You are going to get priced out of the best AI coding tools (newsletter.danielpaleka.com)

A recent analysis argues that the era of inexpensive, broadly accessible AI coding assistants is ending: tools that used to be $10/month (GitHub Copilot) are being replaced by much pricier tiers (Claude Code’s cheapest usable tier around $100/month) and an apparent trend of rapidly rising top-tier subscription prices. The author cites an exponential-like pricing pattern across products and even mentions a reported OpenAI investor discussion about $20k/month “research agents,” suggesting premium, compute-heavy offerings are already being envisioned — meaning the best tools could move behind high paywalls. That shift matters because the biggest cost driver is inference: running frontier LLMs continuously, faster, or in parallel (sampling multiple runs) improves coding and research outputs but multiplies compute cost. Empirical effects like Pass@K gains remain large (DeepSeek-R1 showing ~70% pass once vs ~86% with 64 samples), so better UX and higher success rates almost directly translate to higher prices. The practical implication is academic labs, individual researchers, and students risk being priced out while industry labs may spend $200k+/year per employee on tooling. Counterarguments—competition/open-source pressure, hardware and algorithmic efficiency, or diminishing returns on inference scaling—exist but the author is skeptical they’ll prevent significant price stratification.