High-signal observations from Year 1 of building real AI systems. Just thinking out loud about AI, privacy, and systems design.
Every AI product I see treats privacy as a checkbox — GDPR compliance here, a toggle there. That's backwards. When you design for privacy first, you end up with fundamentally different architecture. Foretyx exists because I needed to build that architecture before someone just bolted compliance on top of an inherently leaky system.
Writing code is the last thing I do. Before a single line, I'm drawing architecture, asking what breaks first, what scales worst, what the real user actually needs. Scripts are temporary. Systems compound. The engineer who understands the system controls the engineer who just knows the syntax.
Everyone talks about GPT-4 and Gemini. The more interesting story is DeepSeek running locally on consumer hardware. When AI inference becomes free and private, the entire cloud AI business model breaks. I'm building for that world now, not waiting for it to arrive.