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Righto, grab a coffee, this one's brought
to you by Jellypod AI.

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I'm Lachlan, that's James, and today it's
Claude Code 2.1.302,

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released October 16, 2026.

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One new environment variable in there
closes a loop we opened last time.

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Right.

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Last episode we covered why proxies and
Bedrock or Vertex setups lose the free

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server side safety check in auto mode and
fall back to a classifier running on your

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own client.

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We left that as a trap.

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2.1.302 gives you a lever.

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It's called CLAUDE_CODE_AUTO_MODE_MODEL,
and it chooses the model the client side

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auto mode classifier uses.

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And the release notes are careful about
scope.

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It does not change the model for server
side auto mode.

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So if you're on the Anthropic API and the
server side check is running,

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this variable does nothing for you.

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Why does it matter?

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In auto mode, Claude Code checks tool
calls before running them.

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When that check happens on your client,
it's a model call, and that call takes time

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and spends tokens.

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Until now you couldn't pick which model
made it.

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My read, and this is interpretation, not
something the changelog states,

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is that a small fast model is the sensible
fit for a yes or no safety check.

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That could cut latency on turns with lots
of tool calls.

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Setting it is dead simple.

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In your shell profile, or CI config, you
export CLAUDE_CODE_AUTO_MODE_MODEL equals

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the model ID you want.

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Pick a Haiku class model if you want cheap
and quick.

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On Bedrock or Vertex, use the identifier
your provider uses for that model,

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whether that's an inference profile or a
model ID.

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Don't paste the Anthropic API name and
hope for the best.

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One caveat there.

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The notes don't say what happens with a
bad or retired model ID.

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So test it.

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Set the variable, run something that
triggers a checked tool call,

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and confirm it behaves before you roll it
out to a team.

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Now, the one that could actually bite you.

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Also in this release, claude in print
mode, the p flag, and Agent SDK sessions with

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no permission mode set now start in
default mode.

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That applies on third party providers,
with telemetry off, or on a fresh install.

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Default mode means it asks for permission.

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Which in a headless pipeline means
nobody's there to answer.

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So if your CI job quietly relied on auto,
it can stall or fail after you upgrade.

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The fix is to say what you want.

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Pass the permission mode flag with the
value auto, and auto stays auto.

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Something like claude, the p flag, the
permission mode flag set to auto,

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then your prompt, say, run the build and
the tests.

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So the combo for Bedrock CI is: set the
permission mode explicitly,

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and set CLAUDE_CODE_AUTO_MODE_MODEL so the
fallback classifier isn't running on

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whatever it picked by default.

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There's one more auto mode fix, and it's
for the server side path.

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Before, if a conversation got too long for
the safety check,

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every checked tool call was denied.

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Now Claude Code compacts the conversation
instead.

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So long sessions shouldn't hit that wall.

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A few smaller bits worth knowing.

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Fork subagents, that's subagent_type fork,
are now on by default in print mode,

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the Agent SDK, the desktop app and VS
Code, same as the terminal already had.

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If you don't want them, set
CLAUDE_CODE_FORK_SUBAGENT to 0.

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And claude mcp serve never offers them.

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Also in the desktop app and VS Code, the
main conversation's subagents now always

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run in the background, like the terminal.

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A subagent's own Agent calls run in the
foreground by default.

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There's a new Idle compaction row in
/config, so you can turn idle compaction off or

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back on without digging through files, and
the notices after an idle compaction now

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tell you how to switch it off.

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Prompt and agent hooks are capped at
twelve running at once per event,

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the rest queue.

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If you've got a pile of hooks on one
event, expect that queueing.

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And the Read tool now refuses image
sources over 128 MB instead of loading them

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whole into memory.

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Plus plugin startup is faster with lots of
plugins, especially on Windows.

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So the takeaway: after you upgrade to
2.1.302, check your headless jobs,

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set the permission mode explicitly, and if
you're on a proxy or a cloud provider,

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pin that classifier model.

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Catch you next time.

