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Official Anthropic tip for Claude Code: stop burning Opus 5.5 on work Sonnet 5.5 can do, while Fable 5.1 sits idle hand the grunt work to Sonnet 5.5 subagents and put Fable 5.1 on call run /advisor fable Opus 5.5 plans and merges Sonnet 5.5 subagents read, edit and...

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delost

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42,409 次观看 • 2 天前 •via X (Twitter)

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9 条评论

Deep 的头像
Deep2 天前

i run the small edits on a cheap model and only wake the expensive one when the plan breaks

EraGroup Sweep" & 🦈 的头像
EraGroup Sweep" & 🦈2 天前

Nâng niu từng khoảnh khắc bác ơi, tuyệt vời

meff 的头像
meff2 天前

does /advisor actually save tokens or just move them around?

Kevin Kreger 的头像
Kevin Kreger2 天前

advisor is called automatically after invoking /advisor once. I've never added any prompt; it just works.

Berliner Sandbox 的头像
Berliner Sandbox1 天前

the planner/subagent split finally in the official docs. i've been running a similar handoff with a cheap model for grunt file edits and a bigger one only for merge decisions. cuts tokens way down. good to see it as a slash command now.

Mário Alexandre 的头像
Mário Alexandre2 天前

crews does this split for you: list the roles, it puts each subagent on Opus, Sonnet, Haiku or Fable at the effort its work needs.

Archive 的头像
Archive2 天前

i heard this tip a couple days ago and honestly everyone should try it

Logics 的头像
Logics2 天前

Ty for tips boss

kaminoontee 的头像
kaminoontee2 天前

this feels way more efficient than throwing Opus at everything

相关视频

Claude Code tip: once Opus 5.5 runs your main session, stop leaving Fable 5.1 on the bench put it on call with /advisor run /advisor fable Opus 5.5 keeps writing the code Fable 5.1 reads the whole session, every tool call included, and only speaks up at three moments: → 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." ↳
0:40

Claude Code tip: once Opus 5.5 runs your main session, stop leaving Fable 5.1 on the bench put it on call with /advisor run /advisor fable Opus 5.5 keeps writing the code Fable 5.1 reads the whole session, every tool call included, and only speaks up at three moments: → 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." ↳

Hanako

51,329 次观看 • 4 天前

Claude Code tip, and it's absolute free f*cking gold: run Opus 5.5, Sonnet 5.5 and Fable 5.1 as one team and stop burning Opus tokens on routine work the setup in one line: plan on high, delegate on medium, keep Fable on call • who does what > Opus 5.5 on high - plans and ships the code > Sonnet 5.5 on medium - explorer reads code, worker edits and runs tests, researcher pulls docs > Fable 5.1 via /advisor fable - reads the whole session and speaks up only when it matters • when Fable 5.1 steps in -> before a plan: is this the right approach? -> when an error repeats: am I digging in the wrong place? -> before "done": what did I miss? Jev engineering takes it one layer lower: which file, which tool, retry or stop all go to Jev in under half a second, so the big models only see the real forks paste this into Claude Code ↓ "Rebuild my Claude Code setup: 1. Find subagents in ~/.claude/agents and .claude/agents that fit explorer, worker and researcher. Draft only the missing ones. Set each to model: sonnet, effort: medium. List any that pin a different model and leave them 2. In ~/.claude/settings.json set effortLevel to high and advisorModel to fable. 3. Report anything that disables the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, flag-fetching blockers) and CLAUDE_CODE_EFFORT_LEVEL. Change nothing. 4. Add to ~/.claude/CLAUDE.md: consult the advisor before a large plan, when an error repeats, and before calling a long task done. Show every change as a diff. No edits until I say go." ↳
0:24

