Yusuf Young

That was annoying in 2019. It's going to be indefensible in 2027.

When software development costs near zero, the economics flip. I wrote about this in detail: how the software industry changes when building software becomes cheap. The short version: building custom software for a single company will become cheaper than researching and selecting the right off-the-shelf product. Generic SaaS doesn't survive that shift unless it's the dominant scale player.

So I'm building the thing that kills generic CRM: a service that builds and maintains custom CRM software for each customer. Not a no-code platform. Not a configurable SaaS. A service that delivers software built around your actual workflow.

The hard part isn't building the software. AI handles that. The hard part is knowing what to build. Most agencies skip this step. They ask you what you want, you list features, they build features, and you get software that's as generic as HubSpot but with worse UI.

The moat is a system that observes how your team actually works, learns what they need, and generates specifications from real usage patterns instead of feature requests. That system is the product. The software it produces is the deliverable. No customer can replicate it because the intelligence lives in the observation and learning layer, not in the code it outputs.

Phase 1: replace HubSpot, Salesforce, and Pipedrive for mid-market companies. I know this domain cold. Phase 2: expand to other software categories using the same methodology. Phase 3: replace any legacy software.

This is early. I'm building the core system now.

• If you're a potential customer tired of paying HubSpot or Salesforce for software that doesn't fit your workflow, email me. Early customers get input on the product direction.
• If you're an investor who understands that AI changes the unit economics of software, let's talk. I'm looking for partners who get the thesis, not just the market size.
• If you're a potential partner with AI engineering depth or GTM experience in mid-market CRM, reach out. This is a big problem and I'm not trying to solve it alone.

If OpenAI, Google, Anthropic, or xAI changes their model, their pricing, or their terms of service, your business adapts. If they decide not to serve you, you're done. You don't own your intelligence. You're renting it from someone who can evict you.

I wrote about where this leads in how the software industry changes when development costs near zero. When building software becomes cheap, generic SaaS loses to custom software built per company. The same shift applies to intelligence itself: when AI is powerful enough to run a company's operations, renting a generic brain from four vendors won't be competitive with owning one that knows your business.

I also wrote about the path from LLMs to AGI. We're closer than most people think, and the mechanical path is clearer than the philosophical debate suggests.

The thesis: every company needs its own AI, trained on its own data, running on its own infrastructure, under its own control. Not a rented API. Not a shared model. A sovereign intelligence that belongs to the company the way its codebase and customer list do.

This is what I'm building with Aether. A runtime that lets any company run its own agent, on a server it controls, with full visibility into what it does and why. The long-term goal is a network of independent, cooperating agents, each owned by the entity it serves.

The technology for this exists. The bottleneck isn't capability. It's trust: companies need to trust their own AI the way they trust their own employees. That's a sovereignty problem, not a model-size problem.

• If this thesis resonates, whether you're an investor who sees the shift, a company that wants to own its intelligence, or an engineer who wants to build it, let's talk.