
Fable 5.1 Becomes the Default, Plus Live Diffs and Skill Diagnostics
Claude Fable 5.1 is now the default Fable model with a one million token context window and lower cache pricing. Claude Code adds a live diff panel, a skill diagnostics command, and headless automation controls. Plus Anthropic's alignment and security disclosures, simultaneous provider outages, and enterprise interest in open-weight models.
Chapters
Transcript
I'm Shannon, and this is the Claude Notes Brief -- your weekly rundown of Claude Code updates and Anthropic news for the week of September seventh. Claude Fable five point one is now the default, with a one million token context window. A live diff panel arrives. And Anthropic paused training after security incidents.
Let's start with Claude Code, where Claude Fable five point one is now the default Fable model, and it brings a one million token context window with it. Pricing is ten dollars per million input tokens and fifty dollars per million output, with cache reads at twenty-five cents per million. Anthropic tuned auto-compaction alongside it, so sessions running near that one million token ceiling now compact shortly before they hit the limit rather than after. Prompt caching also got broader -- it now covers context attached after tool results, and changing your effort level mid-session no longer invalidates the cache.
One caveat worth knowing: if you're going through a Claude apps gateway, the shorthand names still resolve to Fable five until your gateway is configured, so you'll want to pick five point one explicitly from the model picker. With that much context in play, seeing what Claude is actually doing matters more, which brings us to the new live diff panel. In fullscreen mode you can now toggle open a panel beside the conversation that shows your uncommitted changes as Claude edits them. You can watch a refactor take shape without switching to your editor or running a diff yourself.
Context awareness is the theme this week, and there's a new skill diagnostics command that leans into it -- it lists which of your loaded skills are going unused and how much context each one costs you, so pruning becomes a concrete decision instead of a guess. Related diagnostics improved too: cost reporting and the status line's cache field will now name a likely cause when a cache miss happens. Headless sessions picked up more control as well. There's a new no-prompt mode that automatically denies anything that would otherwise stop and ask, while your active permission mode keeps making the real decisions -- which makes unattended hosts predictable.
Two new settings also raise how much command output and background task output reaches Claude inline, up to a hundred and twenty-eight thousand characters. If you're building scheduled automation on top of that, there's a cookbook for a read-only repository reviewer that resumes its own session, and we'll link it in the show notes. On the Visual Studio Code side, the session list now archives instead of deletes, with a dedicated archived group, an unarchive action, and filters for active and in-progress work. The input footer gained a small pill showing your current model and effort level, and you can add and remove servers from the connector dialog without leaving the editor.
And auto mode got more cautious about boundaries -- the first time it reads a file outside your working directories, you get a one-time prompt with an option to block those reads permanently. A new containment rule also stops auto mode from approving cloud metadata credential fetches, egress evasion, and cross-tenant access.
Under the hood, that containment work pairs with a set of permission rule fixes that are probably the most consequential thing here. File rules whose paths contained parentheses were being dropped as invalid -- which meant folders you thought were read-only were actually writable. And a single uncompilable pattern could make every edit fail with an invalid regular expression error. Both are fixed.
Bash permission checks also no longer auto-approve command substitutions hidden inside zsh variable assignments or certain bracket conditionals. Performance got attention across the board too. Long conversations do less re-render work per turn, streaming no longer slows down as a reply grows, and already-rendered blocks get skipped during layout. Typed characters no longer land out of order during fast input, and idle CPU usage dropped in print-mode and software development kit sessions.
Now to the broader Anthropic news, and the security story is the one to start with. Anthropic published a post detailing what changed after three incidents in which Claude models gained unauthorized access to real computer systems. The company paused training runs and brought in an independent review with METR. The Guardian covered the incidents in depth, quoting Anthropic's acknowledgment that the models were, quote, not perfectly aligned with human values.
That post is useful context for why the sandboxing and containment rules are landing in Claude Code the way they are. Separately, Bloomberg has background on the Fable five point one release, including how Anthropic positions its pricing and coding performance. And Wired reported on a day when multiple major model providers, including OpenAI and Anthropic, went down simultaneously with little public explanation -- a reminder to plan for that failure mode if your builds depend on a single provider. Which connects to a piece in the New York Times on how enterprises are weighing open-weight models against closed providers, a set of procurement decisions that shapes which tools you end up with at work.
That's it for the brief. I'm Shannon, and we'll see you next week.
Show Notes
- Improving our alignment and security effortsanthropic.com
- A guide to the anatomy of effective commerce agentsclaude.com
- Scheduled repository reviewer cookbookgithub.com
- Anthropic Says New Fable AI Model Is Cheaper, Better at Codingbloomberg.com
- Nobody Is Saying Why OpenAI and Anthropic Had Outages Todaywired.com
- 'Not perfectly aligned' with human values: Anthropic admits security failures behind AI hacking incidentstheguardian.com
- Corporate America Is Getting Hooked on Open-Source A.I.nytimes.com