Claude Code tip, and it's absolute free f*cking gold: run Opus 5.5, Sonnet 5.5 and Fable 5.1 as one team and stop burning Opus tokens on routine work the setup in one line: plan on high, delegate on medium, keep Fable on call • who does what > Opus 5.5 on high - plans and ships the code > Sonnet 5.5 on medium - explorer reads code, worker edits and runs tests, researcher pulls docs > Fable 5.1 via /advisor fable - reads the whole session and speaks up only when it matters • when Fable 5.1 steps in -> before a plan: is this the right approach? -> when an error repeats: am I digging in the wrong place? -> before "done": what did I miss? Jev engineering takes it one layer lower: which file, which tool, retry or stop all go to Jev in under half a second, so the big models only see the real forks paste this into Claude Code ↓ "Rebuild my Claude Code setup: 1. Find subagents in ~/.claude/agents and .claude/agents that fit explorer, worker and researcher. Draft only the missing ones. Set each to model: sonnet, effort: medium. List any that pin a different model and leave them 2. In ~/.claude/settings.json set effortLevel to high and advisorModel to fable. 3. Report anything that disables the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, flag-fetching blockers) and CLAUDE_CODE_EFFORT_LEVEL. Change nothing. 4. Add to ~/.claude/CLAUDE.md: consult the advisor before a large plan, when an error repeats, and before calling a long task done. Show every change as a diff. No edits until I say go." ↳

Mr. Buzzoni

141,462 次观看 • 4 天前

this is straight f*cking gold for anyone on Claude Code you already pay for Fable 5.1, and while Opus 5.5 does all the work it just sits there one command puts it on your session as a senior reviewer: /advisor fable Opus 5.5 keeps writing the code Fable 5.1 reads the whole session, every tool call included, and speaks up at three moments only: > 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 does the same thing one layer down: 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 actually 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" ↳
0:24

this is straight f*cking gold for anyone on Claude Code you already pay for Fable 5.1, and while Opus 5.5 does all the work it just sits there one command puts it on your session as a senior reviewer: /advisor fable Opus 5.5 keeps writing the code Fable 5.1 reads the whole session, every tool call included, and speaks up at three moments only: > 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 does the same thing one layer down: 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 actually 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" ↳

Annatar.md

73,357 次观看 • 5 天前

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 moments: → before a plan: is this right? → when the same error comes back: am I going the wrong way? → before "done": did I miss anything? Fable 5.1 advises. Opus 5.5 writes the code the same idea sits under Jev engineering: the expensive model stops weighing in on every step and only gets called at the moments that change the outcome • the full setup > Opus 5.5 on high runs the main session > subagent one reads code > subagent two edits and runs tests > subagent three looks up docs > all three on medium > Fable 5.1 on call hand the tree and this prompt to Claude Code 👇 "Set up my Claude Code to match this tree: 1. Reuse fitting subagents from ~/.claude/agents and .claude/agents. > Propose new ones only for missing roles > Set each to model: opus, effort: medium > Leave any that set a different model alone and list them 2. Set main session effort to high via effortLevel in ~/.claude/settings.json 3. Check for env vars that disable the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, anything that stops flag fetching) and CLAUDE_CODE_EFFORT_LEVEL, which overrides subagent effort. Report them, don't change them 4. Add a rule to ~/.claude/CLAUDE.md: ask the advisor before a big plan, when an error repeats, and before calling a long task done Show me the changes first. Don't edit files yet." ↳
0:24

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 moments: → before a plan: is this right? → when the same error comes back: am I going the wrong way? → before "done": did I miss anything? Fable 5.1 advises. Opus 5.5 writes the code the same idea sits under Jev engineering: the expensive model stops weighing in on every step and only gets called at the moments that change the outcome • the full setup > Opus 5.5 on high runs the main session > subagent one reads code > subagent two edits and runs tests > subagent three looks up docs > all three on medium > Fable 5.1 on call hand the tree and this prompt to Claude Code 👇 "Set up my Claude Code to match this tree: 1. Reuse fitting subagents from ~/.claude/agents and .claude/agents. > Propose new ones only for missing roles > Set each to model: opus, effort: medium > Leave any that set a different model alone and list them 2. Set main session effort to high via effortLevel in ~/.claude/settings.json 3. Check for env vars that disable the advisor (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, anything that stops flag fetching) and CLAUDE_CODE_EFFORT_LEVEL, which overrides subagent effort. Report them, don't change them 4. Add a rule to ~/.claude/CLAUDE.md: ask the advisor before a big plan, when an error repeats, and before calling a long task done Show me the changes first. Don't edit files yet." ↳

