Open sourced the methodology behind 600+ frameworks.
One skill file. Any AI tool. Any domain. Produces complete reusable frameworks.
Stop trading baseball cards. Build the card factory.
https://t.co/RmbfLxDUV6
The AI report I dropped this week was built on Claude Fable 5, the model it's about. As of June 12 it's offline. US export-control order over a flagged jailbreak, banned for foreign nationals, so Anthropic pulled it for everyone. No restoration date.
https://t.co/LUHI4ikSBR
@ZssBecker The model's fine. It's the methodology behind it. You're expecting AI to be great out of the box when the only way it gets better is if you teach it how you do things and what good looks like. You need to format that into
frameworks that it can parse.
https://t.co/47HWORfdBB
I fact-checked this week's AI news against primary sources.
Three of the biggest numbers were wrong. One was a model that doesn't exist.
https://t.co/k3TBeY3KCv
@rohanpaul_ai@EvoMapAI The economics framing is right. Worth adding: a Capsule gets more trustworthy with varied failures in its history, not just successes. Most framework libraries throw failures away. The ones that compound treat failure as part of the signal.
You might think frameworks are a modern productivity tool. Something McKinsey invented or that consultants sell.
The history is longer than that. Much longer.
Four eras across roughly twelve thousand years.
https://t.co/R1eS2IXRFA
This AI news report was written by the model it's about. Claude Opus 4.8, fact-checked by the AI itself, then anything that didn't survive got cut.
https://t.co/GWXXAB0slp
Commerce Department just announced $2 billion for quantum computing under the CHIPS Act. IBM alone is getting $1 billion.
When billions flow into an emerging sector, subcontracting opportunities follow. If your business supports advanced manufacturing or R&D environments, this market is worth watching.
(866) 621-5343 | https://t.co/27AGU6tNHi
#GovCon #QuantumComputing #FederalContracting
Add this to your AI:
"Tell me the source of every factual claim. If you don't have a source, say you're inferring and explain how."
Forces honesty about what's actually known.
https://t.co/D5hfQZ3BfX
@DanielMiessler The thread is at the workflow layer. The layer above is methodology, what encodes which workflow is correct, when to escalate, what good output looks like. Workflows are what methodology compiles into. Without that layer, infrastructure-as-code for AI is just executable intuition
@milesdeutscher It's not the model. It's your documentation.
Start with what good looks like, what failure looks like, what the edge cases are. Then encode it into a structure that holds the logic regardless of who's holding it.
That's a framework. Follow for more.
Six practitioner communities are building the same architecture and giving it six different names.
Agent harness. Implementation layer. Governance framework. Cognitive scaffold. Compiled artifact. Framework.
Same object. Six words. No shared map. Until now
https://t.co/3YEiAn3DAQ
DeepMind mapped six ways AI agents get hijacked.
86% success on HTML injection.
10/10 password exfiltration.
One email leaked all of M365 Copilot.
Then Claude Mythos leaked...
The defense isn't the model. It's the structure around it.
https://t.co/HUvQyZhzy5
The Claude web chat doesn't have access to your computer.
Unless you set up an MCP through the Claude desktop app. Same chats, same model, but wired into your filesystem. The chat reads files directly instead of waiting for you to paste them in.
https://t.co/vAKIkbYVmv
Add this to your AI:
"Spend two minutes listing every way this plan could guarantee failure before you tell me how to make it succeed."
Catches the blind spots that destroy good ideas.
https://t.co/D5hfQZ3BfX
A framework is a behavioral standard for a category of work. A skill is an instruction set for a specific task. The framework governs the skill, not the other way around.
Add this to your AI:
"Tell me whether each claim is something you know is true, or a pattern you noticed and assumed is true. Label them differently."
The single change that makes AI output ten times more credible. https://t.co/D5hfQZ3BfX