Podbit · The Prof G Pod with Scott Galloway
Modern investment banks are engineers, not bankers. They manufacture scarcity around IPOs to guarantee a 20% first-day pop — Galloway predicted SpaceX's pop at 20% and it came in at 21-23%.
Where this was said
At 2:45 · chapter starts 1:22
Galloway methodically walks through SpaceX's IPO numbers, noting the stock priced at $135, opened at $150, and peaked somewhere between $210 and $230 — implying a $2.8 trillion market cap that briefly made it one of the most valuable companies ever listed. The fall from grace came fast: a single trading day saw $400 billion evaporate, the second-largest one-day market cap wipeout in stock market history [1] — Scott Galloway "SpaceX shed $400 billion in a single trading day — the second-largest one-day market cap wipeout in history. Yet it still trades above its …" 01:22 . By June 26th, shares had settled at $153, with the company's value reduced to about $2 trillion and the stock sitting more than 30% below its peak. Galloway's verdict is calibrated: 'still an enormous success story' because the base was so astronomical. The key contextual point he makes is that the magnitude of dollar losses is a direct function of the magnitude of gains — SpaceX lost $600 billion precisely because it had a $2.5 trillion market cap to begin with. This framing sets up his broader thesis about whether IPO investors and underwriters will grow more cautious.
SpaceX reached a $2.8 trillion market cap after its IPO, making it one of the most valuable companies ever listed.
SpaceX shed $400 billion in a single trading day — the second-largest one-day market cap wipeout in history. Yet it still trades above its $135 IPO price, making it an undeniable success story despite the carnage.
SpaceX shed $400 billion in market cap in a single day, the second largest one-day wipeout in stock market history.
SpaceX shares remained more than 30% below their peak by Friday June 26th, though still above the IPO price.
SiteGPT attracted over 1 million visitors and $500K in total revenue without spending a cent on paid marketing. The secret: engineering as marketing — building free tools that rank on Google.
Bhanu quit his first job after just 8 months, moved back to his parents' house to cut costs, and started building. One product sold for $250K; the next hit $10K MRR in its first month.
90% of SiteGPT's Google search traffic comes not from the main product but from ~50 free tools Bhanu built. Each tool targets a low-competition keyword and funnels users back to the paid product.
50,000 monthly visitors become 200 leads, 60 trials, and roughly 15–24 new customers per month at ~$100 average revenue each. Add a $1,700–$1,800 LTV and you have a very healthy SaaS.
Start with a blank Ahrefs search, layer in keyword filters (include term, KD < 10, volume > 1,000), list candidates in Notion, design a CTA linking to your main product, then score by volume, difficulty, build effort, and product relevance. That's the whole playbook.
Marketing feels painful for most builders. Engineering as marketing flips the script: instead of writing cold emails or blog posts, you build things — and those things rank on Google forever.
Don't spend months perfecting before launch. Ship the core feature, get real users, and let their feedback dictate the product roadmap. Premature polish is a trap.
SiteGPT launched and hit $10,000 MRR within its first month. That momentum was so overwhelming that Bhanu sold his existing SaaS, Feather, for $250,000 to free up all his time.
PropGPT launched with 20 downloads a day and strong influencer marketing but hit a ceiling at $1,000–$2,000 MRR. High download numbers masked a critical flaw: almost nobody stuck around after the free trial ended.
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