I Cut $150/Month on AI Tools and Got Better Results With Open-Source

Description and use

The author cut AI tool costs from $150/month to zero by replacing paid services with local open‑source solutions, boosting feature delivery, reducing bug‑fix and review times, and lowering tool frustration.

Problem

The author was spending $150/month on multiple AI subscriptions with overlapping functionality and limited cost‑benefit.

Outcome

Zero monthly AI cost, increased feature delivery, reduced bug fix and review times, and lower frustration while maintaining productivity.

Workflow

• Cancel all paid AI subscriptions
• Set up local LLM inference with Ollama (pull llama3.1:8b)
• Install Continue VS Code extension for code completion
• Use Claude Code free tier and Goose for chat/debugging
• Run Goose to execute code for debugging
• Use OpenWiki CLI to generate documentation
• Benchmark models with whichllm and serve with RamaLama
• Iterate on documentation and code using local tools

Evidence

I was spending more on AI subscriptions than on my coffee habit, and getting about the same quality.

Source

After three months, here's what actually changed: Monthly cost $150 → $0, Features shipped ~8/month → ~10/month, Bug fix time ~2h → ~1.5h, Code review time ~45min → ~35min.

Source

Continue + Ollama replaced Copilot and Cursor's inline suggestions.

Source