Mr. Buzzoni

323,076 次观看 • 7 天前

This is f*cking insane. This tip saved me thousands of dollars. run Opus 5.5, Sonnet 5.5, and Fable 5.1 together, and stop burning Opus on work it was never needed for. the whole idea in one line: the strong model plans, the mid-tier model executes, Fable stays quiet until it's actually needed. roles, broken down: Opus 5.5, high effort, owns the plan and ships the final code Sonnet 5.5, medium effort, splits into explorer (reads the codebase), worker (edits files, runs tests), researcher (pulls docs) Fable 5.1, called through /advisor fable, reads everything happening in the session but stays silent unless something's actually wrong three moments where Fable speaks: → a plan goes out: is this actually the right call? → the same failure shows up again: is the search going nowhere? → the task gets marked finished: did something get skipped? Jev engineering does the same thing one level down. the forks that don't need real thought, which file, which tool, keep going or stop, go straight to Jev and come back in under half a second. the big models only ever see the forks that genuinely need a decision. anyone still running one model for everything is paying Opus prices to decide whether a file exists. drop this into Claude Code: "Rebuild my Claude Code setup around this structure: Look through ~/.claude/agents and .claude/agents for subagents already covering explorer, worker, and researcher. Only create new ones for roles that are missing. Set model: sonnet, effort: medium on each. If an existing subagent is locked to a different model, leave it as is and just list it. In ~/.claude/settings.json, set effortLevel to high and advisorModel to fable. Check for anything disabling the advisor, CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, or anything blocking feature-flag fetches, plus CLAUDE_CODE_EFFORT_LEVEL, which can override subagent effort settings. Report what you find. Don't change any of it yet. Add one line to ~/.claude/CLAUDE.md: check in with the advisor before a big plan, when the same error shows up twice, and before marking a long task done. Show every change as a diff first. Wait for my go-ahead before touching anything."
0:20

This is f*cking insane. This tip saved me thousands of dollars. run Opus 5.5, Sonnet 5.5, and Fable 5.1 together, and stop burning Opus on work it was never needed for. the whole idea in one line: the strong model plans, the mid-tier model executes, Fable stays quiet until it's actually needed. roles, broken down: Opus 5.5, high effort, owns the plan and ships the final code Sonnet 5.5, medium effort, splits into explorer (reads the codebase), worker (edits files, runs tests), researcher (pulls docs) Fable 5.1, called through /advisor fable, reads everything happening in the session but stays silent unless something's actually wrong three moments where Fable speaks: → a plan goes out: is this actually the right call? → the same failure shows up again: is the search going nowhere? → the task gets marked finished: did something get skipped? Jev engineering does the same thing one level down. the forks that don't need real thought, which file, which tool, keep going or stop, go straight to Jev and come back in under half a second. the big models only ever see the forks that genuinely need a decision. anyone still running one model for everything is paying Opus prices to decide whether a file exists. drop this into Claude Code: "Rebuild my Claude Code setup around this structure: Look through ~/.claude/agents and .claude/agents for subagents already covering explorer, worker, and researcher. Only create new ones for roles that are missing. Set model: sonnet, effort: medium on each. If an existing subagent is locked to a different model, leave it as is and just list it. In ~/.claude/settings.json, set effortLevel to high and advisorModel to fable. Check for anything disabling the advisor, CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, or anything blocking feature-flag fetches, plus CLAUDE_CODE_EFFORT_LEVEL, which can override subagent effort settings. Report what you find. Don't change any of it yet. Add one line to ~/.claude/CLAUDE.md: check in with the advisor before a big plan, when the same error shows up twice, and before marking a long task done. Show every change as a diff first. Wait for my go-ahead before touching anything."

rvaniaaa

242,307 次观看 • 2 天前

We've just added Claude Sonnet 5.5 to Caffeine. It's Anthropic's model for work you can describe clearly: fix this bug, add a booking form, polish this page. Anthropic says it's 30% faster than Sonnet 5, and cheaper than Opus 5.5. Keep Opus 5.5 for planning something new, and hand the follow-up work to Sonnet 5.5. On Caffeine, you can switch between models in the same conversation.
0:27

