Podbit · BiggerPockets Real Estate Podcast
Foreclosure auctions sat dormant for years, so most investors forgot about them. Henry Washington says they're back, they're fertile, and the room is empty. Even if you don't bid, the old-money cash buyers networking there are worth every minute.
Where this was said
At 10:30 · chapter starts 7:45
This chapter delivers the episode's sharpest insight. Henry Washington openly admits that investors with years of experience — himself included — have grown lazy, relying on automation to pull lists and send mail without ever touching the process themselves. The implication is stark: any deal-finding tactic that requires manual effort, multiple steps, or human interaction is one that experienced investors have opted out of. That's the new investor's moat. [1] — Henry Washington "If you are doing that too, you're competing with me. But if you're getting out and you're riding your bike and you're identifying propertie…" 08:10 Henry illustrates with the example of finding an address, using Claude for skip tracing, and calling the owner while still standing in the neighborhood — a level of immediacy and personalization that no automated system can replicate. Chad chimes in with a memorable real-world example: spending weeks tracking down a property owner through a cousin in Ohio, making a cold call, and buying a deal that multiple other investors had already given up on. [2] — Chad Carson "Multiple investors had tried and given up on this vacant property. Chad Carson spent weeks digging through relatives until he found a cousi…" 08:55
Multiple investors had tried and given up on this vacant property. Chad Carson spent weeks digging through relatives until he found a cousin in Ohio, made one cold call, and walked away with a deal invisible to everyone else. Pure persistence, zero competition.
Chad spent weeks tracking down a property owner through a cousin in Ohio, eventually buying a deal no other investor could access through pure persistence.
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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