シャドーイング練習: Rethinking Claude Code Best Practices — Lydia Hallie, Anthropic - 動画で英語スピーキングを学ぶ

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1
I had some technical difficulties during my talk this morning.
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So I ran back home and I'm just going to record it from my computer instead.
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So hi everyone.
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I'm Lydia.
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I work on the clock code team at Anthropic and the models have gotten really good lately.
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So we have Opus 5 .5, which is my favorite daily driver.
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And earlier this week, we also launched Fable 5 .2.
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And these models are extremely good at long running tasks and understanding your code base.
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And especially Fable was also really good at verifying its own output.
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But as these models get better, the way that we work with them in Cloud Code also changes.
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So earlier this year, I don't know if you remember, but sessions kind of used to look like this.
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So we'd use a model like Opus 4 .5, which honestly for its time was really good.
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I really enjoyed working with Opus 4 .5.
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But compared to today, it would just stop a lot earlier.
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So it would just run for shorter amounts of time.
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And we'd also keep correcting it.
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We'd keep reminding it to do things, add things like importance, exclamation mark, all these things to our CloudMD file.
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And also features like auto mode didn't exist yet.
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So we were either approving everything manually or taking the riskier approach with dangerously skip remission.
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So we were still very much in the loop as humans.
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But as these models got better at taking on bigger tasks, our sessions also changed.
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So nowadays, at least at Anthropic, our sessions look more like this.
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So we're running dozens of sessions at the same time, running for hours, verifying their own results along the way,
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and we even have sessions orchestrate other sessions.
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So whereas we used to be in the loop for almost every step
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and running one or just a couple sessions at a time, we've now essentially become managers for dozens of sessions.
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We also get a lot more done, though.
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Now, you may have seen our blog post in October about
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how Enthropic went from about 2 ,500 changes a day in May to more than 30 ,000 a day in September.
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But this also means that we as developers just have to rethink on what we're focused on instead.
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So if you think about our best practices from earlier this year, it was mainly about steering sessions,
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approving commands, saying no to certain things or restricting what
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Cloud could do, checking the output and also starting the sessions.
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So everywhere that we now step out of that loop, something else has to take over.
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And this is either the model, the harness, or the environment that it's running in.
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So if we are not in a loop to approve every command and we're running so many sessions at the same time,
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how can we make sure that the code it's writing is still high quality?
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And most importantly, if these sessions are running for hours without our supervision, how can we make sure that they're running safely?
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So let's go through that by taking this old session
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and seeing what we have to change to get to that end result that I showed earlier.
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Well, first of all, let's use the actual defaults we start sessions in nowadays.
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So that's not really something you should think about.
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So let's update the model here from Opus 4 .5 to Opus 5 .5 and change the manual permission to auto mode.
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And Opus 5 .5 is a lot better at understanding your intent and understanding your code base.
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So we really don't have to steer it as much anymore mid -session.
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And you also no longer have to approve every command
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because we started making auto mode the default permission mode back in August.
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Now being better at understanding your intent and your code base also means
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that we have to rethink the instructions we have in our code base.
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So if you followed our best practices from earlier this year you may still have things like important
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or never do this exclamation mark all these things in your cloud MD file
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but with today's models you really don't need that
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and it can actually make the model go off track
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so you end up with more tool calls and overall a worse results
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so nowadays your cloud md file should only include the things
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that cloud cannot see from your code
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so for example maybe you have a service that's still using some legacy source somewhere
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but it's not directly referenced in the code that's still good to keep in there
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but everything else like what stack you're on
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or where to look you really don't need that anymore
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and we actually have a command for this called dr prompt audit
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which makes it really easy to optimize your environment for a specific model.
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So if you're on Opus 5 .5 here and you run this command,
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it will automatically check your CloudMD and your skills to see what the new model no longer needs.
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Now auto mode is a permission mode
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that runs a separate classifier on pretty much everything that isn't just reading or editing files in your project.
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So it automatically allows commands that it knows are safe, like running tests or installing dependencies, but still blocks commands where it's unsure whether they're safe
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and normally that's pretty good normally that's kind of you know what we want
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but for example here
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if we ask it to ship something to staging
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we would have just you know approved the push to our deploy repo
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but by default auto mode only trusts this folder and this repo
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so it would block that command
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so we're back in the loop now the defaults should be good in most cases
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but if you still notice that you have to approve a lot of commands, even in auto mode.
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The first thing to look at is settings here because you can configure auto mode in your own settings, just in plain English.
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And this is what gets sent to the classifier, which then decides whether to reject or allow certain commands.
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So here we can just write which repos, buckets, domains we trust and what it should always allow or never do.
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Okay, so honestly, this was pretty easy by just using today's defaults, we've already gotten rid of most of our in the loop stuff
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because the model took over the steering
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and auto mode took over all the approving so getting out of the loop is easy.
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But the harder question now is how do we make sure it's okay that we're not there anymore?
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So first is keeping it safe, and then also verification.
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So let's start with keeping it safe, because everything so far, so upgrading the model and using auto mode, it's just working with a model.
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And in most cases, it does what you tell it to do, but that's not a guarantee.
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So in a study we published back in August, we tested auto mode versus real people in the loop,
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and only about 14 % of people caught a clearly dangerous command.
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AutoMode blocked 89 % of them, so it is a lot better at it than we were.
