53m#NoProjects Beyond Projects - Why Projects Are Wrong & What To Do Instead
37mWhy agile
55mThe Art of Prediction
58mReturn of the rockstars? Building great teams in challenging times