We've just added Claude Sonnet 5.5 to Caffeine. It's Anthropic's model for work you can describe clearly: fix this bug, add a booking form, polish this page. Anthropic says it's 30% faster than Sonnet 5, and cheaper than Opus 5.5. Keep Opus 5.5 for planning something new, and hand the follow-up work to Sonnet 5.5. On Caffeine, you can switch between models in the same conversation.

caffeine

21,391 次观看 • 4 天前

this is certified f*cking gold for anyone paying for Claude Sonnet 5.5 costs half of what Opus 5.5 does on real office work across 44 jobs it scores 1844. Opus scores 1846 on coding it went from 10.3% to 70.6% in one version and passed Opus on the way most of what you pay Opus for, Sonnet 5.5 now does at half the price here's how to split the work: • give it to Sonnet 5.5 > bug fixes and well-scoped coding tasks > decks built from your own slide template > spreadsheets and polished documents > UI polish, it has a real eye for design > fast back-and-forth, it runs 30%+ faster • keep it for Opus 5.5 > long, open-ended work with judgment calls for hours > anything where one wrong assumption costs you a day • the setting that saves the most > Medium is the default in the Claude apps and Claude Code > on Low or Medium it beats Sonnet 5's best score for a tenth of the cost > raise effort only when the first answer falls short • the price > $2 in and $10 out, against $4 and $20 for Opus > cache reads $0.20 on both • check before you switch > if you ran Sonnet with thinking off, move to the new between_tools setting first whoever routes the weekly grunt work to Sonnet 5.5 and saves Opus for the hard calls ships more on half the budget, and that's the person who gets noticed
0:24

this is certified f*cking gold for anyone paying for Claude Sonnet 5.5 costs half of what Opus 5.5 does on real office work across 44 jobs it scores 1844. Opus scores 1846 on coding it went from 10.3% to 70.6% in one version and passed Opus on the way most of what you pay Opus for, Sonnet 5.5 now does at half the price here's how to split the work: • give it to Sonnet 5.5 > bug fixes and well-scoped coding tasks > decks built from your own slide template > spreadsheets and polished documents > UI polish, it has a real eye for design > fast back-and-forth, it runs 30%+ faster • keep it for Opus 5.5 > long, open-ended work with judgment calls for hours > anything where one wrong assumption costs you a day • the setting that saves the most > Medium is the default in the Claude apps and Claude Code > on Low or Medium it beats Sonnet 5's best score for a tenth of the cost > raise effort only when the first answer falls short • the price > $2 in and $10 out, against $4 and $20 for Opus > cache reads $0.20 on both • check before you switch > if you ran Sonnet with thinking off, move to the new between_tools setting first whoever routes the weekly grunt work to Sonnet 5.5 and saves Opus for the hard calls ships more on half the budget, and that's the person who gets noticed

Annatar.md

19,513 次观看 • 6 天前

Codex tip: once GPT-6.1 Sol is your main model, stop running Astra on every turn put Astra on call as an architect agent GPT-6.1 Sol keeps writing the code Astra only gets spawned 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? Astra reviews. Sol 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 models only see the ones that split - the full tree > GPT-6.1 Sol on high runs the main session > explorer reads the code on Luna > worker edits and runs tests on Sol > researcher pulls the docs on Luna > all three on medium > Astra on call as the architect > auto_review checks every approval paste the tree and this prompt into Codex ↓ "Rebuild my Codex setup around this tree: 1. Check ~/.codex/agents and .codex/agents for agents that already fit explorer, worker and researcher. > Draft new TOML files only for missing roles > explorer and researcher on gpt-6-luna, worker on gpt-6.1-sol, all with model_reasoning_effort medium > Add an architect agent on gpt-6-astra, model_reasoning_effort high, whose only job is reviewing plans, repeated errors and finished work > Skip any that pin a different model and list them 2. In ~/.codex/config.toml set model to gpt-6.1-sol, model_reasoning_effort to high and approvals_reviewer to auto_review 3. Find anything that would override this (active profiles, flags in my shell aliases, agents.default_subagent_model). Report it, change nothing 4. Add one rule to AGENTS.md: spawn the architect 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." ↳
0:29

