Hera's target is not just existing After Effects users, but the larger market of people who need motion graphics but find professional tools too complex or expensive. By lowering the barrier to entry, AI tools create entirely new markets of creators, much like Airbnb did for home rentals.

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.

The new wave of entrepreneurship isn't about scaling large companies. It's about solopreneurs acting as "gig entrepreneurs" who master and customize a suite of AI tools to deliver bespoke, high-value outcomes for clients, effectively replacing the work of entire small agencies.

Advanced AI like Gemini 3 allows non-developers to rapidly "vibe code" functional, data-driven applications. This creates a new paradigm of building and monetizing fleets of hyper-specific, low-cost micro-SaaS products (e.g., $4.99 per report) without traditional development cycles.

Early in a technology cycle like the web or AI, successful founders must be technical geniuses to build necessary infrastructure. As the ecosystem matures with tools like AWS or open-source models, the advantage shifts to product geniuses who can build great user experiences without deep technical expertise.

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.

The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.

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.

While the internet has consolidated around major platforms, AI presents a counter-force. By drastically lowering the cost and complexity of building mobile apps, new tools could enable a 'Cambrian explosion' of personalized applications, challenging the one-size-fits-all model.