AI development tools allow startups to operate with small, elite engineering teams of 2-3 people instead of needing to hire 10-20. This dramatically changes the startup landscape, making go-to-market execution—not developer headcount—the main constraint on growth.

The recent market correction is not a temporary dip but a sustained, permanent course correction. Companies are now expected to maintain an "early startup" efficiency mindset—doing more with less—throughout their growth stages. This shift is reinforced by the industry's focus on AI-driven productivity gains.

Low-cost AI tools create a new paradigm for entrepreneurship. Instead of the traditional "supervised learning" model where VCs provide a playbook, we see a "reinforcement learning" approach. Countless solo founders act as "agents," rapidly testing ideas without capital, allowing the market to reward what works and disrupting the VC value proposition.

Founders often start scrappy out of necessity and dream of lavish resources. However, once successful, many realize that small, lean, and scrappy teams are more effective. This creates a paradox where the most successful entrepreneurs intentionally revert to the resource-constrained mindset they once tried to escape.

Monologue's success, built by a single developer with less than $20,000 invested, highlights how AI tools have reset the startup playing field. This lean approach enabled rapid development and achieved product-market fit where heavily funded competitors have struggled, proving capital is no longer the primary moat.

An alternative to chasing hyper-growth AI is to invest in categories where AI adoption is slower. This provides founders with a crucial time advantage to build durable businesses, but it necessitates a more capital-efficient model that can't sustain a hyper-frequent fundraising pace.

Despite raising $380M and hitting $187M in revenue, Boxed's co-founder owned a low single-digit percentage at IPO and did not achieve significant personal liquidity. This is a cautionary tale against the 'growth at all costs' mindset, which can heavily dilute founders in low-margin businesses.

A unique dynamic in the AI era is that product-led traction can be so explosive that it surpasses a startup's capacity to hire. This creates a situation of forced capital efficiency where companies generate significant revenue before they can even build out large teams to spend it.

As AI enables founders to build products in a week for under $500, the need for traditional seed capital for engineering will diminish. The bottleneck—and therefore the need for capital—will shift to winning the intense battle for user attention. VCs will fund marketing war chests instead of just development.