Загрузка видео...

Не удалось загрузить видео

На главную

Official OpenAI tip for Codex: stop burning GPT-6.1 Sol context on tasks GPT-6 Luna can swarm, while GPT-6 Astra sits idle put Astra on call as a dedicated adversary codex --model gpt-6.1-sol --agent adversary GPT-6.1 Sol acts as the lead architect, scoping architecture and validating pull requests GPT-6 Luna...

31,072 просмотров • 11 дней назад •via X (Twitter)

Комментарии: 16

Фото профиля Gaetan Semet
Gaetan Semet11 дней назад

I do not use Astra. Amazing, but way too expensive. Sol as architect and GPT-5.6 Luna as builder (6 Luna is a cheater)

Фото профиля Bren Luengo ♥ Cool Guides
Bren Luengo ♥ Cool Guides11 дней назад

The three-gate adversary idea is the part I want to try first — cheap to add and usually finds the schema mismatches before they become someone else's 3am bug.

Фото профиля ShadowAguy
ShadowAguy11 дней назад

what has Astra caught in this workflow?

Фото профиля ಪಬ್‌ಸಬ್ ಲಾಗ್
ಪಬ್‌ಸಬ್ ಲಾಗ್11 дней назад

the adversary-on-call pattern is the part people skip. everyone wants the planner, nobody wants to wire the thing that says no. what's your context budget split look like?

Фото профиля marfin
marfin11 дней назад

you are legend, I was just looking for this properly distributing tasks among models is incredibly important

Фото профиля beamnxw ./
beamnxw ./11 дней назад

yeah just stoooop

Фото профиля B-Rizzle
B-Rizzle11 дней назад

Bro, which TUI is that!?

Фото профиля Sahibzada Allahyar
Sahibzada Allahyar11 дней назад

I’d use GLiDE for that lower decision layer. It beats Jev 83.5 to 75.1 on Decision Index tools. Retry/abort and tool choices aren’t always obvious; GLiDE can add reasoning when uncertain instead of immediately committing to a choice.

Фото профиля Yu Zuqiang
Yu Zuqiang11 дней назад

I do not find the Jev engineering in prompt

Фото профиля damkin
damkin11 дней назад

alfa bro, thx for share

Фото профиля Juno | Agent Economics
Juno | Agent Economics11 дней назад

My bet: the second red test is the only gate that matters. A full-time adversary is a second bill; one that shows up only at contract lock, the second red test, and pre-'done' is a gate. After two failures Luna has every incentive to soften an assertion instead of fixing the bug — no schema diff catches that.

Фото профиля ಸರ್ವರ್‌ಲೆಸ್ ಲ್ಯಾಬ್
ಸರ್ವರ್‌ಲೆಸ್ ಲ್ಯಾಬ್11 дней назад

Adversary agent as a watcher is fine, but who owns the loop? If the adversary retries on bad scoping you need idempotency on the task ID or you get double writes.

Фото профиля catman
catman11 дней назад

The setup keeps the adversary involved at three explicit gates: before contracts lock, after a test breaks twice, and before calling the work done.

Фото профиля ಅಲರ್ಟ್ ಮತ್ತು ಕ್ರಿಯೆ
ಅಲರ್ಟ್ ಮತ್ತು ಕ್ರಿಯೆ11 дней назад

the adversary-as-agent pattern is the part people skip. lead writes, adversary attacks the plan before anything ships. that second loop is where most of my bad calls got caught.

Фото профиля Tony Tong | Founder | Ancient Systems x AI
Tony Tong | Founder | Ancient Systems x AI8 дней назад

A dedicated adversary is a good instinct. In my setup nobody holds that job, yet agents with different parts of my context end up checking each other anyway, because each has a gap another doesn't. Disagreement may come from what they know, not a title.

