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Claude Code tip: once Opus 5.5 is your main model, stop letting your Fable 5.1 quota go to waste put it on call with /advisor run /advisor fable Opus 5.5 keeps doing the work Fable 5.1 sits on the sidelines, reads the whole session, and steps in at three...

319,285 Aufrufe • vor 2 Tagen •via X (Twitter)

34 Kommentare

Profilbild von Suraj Mandal
Suraj Mandalvor 1 Tag

Fable draws from your same weekly quota, I'd rather use all of it using opus since it feels better to use than fable right now usage wise.

Profilbild von TheEpTic
TheEpTicvor 1 Tag

Doesn’t fable eat the weekly too? I hit 100% on weekly the other day and tried fable to see if it worked but it didn’t

Profilbild von Freedom22
Freedom22vor 1 Tag

Fable doesn't need to step in, it is inferior in everything to opus 5.5

Profilbild von Max Reid
Max Reidvor 2 Tagen

I have been letting Fable plan and direct Opus until 5.5 came along. Opus is really quick now. That makes it easy to forget about Fable. The long waiting times were my biggest complaint of using Fable + subagents.

Profilbild von Lay
Layvor 2 Tagen

the repeat-error trigger is the part i needed. my overnight loops keep rediscovering the same broken fix at 3am and waking me up for it

Profilbild von The AI Therapist
The AI Therapistvor 2 Tagen

J'aime cette astuce : Opus 5.5 pilote le tout pendant que Fable surveille les détails pour toi. Malin !

Profilbild von Jeremy Longshore
Jeremy Longshorevor 1 Tag

API key required.

Profilbild von john🎯 aka Mr. Producer
john🎯 aka Mr. Producervor 1 Tag

Opus is better. Cleaner. Hardly touching fable rn.

Profilbild von riVeN
riVeNvor 1 Tag

solid. just note the docs say advisor timing is model-driven, so that claude.md rule is doing the real work.

Profilbild von Roshni
Roshnivor 1 Tag

Maximizing multi-agent delegation like this makes development so much more efficient.

Profilbild von Final Miro
Final Mirovor 1 Tag

ok buddy

Profilbild von Max Bevza
Max Bevzavor 1 Tag

This is basically model specialization without paying the expensive inference cost on every step

Profilbild von Steven | nevetS
Steven | nevetSvor 1 Tag

AI backseating AI

Profilbild von 山川OK50饭
山川OK50饭vor 1 Tag

把好钢都用在刀刃上这招确实高明

Profilbild von David Cumps
David Cumpsvor 1 Tag

you're still burning weekly credits though

Profilbild von Alex
Alexvor 2 Tagen

Using the second model as a reader that only steps in at decision points is a cleaner split than running two agents on the same task. The hard part is keeping those moments few. If the advisor starts commenting on every step, the quota win disappears.

Profilbild von Fede
Fedevor 1 Tag

@grok come dovrei impostare questi subagenti di fable 5.1?

Profilbild von Ratel
Ratelvor 1 Tag

interesting that you have it on advisor the general version is separating available capability from active context. your system can have access to a much larger surface than what needs to participate in every turn.

Profilbild von YunCuntu | Video & Photo Downloader
YunCuntu | Video & Photo Downloadervor 1 Tag

Having a second model only chime in at decision points feels like a solid way to keep costs sane without losing the sanity check.

Profilbild von m-check1B
m-check1Bvor 1 Tag

bravo but not bravo

Profilbild von 小北繁70|BG
小北繁70|BGvor 1 Tag

这波算力分配省心又高效

Profilbild von Moamen
Moamenvor 2 Tagen

Same idea I landed on without the advisor command. Cheap model stays in the session. Expensive model only gets the decision points

Profilbild von 安叫兽|Bird🕊️ 🔶 BNB
安叫兽|Bird🕊️ 🔶 BNBvor 2 Tagen

这个搭配还挺实用,就是怕旁观的比干活的还费配额。

Profilbild von Vibes McDeploy
Vibes McDeployvor 1 Tag

the advisor kept asking "is this right?" so i muted it

Profilbild von 晚晚
晚晚vor 1 Tag

这套分工挺省脑子,像给主力配了个场外教练

Profilbild von Karol
Karolvor 1 Tag

That looks interesting defenitly would love to test it out, but I'm sure my claude would mess it up either way

Profilbild von Hrundel75 🐷
Hrundel75 🐷vor 1 Tag

this post is pure gold

Profilbild von def not sofia
def not sofiavor 1 Tag

This is so true

Profilbild von Arbaz
Arbazvor 1 Tag

advisor is just polite for don't burn opus

Profilbild von Charlie Deist
Charlie Deistvor 1 Tag

this seems smart but also like it's overindexing on something. I'm not sure what.

