If you are letting Claude run for seven minutes at a time, you aren't thinking hard enough about what you're building.

If you start trying to juggle multiple agents, you are doubling down on the wrong strategy.

https://hbr.org/2010/12/you-cant-multi-task-so-stop-tr

jeapostrophe 2 hours ago | parent | next [-]

I've gone through a bunch of different processes learning how to use Claude.

Giving it large tasks that take 40 minutes basically always fails for me. Giving it small tasks that take 30s to a minute feels like it is my typist and not a worker. I find that I am happiest and most effective at the 5 to 7 minute cycle timeframe.

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samename 3 hours ago | parent | prev [-]

Why should Claude finish complex tasks in less than seven minutes?

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bwestergard 3 hours ago | parent | next [-]

The need for "complex tasks" should be exceptional enough that you're not building your workflow around them. A good example of such an exception would be kickstarting a port of a project for which you have a great test suite from one language to another. This is rare in most professional settings.

	▲	btown 42 minutes ago \| parent [-]
		I wholeheartedly disagree with this. For any iteration, Claude should be reading your codebase, reading hundreds of thousands of tokens of (anonymized) production data, asking itself questions about backwards compatibility that goes beyond existing test suites, running scripts and CI to test that backwards compatibility, running a full-stack dev server and Chrome instance to QA that change, across multiple real-world examples. And if you're building a feature that will call AI at runtime, you'll be iterating on multiple versions of a prompt that will be used at runtime, each of which adds token generation to each round of this. In practice on anything other than a greenfield project, if you're asking for meaningful features in complex systems, you'll be at that 10 minute mark or more. But you've also meaningfully reduced time-to-review, because it's doing all that QA, and can provide executive summaries of what it finds. So multitasking actually works.

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skydhash 3 hours ago | parent | prev [-]

Computers are fast. If a physic engine can compute a game world in 1/60 of a second. The majority of the tasks should be done in less than 7 minutes.

Whenever I see transcript of a long running task, I see a lot of drifting of the agent due to not having any context (or the codebase is not organized) and it trying various way to gather information. Then it settle on the wrong info and produce bad results.

Greppability of the codebase helps. So do following patterns and good naming. A quick overview of the codebase and convention description also shortens the reflection steps. Adding helper tools (scripts) help too.