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But about 1 in 10 of those commands still went through.
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So if you do want the guarantee, you can only enforce that in the harness.
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And this is where some of our older best practices still matters, and that's permission.
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So, for example, if you have a deny rule for a specific tool call in your project,
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clot code looks at this rule before the automo classifier even looks at it in fact
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if a tool call matches a deny rule the classifier never even sees it
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so having deny rules is still the best way to make sure clot actually never does something
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but then how do you know what needs to be a
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rule in your project versus what the model can just know
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because they've gotten so good at it i think it kind of just comes down to
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if clot gets this wrong once can i take it back so if it writes the wrong code, you can still revert that.
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So you can still leave that to the model.
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But if it throws away our uncommitted changes
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or it reads a key that's now in your transcript and you don't want that, that should still be a rule.
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So for example, let's say that we just never want Claude reading our .end file.
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Now by default, Automode is fine with this.
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So it would have just approved it.
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So if you want to make sure that Claude can never read this file, you should just add a deny rule
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and then commands like cat cannot open this file either
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but it's not always that straightforward because sometimes certain commands can have side effects
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so for example let's say
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that npm test here a very normal command it's just a test
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so automote runs it that's fine but
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when the script is running it runs code
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that you didn't write like your dependencies
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or maybe clod runs a script real quick
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that it wrote just to quickly check something so
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if one of those scripts is compromised it could just open
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that same end file or your ssh keys
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and send those to a server you've never heard of right
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and even if we were still there as humans approving everything honestly we would have just clicked allow
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because there's nothing to say no to it's just part of the script
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that in this example case npm test runs and permissions only decide
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if a tool call runs but they cannot limit what it can reach once it's running
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so we want to make sure that these kinds of scripts can still run
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because this is just part of you know how cloud can check its own work running tests
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so we cannot just block npm tests
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but we want to limit its side effects
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so really we just want to limit the environment
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that it's running in so if you're running it locally
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or on your own machine you can run commands like
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that in a sandbox so then you have control over
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which files in a command it can read
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which folders it can write to which hosts it can reach
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and the operating system enforces that also this also applies to everything that command then starts so any child processes
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so on its own that deny rule got checked by claude before the command runs
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but all it sees there is npm test so it doesn't see
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which files that scripts ends up opening but with the sandbox on
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that same rule gets passed on to the operating system
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so now when when
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that dependency tries to open our end file the operating system just doesn't let it
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and by default it can still read most of your machine
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so you'd want to add another rule for your ssh keys
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if you care about that um and it also cannot reach a host
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that wasn't approved but the sandbox only covers the shell commands
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that cloud runs and whatever those start but claude's own files your mcp servers
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and all of your hooks still run outside of it
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so the rest of your session still runs on your own machine
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and everything that's on there
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so ideally you want this whole thing to run somewhere where none of
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that is even there in the first place and
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that is a cloud session
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because there it gets its own machine with a fresh copy of a repo
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and this runs even when we close our laptop
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which is definitely something you want for these longer running sessions
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that run for hours so in this case this automatically gets rid of the end file issue
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because it's not in git and neither are my ssh keys
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or our github token and if it still needs an api key uh you can add
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that as a network secret where it will it will tell you like hey
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i'm missing an api key mid -session um
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so it can use it without actually ever sending it to the model
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and by default also in a cloud session network access is limited to things like package registries and github
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so you have to explicitly add those domains to your environment for claw to to reach other hosts okay
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so with a cloud session we can run these long running sessions even with our laptop closed
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and it keeps us safe
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because it runs in its own environment now it's still good to remember
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that this machine is disposable but the things that leave it aren't
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so a commit that pushed or a message it sent through a connector
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so we still run it in auto mode with our deny rules just commit it into the repo
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so they come along so it could still catch things like a force push
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or a secret and a commit all that kind of stuff
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and beyond just safety we also need to make sure
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that Claude is actually working on the right thing
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so next is verification
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and the nice thing about being in a loop uh like we kind of knew the work was good
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because we'd already kind of seen every change we'd proved everything
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but now if claude works for hours in the background we don't have
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that anymore and we're not really going to read every file at the end either
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so you know say
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that we ask it to move our auth to a new
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api well claude is very good at understanding what we want
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but there are still a lot of small decisions
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that it has to make along the way
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so with the exact same problems you know one run might move it over
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but leave the old api in there or one might move it
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but only for new logins and another one might move it
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but log everyone out and these all look pretty reasonable
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but it really helps to set up these verification points along the way
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so claude keeps verifying its own results and those can be anything
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that comes back as a pass or fail
