The module gives a rigorous analysis of how startup economics have changed through two distinct mechanisms that compound each other. The first: agentic coding compresses development cost and timeline, making projects economically viable that were not before and allowing small teams to build and iterate at the speed that previously required large engineering organisations. The second: cognification opens new product surfaces in domains where software was previously too expensive or too slow to be the solution, such as legal platforms automating document review, fintech systems reasoning over transactions, and operations teams building internal tools.

Case studies are examined analytically rather than anecdotally. For each case the specific mechanism of value creation, the organisational condition that made it possible, and the risk that was managed or ignored are identified. The cases include TELUS reducing 500,000 hours of work through AI-augmented workflows, Zapier achieving 89% AI adoption across the organisation, and a lawyer with no coding background building a Claude-powered legal review workflow that reduced turnaround from days to hours. The analysis frame is what made this work here, and what would have to be true for it to work somewhere else.

The new bottlenecks are as important as the compressed constraints. Development cost and timeline are no longer the primary obstacles for a founder with agentic tools. Distribution, customer understanding, judgment about what to build, and the ability to iterate quickly on product decisions are.