Jensen said that training GPT-1 cost about twenty million dollars and today it’d cost maybe a hundred dollars. That 200,000x compression in under a decade tells the whole story right there. We are still early in the AI cycle, going through fast-paced innovation with things improving by orders of magnitude across every layer of the AI stack (hardware, models, apps/agents, etc). We cannot build a house when the ground underneath is shifting. Same way, we cannot build a product, business model or a business today when the technology landscape underneath is shifting on a weekly basis. New models are dropping every week and token prices are dropping ~10x a year. Stability is needed to build. During such phases, pioneers end up paying the pioneer tax, which explains why they don’t always make it (which I talked about in my previous post). Real winners come downstream after there is stability and the pace of change slows down. At the current pace, being early is expensive. Being early when costs are collapsing at this pace is a trap.