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so tests a build a screenshot whatever you have
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so now we just want to make sure that we review these verification points.
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They're a lot shorter to review than if we just had to, you know, review the whole change at the end.
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So that's pretty reasonable.
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So if one of these runs would still log everyone out, it doesn't get past that first check,
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and then it just has to find another way.
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And there's a couple ways to set this up.
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The easiest one is, of course, just in your prompt.
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So, you know, you say what done looks like
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and ask it to split that into tasks so they have their own tests.
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And I also like to ask it to show the actual output
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because you weren't there to see it but again prompting is not a guarantee
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that a model will do it so for the ones
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that have to run guaranteed run i would use hooks
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which are just you know scripts that cloud code runs at a specific point
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and those give you a lot of control because you decide
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when they run and what they run and what they check
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so for example every time it edits a file
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we can run our linter every time
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it wants to mark a task as complete we can run the tests for what it changed um
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so you know if it touch our off code or something.
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It has to pass the off tests.
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And when it wants to finish the whole session, we can just run the entire test suite.
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And if one of those fails, it goes, oh, that's still broken.
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It goes back until it passes.
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So it fixes it.
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Now, just one thing, when a test fails, by default, most tools that exit with a one exit code.
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But with a one, that task by Cloud Code just gets marked as completed anyway.
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So make sure that your scripts exit with a two exit code
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because that's what actually sends cloud back to fix it
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so okay now we have one session that i'm pretty comfortable with leaving alone
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so now we can start with a few more of those
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because they've all got their own machine
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so they're you know not all working in the same folder
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and we don't really have to think about work trees too much ourselves anymore
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but then we still start every session ourselves
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and we review every one of them
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and honestly this is already a pretty good place to be
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we are still fully in control over what gets started and
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when we call a task done
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but even there um you know we're still the ones kicking off every session
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and we're still in the loop for all of them
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so i think the most important thing to have in place here now is your ci
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because all of these sessions eventually open a pr
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and your ci runs the same checks on every one of them no matter how
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that session was set up or you know what claude decided to do along the way.
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And if you turn on autofix, we have like CI autofix,
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Cloud can also see when one of those checks fails and then go back to fix it.
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So you're not the one spending your review on things that, you know, a check could have already caught.
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And for some of them, you can even turn on merge when ready.
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So then GitHub merges the PR once all of the checks have passed.
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So you're not in the loop to review.
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But again, that's not the default.
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And that really depends on how risky the changes
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so for example on our team every pr gets reviewed by cloud first
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so not by the session that wrote it
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so it comes with a fresh context
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and also a separate group of agents to just double check every bug it finds
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and then how much we review ourselves just depends on the risk
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so smaller changes like docs or copy they don't need a person so once the automated checks are green
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we're pretty good to go.
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Maybe ordinary product changes just need one reviewer, and then risky changes might need two.
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Now, ultimately, kind of where we see things going, and we're already kind of doing more of that adnthropic,
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is that you're not really starting all of those sessions yourself either.
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Because if you're anything like me, I'm terrible at context switching, so having to manage so many sessions at the same time doesn't always go well.
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So instead, you just have one main session that's your orchestrator
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and you can already see this in things like cloud code projects
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which is still in beta but you just tell it what it needs to be done
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and the orchestrator splits it up and then starts other sessions for each task
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and it keeps track of what comes back so it automatically starts
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and verifies these threads which are just new sessions
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so instead of talking to eight sessions you're just talking to one
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and the main session doesn't write the code itself
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so there you want a model that's really good at deciding what to do
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and judging what comes back a model like fable and
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if something comes back that isn't actually done it just you know sends it back
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so until it's actually done and passes everything
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and the threads need a model that's good at actually doing the work like opus 55
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and you can set those separately so you know one model for the main session
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and then another one for the threads and another benefit is
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that with this setup with cloud code projects specifically we don't manage context anymore that's all done automatically for us
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so we no longer have to think about you know
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when to compact or clear all of that stuff okay so
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if you look back at those old best practices they're all still there but they've just moved
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so the model sears it now um auto mode approves your deny rules
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and the environment restrict what's possible your test your hooks
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and your ci check set and then ultimately cloud can just start them as well
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so almost everything we used to do ourselves is now either the model the harness
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or the environments and we're really just here to start
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that first one and to just review what comes out so
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if you want to try this in your own setup
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i would say just take one thing
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that's way bigger than you normally give claude make sure your ci actually catches the things you care about
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and then spend a bit of time just configuring your environment like it's network access it's secret
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and it's you know setup script and then start in the cloud
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and see where your sessions get stuck and where you're still in the loop
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because that's the next thing to hand over to claude
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i also highly recommend checking out our best practices in the docs as well thank you so much

