3. The Economic Argument

The math is simple and hard to argue with. Scrum was designed when implementation was the dominant cost in software development. A team of seven engineers at an average fully-loaded cost of $150,000 represents roughly one million dollars annually. Sprint ceremonies, estimation, and coordination overhead consumed 15-20% of that capacity, but the remaining 80% was spent on the expensive thing: humans writing code. The ceremony cost was justified because it improved the utilization and alignment of that expensive resource.

When AI handles a growing share of implementation, the cost structure shifts. The expensive resource is increasingly the thinking that precedes and follows code production: specification, decision-making, review, and architectural judgment. If a team spends a significant portion of its time in ceremonies designed to optimize code production, and code production is becoming less of a bottleneck, that represents a meaningful investment in coordination infrastructure that optimizes for the wrong constraint.

Dandori redirects that investment. Instead of ceremonies that ask "are our developers productive?" it runs ceremonies that ask "are our specifications precise, our decisions fast, and our reviews thorough?" That is optimizing for the actual bottleneck.