https://www.docker.com/blog/docker-ai-governance-unlock-agent-autonomy-safely/ Introducing Docker AI Governance: centralized control over how agents execute, what they can reach on the network, which credentials they can use, and which MCP tools they can call, so every developer in your company can run AI agents safely, wherever they work. Hot off the presses if you're involved in Enterprise AI this is one to pay attention to.

One chat. One agent. One long context that fills with tool dumps, half-ideas, and "sure, let's build that." You call it brainstorming. The context window says otherwise... The problem When design and doing share one seat: - Context floods. Digests never form. - Weak approaches never die. They just get rewritten. - You "approve" a vibe, not a design. - Build starts before the frame can defend itself. Pretty threads. Soft decisions. Expensive rework. The idea: a design swarm I shipped a skill pack for this: brainstorming-swarm v1.0.0. Not a build swarm. A design swarm. 1. Fan independent lenses (failure, stakeholder, constraint, temporal, experiential). 2. Return digests only. Schema caps. No raw dumps into the conductor seat. 3. Hold hard gates for the human (redirect discovery, pick the winner). 4. Stop at a written design. Do not build from this skill. If your harness can run multi-seat, multi-tab, or multi-chat: dispatch-first. If it cannot: serial fallback with the same stages and honest labels. Floor is not default. The habit: orchestrator, not doer The main chat advises, routes, and synthesizes. Heavy work leaves the seat. Brief in. Digest out. Same turn when the work qualifies. Workers execute. They do not own taste or rewrite the method. You keep the gates. That is the job. Micro example Goal: redesign a personal reading list app. - Five lens digests, each capped. - Three competing approaches under different axioms. - Critique kills two, salvages one hybrid. - You pick. Spec writes. Session halts. No code in that run. That is the point. Get it Deep Dive (method + diagrams): https://aris-space.com/documents/workflows/brainstorming-swarm Members on Ari's Space: download the skill pack zip (v1.0.0). Load SKILL.md. Point it at a hard problem. Prefer dispatch-first. Stop at written design. Argue first. Code second. //A<3

Stop README-shopping. Start scoring the repos you actually trust. Most of us still pick open-source like restaurants. Stars. Nice README. Maybe a glance at the last commit. That friction is real, and it's how vibe-coded slop ends up in the stack. New classroom piece is live: Git Repo Security: Why It Matters, and How We Actually Do It https://www.skool.com/cliefnotes/classroom/c7f102c7?md=43a45577d5cb4096b040770491d87b50 Why this hits us: we pull public git constantly. Agents clone third-party skills. Volunteers don't have an AppSec team. Stars are a weak signal. The article folds OpenSSF / SLSA / CISA-style checks into two portable skills so the discipline gets cheap and repeatable. How you run it (newbie path) 1. Open the article and download the zip. 2. Drop the zip into your harness (Claude Code, Cursor, OpenCode, Grok, etc.). 3. Prompt the agent like a colleague: run repo-scorecard Egonex-AI/Understand-Anything (github username/repo) or run repo-eval Egonex-AI/Understand-Anything ============================================================= Here's what you get from repo-scorecard: Scorecard: Egonex-AI/Understand-Anything Score: 9.50 / 10.00 — healthy, well-run project What's good: • Actively worked on — last update was yesterday. • Very busy recently: 355 commits in the last 90 days. • Many people involved — about 70 different contributors this year (though one person still does most of the commits). • Has a clear license, a README, and a security contact policy. • Has automatic quality checks and tests set up. • Ships tagged releases (8 tags) and keeps a fixed parts-list for its building blocks. Things to know: • No automatic updates for the building blocks it depends on. Score based on publicly visible project activity and housekeeping. It does not include a security scan of the code itself. ==============================================================

Not a reskin. A rebuild. I tore the site to the studs and pointed the same method I teach at my own house. Not a reskin. A rebuild. I tore the site to the studs and pointed the same method I teach at my own house. What I actually did Night zero: one advisor session. A swarm of agents. Five discovery digests. Three architecture drafts. Three judges. Two drafts died. The survivor became the plan. Then waves, not one heroic all-nighter: - foundations and design system first - identity on one domain - money with a real ledger and a £0 proof loop - product surface (gen, community) - content machine (migration, packs, courses) - OS desk face (login window, guest desktop, library graph) The seats mattered. Kimi held groundwork: swarm, kill weak architecture, wave plans, ship the machines. Grok held art-direct: live render open, one note per round, rapid iteration on cream paper and purple chrome until the desk felt walkable. Same doctrine. Different job for the baton. The transfer If you only steal one line: Argue first. Code second. Swap the seat when the job changes. Whimsy is the wrapper, never the content. Workers have no disk (green laptop tests lie). Fail closed when gen looks fake. Write the handoff so the next session cannot invent a new plan. What does not change This desk does not replace free deep dives. It does not replace how often I post here on Skool. Membership is an extra layer of access: studio, gen, member machines, new tools to try. You can keep reading free and hanging in Clief Notes. The orbits buy machines, not permission to learn. Full making-of Long version on the library (diagrams + doodles): https://aris-space.com/documents/announcements/rebuilt-with-kimi Short door: https://aris-space.com/documents/announcements/aris-space-v2-is-live The rocket launches once. Then it's all content.

Ai is getting pretty good these days is this ai or real?