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I think people really need to focus more on working with limited contexts rather than trying to work around it. I really try to keep my sessions as short as possible and it helps a ton with keeping Claude (et al) focused.

Specifically, I like the "canary" trick that people have discussed where you add a small, innocuous rule to your CLAUDE.md like "When responding to me, start every sentence with my name." so that when Claude stops doing this, you know you've used way too much context and need to start a new session.

boc 4 hours ago [ - ]

I set my env up so I can see the exact context used in CC CLI, and then once I get over about 40% ctx used I have it handoff to a new, fresh session. Nothing good comes from running above, say 60% of your context window. Coincidently, I usually have good results with CC. I never compact a session ever.

jen729w 4 hours ago [ - ]

This is the way. Mine looks like `ctx: 0k / Fable 5 high`. When ctx ⪆ 200k, time to start a new session.

```statusline-command.sh

    #!/bin/sh
    input=$(cat)

    model=$(echo "$input" | jq -r '.model.display_name // empty' | sed 's/ context)/)/')
    effort=$(echo "$input" | jq -r '.effort.level // empty')
    used=$(echo "$input" | jq -r '.context_window.total_input_tokens // empty')
    out=""

    [ -n "$used" ] && out="ctx: $(( used / 1000 ))k"
    [ -n "$model" ] && out="$out / $model"
    [ -n "$effort" ] && out="$out $effort"

    # bright yellow + bold
    printf '\033[1;93m%s\033[0m' "$out"

```

faizshah 12 hours ago [ - ]

This or you just repeat the initial prompt every 200k tokens

ianjbutler 9 hours ago [ - ]

Which gets you to the point where the whole thing is.. still unreliable. Generative text engines are going to generate. This calls for real enforcement in deterministic pre-edit hooks.

And here is where naive people will say something like "Why do I care if robots shit all over the codebase? Code is for machines, I don't expect to deal with it much now". But really externalized CoT like this confuses machines too, wastes tokens, and eventually wastes exponentially many tokens. Agents tend to think it's more real grounding than prompts are, even for comments-in-code. One bad comment poisons everything, then gets copied around as a ground-truth assumption everywhere. Hooks are more real to them than prompts or comments, and even then if you add enforced limits and tell them to externalize CoT ONLY in scratch task-tracking docs.. they will violate comment-enforcement hooks about 25% of the time. That tells you everything you need to know: even with constant reinforcement, they just really want to break this kind of rule.

purplepatrick 2 hours ago [ - ]

Yup. If only there were a task completion hook that could be set to fire prior to rendering terminal output. That would more handily address all these issues, as we could simply enforce output style rules that way.

The current output style does work, but it’s a Sisyphean task to tweak it constantly only to find out that CC adhere’s to only 75% of it, no matter what…

faizshah 5 hours ago [ - ]

My take on this is they are a tool to help speed up your work they are not meant to produce finished work. Humans produce finished work. LLM will never be deterministic cause their entire value is that they are generalizable.

ianjbutler 2 hours ago [ - ]

I hear that, sort of, but here's the thing. Using AI at scale means AI needs to be nearly perfect about not shitting where they eat. That's the subject matter of the whole thread

So the options are a) being a really aggressive stickler for generative hygiene with deterministic rules, b) being massively wasteful about hiring a few machine janitors for every machine coder, or c) humans become the machine's janitor. If I haven't missed an option.. only the first option seems reasonable here.