Boom Supersonic's move to power data centers with its engines isn't a failure, but a strategic way to fund its capital-intensive vision. This mirrors early Tesla's survival tactic of doing contract engineering for other automakers. Such projects can be a crucial source of non-dilutive capital for deep tech companies.
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For projects requiring hundreds of millions, fundraising should be split into phases. The initial "pre-industrialization" phase, focused on proving technology, is suited for venture capital. Later phases for manufacturing and scaling should target project finance structures with debt/equity combinations and strategic partners.
Founders can waste time trying to force an initial idea. The key is to remain open-minded and identify where the market is surprisingly easy to sell into. Mercor found hypergrowth by pivoting from general hiring to serving the intense, specific needs of AI labs.
Beta Technologies isn't just selling electric airplanes; it's building a network of proprietary "charge cubes" at airports. This strategy, reminiscent of Tesla's Superchargers, creates a competitive moat and ensures viability for its own aircraft. It also establishes a new revenue stream, making money even if a competitor sells the plane.
To maintain product focus and avoid the 'raising money game,' the founders of Cues established a separate trading company. They used the profits from this successful venture to self-fund their AI startup, enabling them to build patiently without being beholden to VC timelines or expectations.
SoftBank selling its NVIDIA stake to fund OpenAI's data centers shows that the cost of AI infrastructure exceeds any single funding source. To pay for it, companies are creating a "Barbenheimer" mix of financing: selling public stock, raising private venture capital, securing government backing, and issuing long-term corporate debt.