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このレッスンの語彙とスピーキングのポイント

このスピーキングレッスンは、動画「Rethinking Claude Code Best Practices — Lydia Hallie, Anthropic」を教材にしています。 繰り返し出てくる語は次のとおりです:session, model, command, code, cloud。 この動画には、シャドーイング用の文が286文、単語が3581語あります。 音声の長さは17:31です。 話す速さは速く、1分あたり約204語です。音のつながりや弱く発音される音が多くなります。 単語の86%は英語の頻出3,000語に含まれます。残りは練習の前に確認しておきましょう。

この動画の重要語彙

動画に出てくる覚えておきたい単語15語を、発音と意味つきで紹介します。

単語発音意味
cloud 名詞/ˈklaʊ̯d/雲, 雲霞
loop 名詞/luːp/ループ
approve 動詞/əˈpɹuːv/承認する, 賛成する
default 名詞/dɪˈfɔlt/デフォルト
script 名詞/skɹɪpt/文書, 文章
deny 動詞/dəˈnaɪ/否む, 打ち消す
guarantee 名詞/ˌɡæɹ.ənˈtiː/保証
exit 名詞/ˈɛɡzət/出口
verification 名詞/ˌvɛ.ɹə.fɪˈkeɪ.ʃən/確証, 検証
thread 名詞/ˈθɹɛd/糸
output 名詞/ˈaʊtpʊt/出力
hook 名詞/hʊk/鉤, フック
commit 動詞/kəˈmɪt/預ける, 任せる
nowadays 副詞/ˈnaʊ.ə.deɪz/現在, 現代では
risky 形容詞/ˈɹɪski/危険な

動画に出てくる句動詞

単語発音意味
come back 動詞戻る, 帰る
take over 動詞引き受ける
check out 動詞試験する, 検査する
come out 動詞/ˌkʌm ˈaʊt/出る
go back 動詞戻る, 帰る
throw away 動詞棄てる, 捨てる

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型動画での表現
「used to」 used to + 動詞 — 今はもう違う過去の習慣や状態used to look · used to be · used to do
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係しているhave gotten · we've now essentially become · we've already gotten
受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てるis compromised · wasn't approved · was set

注意したい発音

話し手はwe're, don't, you'reなど、短縮形や弱形を63回使っています。聞こえたとおりの短い形で発音しましょう。

  • 「th」の音: thread /ˈθɹɛd/, rethink /ɹiːˈθɪŋk/, auth /ɔːθ/
  • 「sh」と「zh」の音: verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/, essentially /ɪˈsɛnʃəli/, shell /ʃɛl/, instruction /ɪnˈstɹʌkʃən/, supervision /ˌs(j)uːpəˈvɪʒən/
  • 長い単語(アクセントの位置に注意): verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, essentially /ɪˈsɛnʃəli/, ordinary /ˈɔɹdɪnɛɹi/, difficulty /ˈdɪfɪkəlti/

日本語話者が苦手な音:

  • /r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: importantly /ɪmˈpɔɹ.tənt.li/, separately /ˈsɛp.ɹət.li/
  • /v/ — /b/ にならないように、上の歯を下唇に当てる: approve /əˈpɹuːv/, verify /ˈvɛɹɪfaɪ/, verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/, server /ˈsɝvɚ/, versus /ˈvɝsəs/
  • /f/ — 「フ」ではなく、上の歯と下唇で出す: default /dɪˈfɔlt/, verify /ˈvɛɹɪfaɪ/, verification /ˌvɛ.ɹə.fɪˈkeɪ.ʃən/, folder /ˈfoʊldɚ/, enforce /ɪnˈfoɹs/

この動画での練習方法

  1. まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
  2. まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
  3. 自分の声を録音して元の音声と比べます。cloud, loop, approveなどの単語に特に注意しましょう。

シャドーイングとは?英語上達に効果的な理由

シャドーイング(Shadowing)は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的:ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影(shadow)」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

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