Codex tip: once GPT-6.1 Sol is your main model, stop running Astra on every turn put Astra on call as an architect agent GPT-6.1 Sol keeps writing the code Astra only gets spawned 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? Astra reviews. Sol 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 models only see the ones that split - the full tree > GPT-6.1 Sol on high runs the main session > explorer reads the code on Luna > worker edits and runs tests on Sol > researcher pulls the docs on Luna > all three on medium > Astra on call as the architect > auto_review checks every approval paste the tree and this prompt into Codex ↓ "Rebuild my Codex setup around this tree: 1. Check ~/.codex/agents and .codex/agents for agents that already fit explorer, worker and researcher. > Draft new TOML files only for missing roles > explorer and researcher on gpt-6-luna, worker on gpt-6.1-sol, all with model_reasoning_effort medium > Add an architect agent on gpt-6-astra, model_reasoning_effort high, whose only job is reviewing plans, repeated errors and finished work > Skip any that pin a different model and list them 2. In ~/.codex/config.toml set model to gpt-6.1-sol, model_reasoning_effort to high and approvals_reviewer to auto_review 3. Find anything that would override this (active profiles, flags in my shell aliases, agents.default_subagent_model). Report it, change nothing 4. Add one rule to AGENTS.md: spawn the architect 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." ↳

delost

1,017,721 次观看 • 4 天前

I don't understand why everyone isn't doing this yet. Anthropic released a guide for Claude that makes work much more efficient while burning a fraction of the tokens Main Idea: Agent Teams in Claude Code Instead of burning the expensive Opus 5.5 context on every line of code, tasks are delegated across an autonomous swarm: Architect (Opus 5.5, high effort): Plans the structure and handles final PR merges Developers (Sonnet 5.5, medium effort): Write code inside isolated ⁠git worktree⁠ environments (UI/UX, backend) Adversary / Critic (Fable 5.1): Steps in at contract boundaries, recurring test failures, and pre-PR audits to catch vulnerabilities Script Layer (Jev): Handles mechanical tasks (opening files, CLI invocations) in 16ms without involving LLMs Launch the team via terminal: claude --teammates ux,backend,adversary Configure my Claude Code workspace for autonomous agent teams: In ⁠~/.claude/teams⁠, generate missing roles: set workers to ⁠Sonnet⁠ (⁠medium effort⁠) in separate ⁠git worktree⁠ branches, and the adversary to ⁠Fable⁠ In ⁠~/.claude/settings.json⁠, set ⁠CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1⁠ and lock the main session to ⁠effortLevel: high⁠ Initialize ⁠tasks.json⁠ with file-level locking for direct peer coordination In ⁠CLAUDE.md⁠, add a rule requiring an adversary review before opening a PR. Show configuration diffs before applying edits >
0:24

I don't understand why everyone isn't doing this yet. Anthropic released a guide for Claude that makes work much more efficient while burning a fraction of the tokens Main Idea: Agent Teams in Claude Code Instead of burning the expensive Opus 5.5 context on every line of code, tasks are delegated across an autonomous swarm: Architect (Opus 5.5, high effort): Plans the structure and handles final PR merges Developers (Sonnet 5.5, medium effort): Write code inside isolated ⁠git worktree⁠ environments (UI/UX, backend) Adversary / Critic (Fable 5.1): Steps in at contract boundaries, recurring test failures, and pre-PR audits to catch vulnerabilities Script Layer (Jev): Handles mechanical tasks (opening files, CLI invocations) in 16ms without involving LLMs Launch the team via terminal: claude --teammates ux,backend,adversary Configure my Claude Code workspace for autonomous agent teams: In ⁠~/.claude/teams⁠, generate missing roles: set workers to ⁠Sonnet⁠ (⁠medium effort⁠) in separate ⁠git worktree⁠ branches, and the adversary to ⁠Fable⁠ In ⁠~/.claude/settings.json⁠, set ⁠CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1⁠ and lock the main session to ⁠effortLevel: high⁠ Initialize ⁠tasks.json⁠ with file-level locking for direct peer coordination In ⁠CLAUDE.md⁠, add a rule requiring an adversary review before opening a PR. Show configuration diffs before applying edits >

Bober_smart

295,908 次观看 • 1 天前

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.
0:24

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.