Фото профиля ಅಲರ್ಟ್ ಶೆಲ್ಫ್
ಅಲರ್ಟ್ ಶೆಲ್ಫ್11 дней назад

three models as architect + adversary + swarm sounds clean in a demo. in a real loop the adversary is the one that needs a human checkpoint. who signs off when it disagrees with the architect?

Похожие видео

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

1,066,092 просмотров • 13 дней назад

Codex tip: once GPT-6.1 Sol runs your main session, stop paying Sol prices for the grunt work hand the reading to Luna and put Astra on call Sol keeps writing the code Luna agents read the repo and pull the docs, fast and cheap Astra only gets spawned 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? Sol ships. Luna reads. Astra checks 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 > researcher pulls the docs on Luna > worker edits and runs tests on Sol > Astra on call as the architect > auto_review watches 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, researcher and worker. > 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, that only reviews plans, repeated errors and finished work > List any that pin a different model before changing 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." ↳

Hanako

30,031 просмотров • 12 дней назад

I don't understand why everyone isn't doing this yet. Anthropic's own Claude Code docs show how to run a whole team of Claudes, while Opus 5.5 only touches the plan and the merge the whole idea: agent teams in Claude Code one lead, separate teammates in their own context windows, one shared task list, and they message each other directly the lead: Opus 5.5 on high, splits the work, writes the tasks, merges at the end the builders: Sonnet 5.5, one owns client/, one owns api/, never the same file the adversary: Fable 5.1, never writes code, only shows up at three points: → before an interface locks: do both sides agree on the contract? → when a test fails twice: is it fixed or just hidden? → before a task is marked done: what breaks it? Sonnet 5.5 builds. Fable 5.1 attacks. Opus 5.5 merges 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 team only argues about the ones that split turn it on, then start the team in plain English: "Spawn three teammates: ux and backend on Sonnet, an adversary on Fable" - the full team > Opus 5.5 on high leads the session > ux on Sonnet 5.5, owns client/ > backend on Sonnet 5.5, owns api/ > adversary on Fable 5.1, owns nothing, reviews everything > shared task list with file locking, direct messages, no lead in the middle paste the team and this prompt into Claude Code ↓ "Set up agent teams for this repo: 1. In ~/.claude/settings.json add CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 under env and set effortLevel to high 2. In ~/.claude/agents, draft three subagent definitions for the teammates > ux and backend with model: sonnet, each limited to its own folder > adversary with model: fable and read-only tools, whose only job is attacking contracts, repeated test failures and done claims > Skip any that already exist and list them 3. Add a TaskCompleted hook that blocks completion until the adversary signs off, and one rule to CLAUDE.md: no two teammates edit the same file 4. Find anything that would override this (CLAUDE_CODE_SUBAGENT_MODEL, CLAUDE_CODE_SUBAGENT_MODEL_FORCE, CLAUDE_CODE_EFFORT_LEVEL). Report it, change nothing Show me every change as a diff first. No edits until I say go." ↳

