Use Fable 5 as orchestrator and Opus + Codex to execute (to save fable usage):
Fable 5 (max reasoning) = orchestrator
Opus = deep reasoning subagent
Sonnet = mechanical work subagent
Codex = peer Sr. engineer, different perspective
Setup:
1. Set Fable 5 as your main model In Claude Code: /model → Fable 5 → reasoning /effort to max
2. Create 2 subagents with /agents In Claude Code:
deep-reasoner → pinned to opus "Use for reasoning-heavy phases, architecture, debugging complex issues, algorithm design. Think thoroughly, return a concise conclusion the orchestrator can act on."
fast-worker → pinned to sonnet "Use for mechanical tasks, boilerplate, tests, formatting, simple edits. Execute efficiently."
3. Add OpenAI's official Codex plugin (install codex cli in your computer first), In Claude Code type:
/plugin marketplace add openai/codex-plugin-cc
/plugin install codex@openai-codex
/codex:setup
4. Drop this in your CLAUDE.md in your folder:
## Orchestration workflow
You (Fable) are the orchestrator. Plan, decompose, synthesize.
Reasoning-heavy phases → deep-reasoner
Mechanical work → fast-worker
Codex (/codex:rescue --background) is a cracked engineer on par with deep-reasoner, from a different perspective. Treat as a peer, not a reviewer.
High-stakes decisions: task Opus + Codex on the same problem in parallel, synthesize the best of both, without showing either the other's answer. Keep your own context lean.
5. Then prompt Fable like a tech lead: "Goal: [what you want] Context: [files, constraints] You're the lead. Delegate reasoning to deep-reasoner, grunt work to fast-worker, fresh-perspective problems to Codex. Show me your plan first, then execute."
That's it.
@terziev Бетонните павенца, са доказано лоша практика, и изискват ужасно много подръжка, и както вече някой се изказа, нека да взаимстваме и подобрим настилките. Асфалтираните тротоари са не лоша идея, доста по удобни за детски колички, колела и тн.
i'm mass-releasing everything.
the complete automation playbook i use to run a $600K/month agency:
→ 47 n8n workflows agencies charge $5K-$15K each for
→ the one-sentence prompts that build any of them in under 3 minutes
→ my "consultant pricing" spreadsheet (what they charge vs what it costs)
→ 12 plug-and-play templates for the automations every business needs
→ the exact Claude prompts i use to debug workflows instantly
here's what's in it:
LEAD GEN (agencies charge $18K+ total):
- lead enrichment + scoring pipeline
- competitor monitoring system
- social listening engine
- cold outreach sequencer
OPERATIONS (agencies charge $24K+ total):
- client onboarding automations
- invoice recovery system
- meeting no-show rescuer
- daily CEO dashboard
CONTENT (agencies charge $15K+ total):
- blog-to-social repurposer
- AI content calendar builder
- review response drafter
- newsletter automation
every workflow is described in plain english.
paste into Synta → deploys to n8n → running in minutes.
no code. no courses. no $200/hr "experts."
i built my entire agency on these.
now you can too.
reply "PLAYBOOK" + retweet
i'll send the entire vault.
(must be following so i can DM)
taking this down friday. this should be a $997 product.
A really cool app for parents. I will probably become a paying user.
Essentially, you scan your entire Lego collection, and it gives you instructions on what to build.
Also, it's a great example of an app with a moat. It's not easy to replicate this app since (I assume) it requires a solid investment into gathering all the data (instructions) and training the model to segment Legos properly.
I have so many questions about this. Will this in any way affect third party sites like APKMirror? How will Google match identities of developers to sideloaded APKs? Based on signatures? I'm so confused.
Why is no one talking about this?
This is why I don't use an AI browser
You can literally get prompt injected and your bank account drained by doomscrolling on reddit:
How to build a thriving open source community by writing code like bacteria do 🦠. Bacterial code (genomes) are:
- small (each line of code costs energy)
- modular (organized into groups of swappable operons)
- self-contained (easily "copy paste-able" via horizontal gene transfer)
If chunks of code are small, modular, self-contained and trivial to copy-and-paste, the community can thrive via horizontal gene transfer. For any function (gene) or class (operon) that you write: can you imagine someone going "yoink" without knowing the rest of your code or having to import anything new, to gain a benefit? Could your code be a trending GitHub gist?
This coding style guide has allowed bacteria to colonize every ecological nook from cold to hot to acidic or alkaline in the depths of the Earth and the vacuum of space, along with an insane diversity of carbon anabolism, energy metabolism, etc. It excels at rapid prototyping but... it can't build complex life. By comparison, the eukaryotic genome is a significantly larger, more complex, organized and coupled monorepo. Significantly less inventive but necessary for complex life - for building entire organs and coordinating their activity. With our advantage of intelligent design, it should possible to take advantage of both. Build a eukaryotic monorepo backbone if you have to, but maximize bacterial DNA.
1. Download Google AI Edge Gallery
Access the official Google AI Edge Gallery GitHub repo.
Go to the "Releases" section, then download and install the .apk file (Android).
The iOS version is coming soon.
Link: https://t.co/KKUgxtyyuV