Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
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Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#2Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#3Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#41. Read X feature of Y and tell me when you fully understand it (if there's any detail missing in the summary, repeat until the context is primed)
2. What time is it?
3. /goal Spend X minutes from $time writing a technical design doc on $feature. There must not be any vague language or ambiguity in the document. Read carry_forward_requirements.md and testing_best_practices.md and explicitly incorporate them into the document you write. The document should be executable for a contextless implementer when done and include specific code and document references and changes needed. Spend the full X minutes working on and reviewing this document - do not quit early and wait
Even just spending 10 minutes forcing GPT to write a design doc results in much more robust plans than plan mode, in my experience, and saves time I would spend iterating on the initial plan mode draft anyway.
Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#5The chart at the top is somewhat confusing. It says, “lower is better” but the y-axis is inverted! So visually higher in the chart is better but lower in terms of # value.
Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#6/goal has replaced plan mode for me. This is the pattern I use for 95% of my AI work now: 1. Read X feature of Y and tell me when you fully understand it (if there's any detail missing in the summary, repeat until the context is primed) 2. What time is it? 3. /goal Spend X minutes from $time writing a technical design doc on $feature. There must not be any vague language or ambiguity in the document. Read carry_forwa…
Hmm, I feel like this is akin to making a recursive function have a exit condition not based on what it actually did/found, but based on how long time it took.
I'm always using /goal with explicit goals that the agent needs to achieve. Time-bounding them wouldn't make sense, I want something specific done regardless of how long time it takes.
So instead I'd put goals on what the design/architecture needs to achieve, and for the model to continuously check the outcome against these, then finish when everything is achieved. Doesn't really matter if it takes 10 minutes or 10 hours, which for me is a bit the point of /goal in the first place, otherwise I'd just use the agent normally.
Re: Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?
#7/goal has replaced plan mode for me. This is the pattern I use for 95% of my AI work now: 1. Read X feature of Y and tell me when you fully understand it (if there's any detail missing in the summary, repeat until the context is primed) 2. What time is it? 3. /goal Spend X minutes from $time writing a technical design doc on $feature. There must not be any vague language or ambiguity in the document. Read carry_forwa…
> 3. /goal Spend X minutes from $time writing a technical design doc on $feature. Hmm, I feel like this is akin to making a recursive function have a exit condition not based on what it actually did/found, but based on how long time it took. I'm always using /goal with explicit goals that the agent needs to achieve. Time-bounding them wouldn't make sense, I want something specific done regardless of how long time it…
I find explicit time bounds are useful for tasks like this, otherwise the LLM will almost certainly return too early.