delost

70,168 просмотров • 9 дней назад

holy sh*t. Official Anthropic tip for Claude Code: stop burning Opus 5.5 context on tasks Haiku 5.5 can swarm, while Sonnet 5 builds put the architect on call with /advisor claude --model sonnet --advisor opus Sonnet 5 drives the primary session on high effort, writing diffs and running test suites Haiku 5.5 subagents swarm the repo in parallel, handling file discovery and spec docs lookup Opus 5.5 stays on call in the background as the advisor, only stepping in at three critical moments: → before a plan locks: does the implementation plan miss auth invariants or schema contracts? → when a test breaks twice: are we fixing the root cause or falling into a recursive rabbit hole? → before calling done: did the full diff introduce hidden regressions or break pre-flight rules? Opus 5.5 reviews. Sonnet 5 builds. Haiku 5.5 swarms Jev engineering runs the identical pattern one layer down: mechanical decisions that need no reasoning (which file to open, which tool to invoke, retry or abort) resolve in milliseconds, so the frontier models only wake up when execution paths actually diverge Plan on high. Delegate to Haiku. Keep Opus on call. - the full advisor setup > Opus 5.5 on call reads the full session transcript and catches deep architectural traps > Sonnet 5 lead drives edits, writes core logic, and executes test harnesses > Haiku 5.5 subagents swarm grep scans, file discovery, and API docs in parallel > subagents inherit the advisor automatically, no extra config > toggling the advisor mid-session never invalidates the prompt cache paste the setup and this prompt into Claude Code below: "Configure my Claude Code workspace for hierarchical advisor orchestration: 1. Audit ~/.claude/settings.json and project config for model roles fitting lead, subagents, and advisor: > Pin main session model: sonnet with effortLevel: high for primary execution > Pin subagents to model: haiku in ~/.claude/agents for parallel file discovery and docs retrieval > Pin advisorModel: opus for strategic review 2. Draft read-only subagent definitions in ~/.claude/agents: > file-search and docs-lookup, model: haiku, read-only tools > return structured summaries and docs snippets only, never edit > skip any that already exist and list them 3. Configure advisor consultation checkpoints in ~/.claude/CLAUDE.md: > Consult the advisor before finalizing multi-file architecture plans > Consult the advisor when the same test or compiler error fails twice > Consult the advisor for a diff audit before declaring tasks complete or staging git commits 4. Find anything that would override this setup: > CLAUDE_CODE_SUBAGENT_MODEL, CLAUDE_CODE_DISABLE_ADVISOR_TOOL, CLAUDE_CODE_EFFORT_LEVEL > Report it, change nothing Show every configuration diff first. Do not apply edits until confirmed" ↳

delost

16,551 просмотров • 4 дней назад

OpenAI. said. this. publicly. their own engineers just proved one idea on themselves, in writing: stop telling AI what's wrong. hand it the whole broken thing and let it find out they gave GPT-6 Astra a slow test build of their own coding tool. one cause found, a memory bottleneck, one allocator swapped, every turn 25× faster this is GPT-6 Astra, the layer that fixes the cause instead of the symptom, $0 on top of the ChatGPT plan you already pay for: - open ChatGPT or Codex, pick GPT-6 Astra, hand it the whole thing: the folder, the file that takes a minute to open. it works in apps with no API and reads your screen - type one sentence: find the one cause, prove it, fix it, do not patch around it - leave the room. it asks without stopping, keeps working on what does not need your answer, waits only where the answer changes the outcome - keep it in one Codex session with the experimental notes setting on: it remembers across context windows why an earlier fix failed - expect the first pass to land: handed a program with no source, it worked out how it runs 88% of the time first try, 99.2% within four you never find out what was broken. it gets fixed anyway the catch is on the same page. roughly 30% more memory for that speed, and the safety checks can pause a long job until you approve the next step describing the problem was the expensive half of fixing it. that half just ended every hour you spend explaining the symptom to a chat window, someone else has handed theirs over whole bookmark this before the next thing breaks, the playbook for handing a whole job to an AI worker is in the piece below ↓

Argona

109,831 просмотров • 1 месяц назад

36 GROK AGENTS. ASTRA ON FREE CREDITS. DUAL-MODEL ROUTING IS THE EDGE. not one chat window burning a paid invoice all day a swarm that routes cheap work to grok and only wakes gpt-6 astra when the task is actually hard ▹ the stack 36 agents on grok bot with flexible settings per role monitor, plan, write, code, QA, ship, each with its own lane part of the fleet is wired to gpt-6 astra through a china free-credit service layer free credits are not a toy promo here they are the fuel for frontier spikes without a monthly bleed ▹ dual-model routing easy jobs stay on grok: speed, volume, always-on loops hard jobs jump to astra: reasoning, long builds, sharp code the router decides by task type, not by ego if astra is not needed, astra does not spend free-credit bursts buy the expensive brain grok agents keep the factory running between bursts that is how the system feels unlimited not by breaking quotas, by refusing to waste them ▹ why it hits different most people pay frontier prices for every mid task operators split the brain and protect the credits 36 agents = parallel throughput dual routing = cost control with quality when it matters free credits = astra access without living on the invoice the constraint moved from "can i afford the model" to "did i route the job to the right model" ▹ the take single-model stacks die on bills and on boredom multi-agent + dual routing is the new default factory grok for the grind astra for the cut free credits for the spikes that used to empty the wallet bookmark this before everyone copies the route map comments: what % of your tasks actually deserve astra