Dan McAteer

912,025 次观看 • 3 个月前

Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.
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Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.

Dan McAteer

191,832 次观看 • 2 个月前

Claude Sonnet 4.8 is imminent. Most likely dropping today. Sonnet 4.6 is starting to look outdated. Look at the Flappy Bird test on BridgeBench. GPT 5.5 and Claude Opus 4.7 have moved past it. The model that used to be the default for most vibe coders is falling behind. Anthropic needs Sonnet 4.8 to close the gap. The second it drops, we're running it through every BridgeBench test and posting the results live. New Sonnet day. Let's see what Anthropic has.
0:28

Claude Sonnet 4.8 is imminent. Most likely dropping today. Sonnet 4.6 is starting to look outdated. Look at the Flappy Bird test on BridgeBench. GPT 5.5 and Claude Opus 4.7 have moved past it. The model that used to be the default for most vibe coders is falling behind. Anthropic needs Sonnet 4.8 to close the gap. The second it drops, we're running it through every BridgeBench test and posting the results live. New Sonnet day. Let's see what Anthropic has.

Bridgebench

16,715 次观看 • 4 个月前

You can now choose which model builds your app on Caffeine. The latest models are all in there: Opus 5.5 Fable 5.1 GPT-6 Astra GPT-6 Sol Kimi K3 Sonnet 5 DeepSeek V4.1 Flash Plan a whole new app with a frontier model, then switch to a faster, cheaper one for quick questions and small changes. It works on every plan, starting today.
3:11

You can now choose which model builds your app on Caffeine. The latest models are all in there: Opus 5.5 Fable 5.1 GPT-6 Astra GPT-6 Sol Kimi K3 Sonnet 5 DeepSeek V4.1 Flash Plan a whole new app with a frontier model, then switch to a faster, cheaper one for quick questions and small changes. It works on every plan, starting today.

caffeine

15,833 次观看 • 10 天前

Jev + Opus 5.5: Anthropic's new model beats GPT-6 Astra for 1/5 the cost, and 4 API changes will 400 your agent before it writes a single line I pulled these 10 steps from the migration docs so you don't learn them in production step 1 → $4 / $20 per 1M. Opus 5 was $5 / $25. cache reads dropped from $0.50 to $0.20 step 2 → 66.4% on Terminal-Bench 4.0 vs GPT-6 Astra 57.9% and Opus 5 52.3%. +14.1 points in one release, and on FrontierCode it beats Astra at default effort for 1/5 the cost step 3 → thinking can't be turned off anymore. send thinking: disabled and you get a 400. drop the field, set effort step 4 → tool_choice any and tool are gone. 400. switch to auto + strict step 5 → edit anything above a thinking block and the request dies. append only, or opt into drop_block step 6 → computer_20251124 is dead on the API. 400. move to computer_toolset_20260801 step 7 → the quiet one: default effort fell from high to medium. your agent thinks less than you set it up to and nothing tells you step 8 → hop Opus 5.5 → Sonnet 5 → Opus 5.5 and you pay 4.36 instead of 3.32. +31%, the cache dies and Sonnet can't read Opus's reasoning step 9 → change effort at the top of the request and the cache is gone. Jev sets it per message and the cache stays step 10 → switch fast - standard mid-session and it's a full cache miss. Jev picks speed once, on turn one one model, three knobs, zero 400s. that is Jev + Opus 5.5 send this to your Claude Code before you touch the model ID, then read my full Jev deep dive in the article below ↓
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Jev + Opus 5.5: Anthropic's new model beats GPT-6 Astra for 1/5 the cost, and 4 API changes will 400 your agent before it writes a single line I pulled these 10 steps from the migration docs so you don't learn them in production step 1 → $4 / $20 per 1M. Opus 5 was $5 / $25. cache reads dropped from $0.50 to $0.20 step 2 → 66.4% on Terminal-Bench 4.0 vs GPT-6 Astra 57.9% and Opus 5 52.3%. +14.1 points in one release, and on FrontierCode it beats Astra at default effort for 1/5 the cost step 3 → thinking can't be turned off anymore. send thinking: disabled and you get a 400. drop the field, set effort step 4 → tool_choice any and tool are gone. 400. switch to auto + strict step 5 → edit anything above a thinking block and the request dies. append only, or opt into drop_block step 6 → computer_20251124 is dead on the API. 400. move to computer_toolset_20260801 step 7 → the quiet one: default effort fell from high to medium. your agent thinks less than you set it up to and nothing tells you step 8 → hop Opus 5.5 → Sonnet 5 → Opus 5.5 and you pay 4.36 instead of 3.32. +31%, the cache dies and Sonnet can't read Opus's reasoning step 9 → change effort at the top of the request and the cache is gone. Jev sets it per message and the cache stays step 10 → switch fast - standard mid-session and it's a full cache miss. Jev picks speed once, on turn one one model, three knobs, zero 400s. that is Jev + Opus 5.5 send this to your Claude Code before you touch the model ID, then read my full Jev deep dive in the article below ↓

