I created a skill to better manage agents, including a way to keep the caches valid, and it has decreased my usage considerably. I now struggle to use my 100% each week and I hit claude hard. I have a reset expiring in 5 days and I'm trying to burn down the tokens (68% with 3d 8h left) quickly so I can use my reset before it expires.
Token efficiency just means understanding the way the system works. Best person to help with that... my old friend claude.
However where i think you have a point is that it tends to run tests quite casually where a reviewer would have been enough to catch mistakes.
IMHO, the real problem is the 5min cache way too small. They should up it to 1 hour.
I don't actually know the real mechanism, I came across this serendipitously.
Buid alone takes 4 minutes. Test suite heavily parallelized runs in about 2 to 3 minutes, infrastructure dependencies fully containerized using podman, no external API call.
And this is without mentioning the 5000 frontend tests (angular), including Playwright end-to-end tests wired to the backend (about 3 to 4 minutes run without the e2e tests).
And this is running on a dev machine with 64gb of RAM and an NVMe disk.
Some systems are just massive, and even if you run focused tests, it's easy for a change to have a large blast at least requiring a large rebuild, and at times to rerun a larger set of tests.
Claude: Confirmed: 195M of the 212M cache tokens (92%) come from full re-writes after 5+ minute gaps, accounting for 77% of relative cost. Now I'll check the existing wrappers so the skill builds on them.
Can you invert things. What’s deterministic and what needs “thinking”?
Can you create a script that runs things chaining together the deterministic parts with calling out to Claude for glue that needs “thinking”.
I think the tests problem is really having an impact for me. Hadn't considered it before so thanks for flagging.
Maybe doing bogus small requests to prevent the cache from expiring?
I mean in the API you can set the cache expiration time right? But I guess claude code can't do this
Awfully new old friend.
What exactly are they doing for you that's giving you $200 of value in such a short timeframe?
- How long do you reckon it would take a human to do the task?
- What percentage of features/ feature-extensions you add would have been done at all if you didn't have agentic assistance? Is there a tension between llm productivity gains and 'because we can' feature additions?
- Are many of the tasks for throwaway v1 features, exploratory tries?
- How speced out is the work you give it, eg did this task have pages of specs, how long did the spec take to write?
- How deeply will you manually review the work and how much time will it take? Will you read all the code / review at a high level and interrogate with llm / have the llm review and self iterate?
I do now add all the major features I want, and write a task list where I add a few more minor tasks each week that just come to my mind. I need to write them down before I forget. I often ask Claude to implement several different implementations/algorithms and compare them. There are plenty of trade-offs, which usually end up in building configuration profiles, so the application can work optimally in multiple environments.
The specification is actually really large, and has grown over time as I've been learning and new ideas has come to my mind. I do not review/audit the code, it's massive would take me months, no chance! I do however use code inspection/audit tools like TSAN, ASAN and more. I will also spend time on full code reviews with the coming Fable 5.5 when a release is about ready. I do however review behavior together with Claude, and this is also where the specification grow, because this and that should be possible, but not this and that. User stories also helps.
There's no reason to blow through tokens this way, there's a 99% chance nobody uses the output (except maybe themselves).
That’s the “how” we’re wondering about.