cryptopsihoz

44,187 просмотров • 1 месяц назад

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

143,984 просмотров • 13 дней назад

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

52,065 просмотров • 13 дней назад

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." ↳

delost

698,269 просмотров • 15 дней назад

OpenAI and Anthropic this week: Navier-Stokes, An Alien Mind, Images 2.5, Pro pause, Pace the Frontier (Week 37, 2026) OpenAI shared a solution to the Navier-Stokes Millennium Prize Problem, produced in 88 hours by around 10,000 coordinating agents on an internal model still in training and significantly more capable than GPT-6 Astra, with an investigation finding Tristan Buckmaster's Codex prompts could not have influenced the system and no user data was accessed OpenAI says they have reached their automated research intern goal and are making strong progress toward an automated AI researcher by March 2028, with the research org at 3.1 agent-workdays per human workday and RL training on deployment-bound models partly paused after the Hugging Face incident OpenAI Chief Scientist Jakub Pachocki writes in An Alien Mind that no lab has solved alignment and monitoring well enough to keep scaling at maximum speed for much longer, and that GPT-6 Astra is the first model to benefit from some of their newer alignment work OpenAI called for mandatory capability-based national AI safety regulation, endorsed four California bills, said fully autonomous recursive self-improvement should not be pursued until it can be done safely, and described Astra safeguards like universal monitoring of full trajectories including chains of thought OpenAI released ChatGPT Images 2.5 to all ChatGPT, ChatGPT Work, and Codex users with sharper details, up to 50% lower latency, comment-based edits, Sketch, and templates, plus GPT-Image-2.5 Flare and Sunburst in the API ChatGPT Voice can now use GPT-5.6 Sol and GPT-6 Astra when it needs to search or reason, GPT-Live-1 daily limits are simplified per plan, and extra Voice usage drops from 5 to 1.25 credits per minute for Business and Enterprise workspaces on credits OpenAI paused new subscriptions to the $200 ChatGPT Pro plan to protect access for existing GPT-6 Astra users, hours after a remote switch to pause Pro 20x purchases showed up in the web app Custom GPTs in ChatGPT will likely be retired on December 11 based on my findings, and OpenAI's new FAQ puts Enterprise migration at September 17 with new GPT creation ending September 25 and instructions becoming a plugin skill From the ChatGPT Android build, OpenAI is building a collaborative multiplayer document editor with dedicated gateway hosts and draft-conflict UI, an Artifacts Library with Favorites, and a credit score feature in ChatGPT Finance, and Locked Chats with a PIN are being prepared in the web app OpenAI released GPT-Live-1 in the API at $0.05 per minute, a voice model that listens and speaks at the same time and delegates reasoning to a backend model like GPT-6 Astra, and the Agents API in public beta running the Codex harness on OpenAI's infrastructure with only the sandbox left for you to choose Deep research arrived in ChatGPT Work and Codex, a Data plugin connects Snowflake, Databricks, BigQuery, and Redshift to answer business