Profilbild von AIガチ勢オジ|40代×Claude Code
AIガチ勢オジ|40代×Claude Codevor 1 Tag

メインモデルとアドバイザーを分けて、クォータを無駄にしない運用は本当に参考になります。3つの介入タイミングも試してみます。ありがとうございます!

Profilbild von helicerat
heliceratvor 1 Tag

woah bro, setting this up right now

Profilbild von JoshuaLP
JoshuaLPvor 1 Tag

Don’t do this, it is not needed

Profilbild von notgwapo
notgwapovor 1 Tag

sounds like a decent setup. gotta see if fable 5.1 throws any curveballs while opus keeps grinding. 🤔

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Claude Code tip: once Opus 5.5 is your main model, stop leaving Fable 5.1 sitting idle put it on call with /advisor run /advisor fable Opus 5.5 keeps writing the code Fable 5.1 reads the full session, every tool call included, and only speaks up at three points: → before a plan: is this the right approach? → when the same error comes back: am I digging in the wrong place? → before "done": what did I miss? Fable 5.1 reviews. Opus 5.5 ships Jev engineering is the same move one layer down: the forks that need no thinker (which file, which tool, retry or stop) go to Jev in under half a second, and the big model only sees the ones that split - the full tree > Opus 5.5 on high runs the main session > explorer reads the code > worker edits and runs tests > researcher pulls the docs > all three on medium > Fable 5.1 on call as the advisor paste the tree and this prompt into Claude Code ↓ "Rebuild my Claude Code setup around this tree: 1. Check ~/.claude/agents and .claude/agents for subagents that already fit explorer, worker and researcher. > Draft new ones only for missing roles > Give each model: opus, effort: medium > Skip any that pin a different model and list them 2. Set the main session to high via effortLevel in ~/.claude/settings.json, and set advisorModel to fable 3. Find anything that keeps the advisor off (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, any variable that stops feature-flag fetching) plus CLAUDE_CODE_EFFORT_LEVEL, which overrides subagent effort. Report them, change nothing 4. Add one rule to ~/.claude/CLAUDE.md: consult the advisor before a large plan, when an error repeats, and before calling a long task done Show me every change as a diff first. No edits until I say go." ↳

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Carnage

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fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

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18,509 Aufrufe • vor 27 Tagen

i finally mastered how to maximise my opus 5.5 usage limits... the trick: let jev choose which subagent gets each task and how much effort it should use. [here’s how i’d wire it:] claude breaks the project into tasks. jev selects from predefined worker profiles. claude applies the selected settings and dispatches the work. → main session, medium: clarify the requirements, define what “done” looks like, and prepare the tasks → builder, low: small, clearly defined tasks with existing examples or patterns → builder, medium: tasks that connect multiple parts or need decisions within the approved plan → verifier, high: check requirements, probe edge cases, and report problems for the builder to fix jev gets the task’s scope, what’s uncertain, and the consequences of failure. it chooses from the profiles allowed for that task. your approval checkpoints stay in place. paste this into your next planning session: “use opus 5.5 with jev selecting the worker and effort profile for each task. first, check that a working jev integration is available and that this environment supports separate effort settings for subagents. check for configuration or environment overrides that could prevent those settings from taking effect. if anything is missing, explain what needs wiring before proceeding. break my request into tasks with clear ownership, dependencies, relevant context, and acceptance checks. keep small related tasks together when a separate subagent would add unnecessary overhead. keep the main session at medium effort. offer jev these worker profiles: builder at low effort for small, clearly defined tasks using existing patterns; builder at medium effort for tasks that connect multiple parts or require decisions within the approved plan; verifier at high effort for checking requirements and edge cases. give jev each task’s scope, uncertainties, dependencies, and consequences of failure. only offer profiles appropriate to the current stage. validate its selection before dispatching. use the actual jev integration; don’t simulate its decisions. if it abstains or returns an invalid choice, stop that handoff and ask me. show me the task plan and proposed assignments before starting. after approval, launch the selected workers with their assigned effort settings, relevant context, file ownership, and completion checks. let me review the result before verification. the verifier may add tests but must leave implementation code unchanged. have it report what passed, what failed, and what remains uncertain. send implementation fixes back to the builder, then recheck the affected parts. if a task repeatedly fails, examine the requirements and approach before increasing effort. report available total usage, including jev calls, worker calls, retries, and verification. don’t invent missing data. compare similar completed tasks before claiming savings.” steal this 👇

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