1 link tagged with all of: llms + cost-analysis + saas + build-vs-buy
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The author breaks down how large language models lower software development costs but don’t eliminate human-driven feedback loops and ongoing maintenance expenses. By comparing real-world SaaS prices (Jira at $400/month vs. Salesforce at $500/seat) to engineer-hour costs, he defines a “zone of viability” where buying remains cheaper than LLM-powered rebuilding. He frames his own project River against this threshold to gauge its business potential today.
- Rebuilding cheap SaaS with LLMs doesn't pay off: replacing $400/month Jira takes over three years to break even at $96/hour engineer costs, even with minimal maintenance.
- Expensive per-seat SaaS like Salesforce ($25,000/month for 50 seats) crosses into "build" territory since that budget covers 1.5 full-time engineers.
- The "zone of viability" for buy-vs-build depends on both price and novelty/difficulty of re-implementation, not price alone.
- River (Go/Postgres job queue, $125/month Pro tier for up to 20 devs) is positioned to stay on the "buy" side because its design and performance edge make LLM replication costly despite feature copyability.