Lately, I ve been looking closely at how independent builders and small teams are managing AI knowledge bases. It feels like the default "industry standard" is to immediately reach for a complex RAG pipeline and a heavy, paid Vector Database.
But I'm starting to wonder if we are over-engineering this for 90% of standard use cases.
Vector DBs are incredibly powerful for massive scale, but for smaller or non-massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare.
We recently implemented custom domain support in Inquir Compute, and it feels like one of those features that really changes a platform from works technically to ready for production.
For me, custom domains are a core part of production-grade infrastructure. They are not just cosmetic they affect branding, trust, onboarding, and the overall developer experience.
I d be curious how others think about this in serverless and deployment platforms:
At what point do you consider custom domains a must-have?
What parts are usually the hardest in practice: DNS flow, TLS issuance, routing, verification, or UX?
Do you prefer keeping platform subdomains as the canonical entry point, or treating custom domains as the primary one?
As usual, Y Combinator came up with segments that are worth investing:
1. Cursor for Product Managers
2. AI-Native Hedge Funds
3. AI-Native Agencies
4. Stablecoin Financial Services
5. AI for Government
6. Modern Metal Mills
7. AI Guidance for Physical Work 8. Large Spatial Models 9. Infra for Government Fraud Hunters 10. Make LLMs Easy to Train
I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market. That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.
In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.
For those of you building AI or compute-intensive tools:
This is something I ll find out in just a short while, one week from now (Jan 28), as I m about to re-launch a digital detox app. If you want, follow, maybe you will be on watch of my steps and activities
