startup-economics

3 items

Wall Street Journal 2026-04-02-1

To Lure Top AI Talent, Startups Are Turning to Cold Hard Cash

Median startup SWE base jumped 25% since 2022; total comp only 18%. The gap is the story: equity's share of the package is shrinking. Startups are paying FAANG cash without FAANG revenue, and the retention mechanism that made equity valuable — time-locked upside — is dissolving alongside vesting cliffs. The bill comes due when the funding cycle turns; the base rate on every well-funded AI startup becoming a generational business is about 2%.

Colossus 2026-03-21-1

We Have Learned Nothing: The Red Queen Eats Startup Method

BLS survival data is flat over 30 years and Crunchbase seed-to-Series-A conversion is declining: Jerry Neumann's case that Lean Startup, Customer Development, and the rest of the New Punditry produced zero measurable improvement is empirically anchored. His prescription is a Red Queen meta-theory via Feyerabend: any method, once widely adopted, becomes self-defeating through competitive convergence, so the only science of entrepreneurship operates at the level of generating new methods, not prescribing them. The convergence argument is the strongest element; the data argument has an ecological fallacy problem (BLS counts restaurants alongside SaaS startups) and a missing counterfactual (flat survival might mean methods prevented a decline, which is the Red Queen working within punditry itself). The sharpest extension is to AI-native startups: if method convergence is the mechanism, AI collapses the cost of convergence to near-zero; everyone builds the same thing faster, differentiation half-life shrinks to weeks, and the Red Queen sprints where she once walked.

Wired 2026-03-16-2

Can AI Kill the Venture Capitalist?

The real VC disruption isn't AI replacing analysts: it's AI eliminating the customer. When a $300M-revenue company can reach unicorn status with 100 people and zero venture funding, the disruption is demand-side: startups don't need the capital. The "Moneyball for VC" thesis is flattering but structurally wrong; VC has a data poverty problem, not a data utilization problem.