Carnage

16,674 次观看 • 12 天前

Jev + Opus 5.5 is the most underrated setup in AI right now, and i don't get why nobody's talking about it. I stopped letting Opus make every small decision in my agents. Jev makes them now. My Opus bill dropped ~500% on the same tasks, same results. Here's what Jev handles: - which files and notes to load before Opus sees anything - which effort level each task actually needs - what to do when a tool fails - which tests to run, and when to stop Opus only gets called for the hard reasoning. Every decision is a typed result the host checks before it runs. The exact prompt to set this up in your workflow is below.
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Jev + Opus 5.5 is the most underrated setup in AI right now, and i don't get why nobody's talking about it. I stopped letting Opus make every small decision in my agents. Jev makes them now. My Opus bill dropped ~500% on the same tasks, same results. Here's what Jev handles: - which files and notes to load before Opus sees anything - which effort level each task actually needs - what to do when a tool fails - which tests to run, and when to stop Opus only gets called for the hard reasoning. Every decision is a typed result the host checks before it runs. The exact prompt to set this up in your workflow is below.

Anatoli Kopadze

74,966 次观看 • 8 天前

OPUS 5.5 + SONNET 5.5 + JEV + DOTS on one spider, and 90% of your work is gone... one spider reads 5,152 items across 6 sources that you never open: 2,140 emails, 1,204 CRM records, 860 slack messages nothing waits for you to write a prompt, because Dots is always on and owns the job 24/7 every item gets a decision from Jev in 81 ms, so all 5,152 take under 7 minutes: urgent or not, how risky, and 1 of 3 routes the routine work goes to Sonnet 5.5, 12 drafts in this run, 12 marked done, 0 written by you the whole time Opus 5.5 sleeps and wakes up for 1 hard case out of 5,152. the other 5,151 never wake it your share drops from 100% to 10%, the other 90% of your work is gone ↓
0:33

OPUS 5.5 + SONNET 5.5 + JEV + DOTS on one spider, and 90% of your work is gone... one spider reads 5,152 items across 6 sources that you never open: 2,140 emails, 1,204 CRM records, 860 slack messages nothing waits for you to write a prompt, because Dots is always on and owns the job 24/7 every item gets a decision from Jev in 81 ms, so all 5,152 take under 7 minutes: urgent or not, how risky, and 1 of 3 routes the routine work goes to Sonnet 5.5, 12 drafts in this run, 12 marked done, 0 written by you the whole time Opus 5.5 sleeps and wakes up for 1 hard case out of 5,152. the other 5,151 never wake it your share drops from 100% to 10%, the other 90% of your work is gone ↓

