When companies compare buying software to building it with LLMs, the old rule was “only build what’s core.” Now tools like GPT and Claude can crank out code faster, but they don’t eliminate human costs. The author points to a LinkedIn story: a team dropped $400/month on Jira in favor of an internal tracker generated and maintained via Claude. At $96/hour for an engineer earning $200k/year, even cutting maintenance to two hours a month, it still takes over three years to match what they’d pay Atlassian. That math makes rebuilding low-cost tools a losing bet. On the other hand, expensive SaaS like Salesforce at $500 per seat per month (50 seats = $25,000/month) flips the script. You could hire the equivalent of 1.5 full-time engineers for that money. Building a replacement CRM becomes feasible. The author calls this span the “zone of viability”: software priced low enough to favor buying (Jira) and high enough to favor building (Salesforce). Where a product sits in that zone depends on novelty (how hard it is to re-implement) and price. He’s betting his side project River lands on the buy-not-build side. River is an open-source Go/Postgres job queue. Basic features are free; advanced workflows, concurrency controls and billing APIs are behind a Pro tier. At $125/month for teams up to 20 developers, it sits in the zone where ongoing license fees undercut LLM-driven rebuild costs. The author acknowledges LLMs could copy River’s features, but argues the design and performance edge makes replicated quality expensive to reach.