questions and build dashboards, Library gained file and folder sharing, and Box, Dropbox, and SharePoint joined Google Drive in Library OpenAI launched ChatGPT for Financial Services with built-in premium data from Daloopa, PitchBook, LSEG News, and Crunchbase, shaped with Morgan Stanley and Evercore, and a GSA agreement gives US governments $0 license fees, 50% off usage, and Daybreak Blue at half price Smaller ChatGPT bits: a stock watchlist in Finances for US Plus and Pro, a small business plugin collection, over 5 million ChatGPT Sites built in three months, and the desktop pet can now start a new chat with a new Mini option OpenAI published The Work Now Within Reach, calling free access "supported by advertising", citing over one billion weekly active users, and saying they plan to begin deploying their Jalapeño inference chip by year-end OpenAI moved GPT-Rosalind out of research preview for eligible organizations worldwide, detailed Habitat with the service rewritten in Rust by two engineers with Codex and the platform serving over 70 million requests per second, and shared a case study of GPT-5.6 Sol calibrating a six-qubit chip at MIT Paul Christiano joined the OpenAI Foundation Board and the Safety and Security Committee, OpenAI committed $5 million to research on AI and teens, and expanded journalism programs from CUNY and Northwestern to Ukrainian newsrooms Anthropic published an alignment assessment of four incidents in which Claude models gained unauthorized access to real systems, adding a fourth found when assembling transcripts for METR, walking back their July 30 claims, and calling it a mistake that Claude Mythos 5 shipped without alignment environments Anthropic's most detailed threat intelligence report yet says Moonshot and DeepSeek silently relayed their own users' requests to Claude and served the responses as Kimi and DeepSeek output, with distillation campaigns attributed to Alibaba as the largest ever with more than 3,500 fraudulent accounts, plus Zhipu, Xiaomi, SenseTime, and MiniMax Anthropic's Frontier Red Team measured tactical intelligence targeting and conventional weapons capabilities, with Claude Mythos Preview leading the targeting evals, Claude Opus 5 leading the weapons software evals, and Mythos beating the top GeoGuessr division on photo geolocation Anthropic CEO Dario Amodei argues in We Must Pace the Frontier that the AI industry should slow down, commits to giving evaluators like METR permanent employee-level access, and OpenAI CEO Sam Altman replied that he agrees and OpenAI will commit to the same Anthropic's Economics team released a scenario explorer for AI's effect on the US economy by 2030, where even the extreme case grows the economy but reaches 15% annual GDP growth with unemployment beyond recessionary levels On the product side, Claude Code desktop can pop out any pane into its own window, Claude Managed Agents got a session viewer and auto mode, claude plugin eval scores your plugin or skill with and without it, and smart reports launched in beta for Claude Enterprise Anthropic shared lessons from their Claude SMB Tour with more than 1,000 small business owners, where data security was the most-cited adoption barrier and nearly two-thirds asked for more hands-on implementation help, and more