Noisy

36,018 次观看 • 2 天前

A viral Claude Code guide claims agent teams cut token use, but Anthropic's documentation says teams use significantly more tokens than a single session. → Agent teams are experimental and turn on with CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1, and each teammate has its own context window → There is no --teammates flag: users ask Claude for teammates in plain language, and custom roles go in subagent definitions → The token saver is the advisor tool, where a cheaper main model consults Opus or Fable only at key decision points → The advisor turns on with /advisor opus, the advisorModel setting or claude --advisor opus Source:
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A viral Claude Code guide claims agent teams cut token use, but Anthropic's documentation says teams use significantly more tokens than a single session. → Agent teams are experimental and turn on with CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1, and each teammate has its own context window → There is no --teammates flag: users ask Claude for teammates in plain language, and custom roles go in subagent definitions → The token saver is the advisor tool, where a cheaper main model consults Opus or Fable only at key decision points → The advisor turns on with /advisor opus, the advisorModel setting or claude --advisor opus Source:

0xMarioNawfal

46,292 次观看 • 10 小时前

JEV + OPUS 5.5 IS INSANE FOR BUILDING A COMPANY BRAIN I pulled the whole architecture out of the TypeSafe and Anthropic docs and packed it into a 14-page PDF the 10 steps: 1. meet the pair > Opus 5.5 thinks, Jev decides, your code holds the branch 2. stop asking a text generator for a yes or no > Jev returns a typed answer with a calibrated probability in 0.44s for $0.00035 3. ask everything at once > Choice, Score and Noul run in parallel, so the fourth question costs almost nothing 4. branch on the number > 0.999 goes straight into the if statement. ~99% of turns end right here 5. stop routing blind > Opus 5.5 to Sonnet and back costs 5.84 against 3.32 for staying on 5.5 6. keep one context warm > cache reads at $0.20 per Mtok are 20x cheaper than a fresh load 7. escalate the hard part > the toughest 1% goes to Opus 5.5 with 1M context and 66.4% on Terminal-Bench 4.0 8. score every chunk on every query > keep whole, summarize or drop. the context gets rebuilt each turn 9. gate the actual command > every bash call gets classified before it runs, inside your own code 10. judge 100% of runs > $3.50 a day for 10,000 traces, and it matched the human label on all 500 decisions the result: a while loop that paid a frontier model for every tiny call turns into a brain that spends a fraction of a cent to notice and pays properly only when it has to think the person who brings this into their team walks into the budget meeting with the AI bill cut and the output up the PDF maps the company brain. the loop side of it - how Jev takes a Claude bill from $765 to $3 a month - is in the article below ↓
0:24

JEV + OPUS 5.5 IS INSANE FOR BUILDING A COMPANY BRAIN I pulled the whole architecture out of the TypeSafe and Anthropic docs and packed it into a 14-page PDF the 10 steps: 1. meet the pair > Opus 5.5 thinks, Jev decides, your code holds the branch 2. stop asking a text generator for a yes or no > Jev returns a typed answer with a calibrated probability in 0.44s for $0.00035 3. ask everything at once > Choice, Score and Noul run in parallel, so the fourth question costs almost nothing 4. branch on the number > 0.999 goes straight into the if statement. ~99% of turns end right here 5. stop routing blind > Opus 5.5 to Sonnet and back costs 5.84 against 3.32 for staying on 5.5 6. keep one context warm > cache reads at $0.20 per Mtok are 20x cheaper than a fresh load 7. escalate the hard part > the toughest 1% goes to Opus 5.5 with 1M context and 66.4% on Terminal-Bench 4.0 8. score every chunk on every query > keep whole, summarize or drop. the context gets rebuilt each turn 9. gate the actual command > every bash call gets classified before it runs, inside your own code 10. judge 100% of runs > $3.50 a day for 10,000 traces, and it matched the human label on all 500 decisions the result: a while loop that paid a frontier model for every tiny call turns into a brain that spends a fraction of a cent to notice and pays properly only when it has to think the person who brings this into their team walks into the budget meeting with the AI bill cut and the output up the PDF maps the company brain. the loop side of it - how Jev takes a Claude bill from $765 to $3 a month - is in the article below ↓

Mr. Buzzoni

85,590 次观看 • 7 天前

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?
18:49

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?

JJ Englert

10,737 次观看 • 3 个月前

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
0:30

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

thehype.

18,509 次观看 • 1 个月前