Ask HN: What works for cutting AI token costs?
6 comments
When I work with AI to build something I like to summarize every conversation into separate folder and basically keep a journal for AI. This is how it looks like:
"journal" folder:
- 2026-05-12 Add comments support for the cells.md
- 2026-06-15 Rework onboarding screen.md
Each document contains show description of the problem and explanation how did we solve it. Then If I need to go back in time and improve one of the features I can use one or multiple of those files as a reference so we don't need to "rescan" entire code base and re-analyze it. And the most important - I'm not loosing some decisions we made which from the code alone can be considered bugs but they are features actually
"journal" folder:
- 2026-05-12 Add comments support for the cells.md
- 2026-06-15 Rework onboarding screen.md
Each document contains show description of the problem and explanation how did we solve it. Then If I need to go back in time and improve one of the features I can use one or multiple of those files as a reference so we don't need to "rescan" entire code base and re-analyze it. And the most important - I'm not loosing some decisions we made which from the code alone can be considered bugs but they are features actually
Haven't benchmarked it, but for agentic coding e.g. Claude Code I found this useful:
https://github.com/rtk-ai/rtk
https://github.com/rtk-ai/rtk
Besides switching to cheaper models, what have you personally used to reduce cost in real applications?