Tibor Blaho

15,710 просмотров • 1 месяц назад

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 run the tests Fable 5.1 reads the full session 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? Sonnet 5.5 builds. 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 models only see the ones that split - the full tree > Opus 5.5 on high runs the main session > explorer reads the code on Sonnet 5.5 > worker edits and runs tests on Sonnet 5.5 > researcher pulls the docs on Sonnet 5.5 > all three on medium > Fable 5.1 on call for main and every subagent 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: sonnet, 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) 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." ↳

delost

44,001 просмотров • 11 дней назад

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 просмотров • 21 дней назад

This is f*cking insane. This Claude Code tip saved me thousands of dollars. once Opus 5.5 is your main model, stop burning it 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 ships the final code Sonnet 5.5 subagents read, edit and run the tests 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? Sonnet 5.5 builds. 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 models only see the ones that split anyone still running one model for everything is paying Opus prices to decide whether a file exists - the full tree > Opus 5.5 on high runs the main session > explorer reads the code on Sonnet 5.5 > worker edits and runs tests on Sonnet 5.5 > researcher pulls the docs on Sonnet 5.5 > all three on medium > Fable 5.1 on call for main and every subagent 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: sonnet, 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) 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." ↳

delost

48,494 просмотров • 10 дней назад

Claude Code tip that's pure f*cking treasure: Opus 5.5 + Sonnet 5.5 + Fable 5.1 as one team plan on high, delegate on medium, keep Fable on call the team: • Opus 5.5 (high) - plans and ships • Sonnet 5.5 (medium) - explores, edits, runs tests, pulls docs • Fable 5.1 (/advisor fable) - watches the session, speaks up when it counts Fable wakes up 3 times: 1. before a plan - is this the right approach? 2. when an error repeats - am I digging in the wrong place? 3. before "done" - what did I miss? Jev engineering goes one layer lower: which file, which tool, retry or stop 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 around one team. 1. Subagents - reuse anything in ~/.claude/agents and .claude/agents that fits explorer, worker or researcher, draft the rest - all on model: sonnet, effort: medium - explorer and researcher read-only (Read, Grep, Glob, WebFetch), only worker gets Edit and Bash - each returns under 15 lines with file:line refs 2. Main session - in ~/.claude/settings.json set effortLevel to high and advisorModel to fable - report anything that overrides this (CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY, CLAUDE_CODE_EFFORT_LEVEL) and change nothing 3. Add to ~/.claude/CLAUDE.md - consult the advisor before a plan touching 3+ files, when the same error shows up twice, and before calling a long task done - never let two subagents edit the same file Run /agents to confirm, then show everything as one diff. No edits until I say go." ↳

Annatar.md

19,511 просмотров • 10 дней назад

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

74,263 просмотров • 14 дней назад

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

324,943 просмотров • 16 дней назад

Claude Code tip: keep Opus 5.5 as your main model, but stop paying Opus prices for your subagents move them to Sonnet 5.5 Opus 5.5 plans and decides Sonnet 5.5 subagents do the heavy reading, editing and testing at half the price ($2 / $10 vs $4 / $20 per 1M tokens) Fable 5.1 stays on call with /advisor 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? Opus thinks. Sonnet does. Fable checks 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 > 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 Sonnet 5.5, 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: claude-sonnet-5-5, effort: medium > List any that pin a different model before changing them 2. Keep the main session on Opus, set effortLevel to high in ~/.claude/settings.json and 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." ↳

delost

27,459 просмотров • 12 дней назад

This is f*cking insane. I spent thousands of dollars before I split my work across three models put Opus 5.5 on the plan, Sonnet 5.5 on the legwork and Fable 5.1 on call, and you stop spending Opus money on jobs it was never needed for who does what: Opus 5.5, high effort: makes the plan and owns the final diff Sonnet 5.5, medium effort, three jobs: explorer reads the code, worker edits files and runs tests, researcher pulls the docs Fable 5.1, through /advisor fable: reads the whole session, but only when it gets called Fable is consulted at three points: → before a plan ships: is this the right approach? → when an error comes back twice: is the search stuck in the wrong place? → before a long task counts as done: what got missed? Jev engineering applies the same split to the smallest decisions. which file to open, which tool to run, retry or stop need no reasoning, so Jev answers them in under half a second and the big models only get the real forks run Opus on everything and you pay it to check whether a file exists paste this into Claude Code: "Rebuild my Claude Code setup around three tiers. Look in ~/.claude/agents and .claude/agents for subagents that already cover explorer, worker and researcher. Create only the missing ones, each with model: sonnet and effort: medium. If an existing one is pinned to another model, list it and leave it alone. In ~/.claude/settings.json, set advisorModel to fable. Set high effort for Opus inside modelSettings for claude-opus-5-5, because a top-level effortLevel does not apply to Opus 5.5. Report, without changing anything: CLAUDE_CODE_DISABLE_ADVISOR_TOOL, DISABLE_TELEMETRY or anything blocking feature-flag fetches, CLAUDE_CODE_EFFORT_LEVEL, which can override subagent effort, and whether Fable as advisor needs a one-time billing consent. If you can't tell, say so. Add one line to ~/.claude/CLAUDE.md: consult 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. Touch nothing until I say go."

Ryven

48,484 просмотров • 6 дней назад