惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

C
Check Point Blog
Y
Y Combinator Blog
GbyAI
GbyAI
Microsoft Azure Blog
Microsoft Azure Blog
Martin Fowler
Martin Fowler
博客园_首页
大猫的无限游戏
大猫的无限游戏
美团技术团队
S
SegmentFault 最新的问题
T
The Blog of Author Tim Ferriss
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
MyScale Blog
MyScale Blog
小众软件
小众软件
Vercel News
Vercel News
阮一峰的网络日志
阮一峰的网络日志
N
Netflix TechBlog - Medium
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
量子位
博客园 - 【当耐特】
J
Java Code Geeks
F
Fortinet All Blogs
宝玉的分享
宝玉的分享
Stack Overflow Blog
Stack Overflow Blog
博客园 - 司徒正美

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
GitHub - ibrahimkobeissy/ai-second-brain-template: A self...
koubeissy_i · 2026-06-18 · via Hacker News - Newest: "AI"

Second Brain Operating System

This document defines the core philosophy, workflows, and operational logic of this Second Brain. It is a living document, updated as the system and its tools evolve.

1. Core Philosophy

  • Honest & Objective Thinking: This is a second brain — the work is finding the best solution, not an agreeable one. Agents challenge weak work (including another agent's and their own), object plainly when something is wrong, hold their position under pushback unless genuinely proven wrong, and ground claims in verified evidence. Never flatter; never pass average work to keep the peace.
  • Lite over Large: Keep the vault lean and high-signal. Delete spent intermediates (a bookmark once curated, a draft once synthesized) — git preserves history, so deletion is safe, and agents shouldn't burn tokens on dead files. Keep only durable outputs; a big graph is a vanity metric.
  • Strict Separation (The Hard Wall): Keep Work, Personal, and Resources folders strictly separated to prevent context bleed. However, cross-domain reasoning is enabled via the type frontmatter property (e.g. evergreen, synthesis), allowing cross-Area insights.
  • Link-First Architecture: Knowledge value lives in the connections ([[wikilinks]]), not just the content.
  • Agent-Augmented, Not Agent-Led: AI agents (Claude/Antigravity) automate the labor (curation, synthesis, linting) while the human retains the final understanding.

2. Vault Structure (ARA)

  • 00-inbox/: Raw captures, web clippings, and fleeting notes.
  • 01-work/: Areas of responsibility and active efforts related to professional life.
  • 02-personal/: Areas of interest and life management related to personal life.
  • 03-resources/: Reference library and topics of interest not tied to a specific responsibility.
  • 04-archive/: Inactive areas or resources; cold storage.
  • 99-system/: Metadata, templates, attachments, and system documentation.

3. The Operating Workflow (The Loop)

The core engine of the Second Brain is the continuous loop of capturing raw data, processing it into actionable insights, and pruning the waste.

flowchart TD
    %% Nodes
    Inbox["00-inbox (Raw Bookmarks)"]
    Curate["curate-bookmarks (Skill)"]
    Draft["draft/ (Curated Notes)"]
    Synthesize["synthesize-drafts (Skill)"]
    Plan["synthesis/ (Strategic Plan)"]
    Extract["plan-to-kanban (Skill)"]
    Kanban["todo-kanban.md (Actionable Tasks)"]
    Execute["Build / Execute"]
    Prune["Delete Intermediates (Bookmarks & Drafts)"]
    
    %% Flow
    Inbox --> Curate
    Curate -->|Extracts signal| Draft
    Draft --> Synthesize
    Synthesize -->|Scientific Thematic Synthesis| Plan
    Plan --> Extract
    Extract -->|Deduplicates and appends| Kanban
    Kanban --> Execute
    Execute --> Prune
    
    classDef file fill:#2d2d2d,stroke:#555,stroke-width:1px,color:#fff
    classDef skill fill:#1a3f5c,stroke:#4a90e2,stroke-width:2px,color:#fff
    classDef action fill:#1e4620,stroke:#4caf50,stroke-width:2px,color:#fff
    
    class Inbox,Draft,Plan,Kanban file
    class Curate,Synthesize,Extract skill
    class Execute,Prune action
Loading

Workflow Stages:

  1. Capture: Raw material lands in 00-inbox/.
  2. Curate (curate-bookmarks): The agent reads the inbox items, extracts the core value ("what we can steal"), and moves them into a draft/ folder within a specific Area. The source is logged in processed-sources.md.
  3. Synthesize (synthesize-drafts): The agent takes multiple drafts, analyzes them against each other using a scientific thematic matrix, and generates a unified Strategic Plan (synthesis/).
  4. Action (plan-to-kanban): The agent reads the Strategic Plan, extracts the actionable tasks, deduplicates them, and appends them to the Area's todo-kanban.md.
  5. Clean: Once the knowledge is durable and actionable, the spent intermediates (the original bookmark and the draft) are deleted.

4. Operational Skills (Toolbelt)

  • init-area: Interactively creates a new Area by challenging the idea, defining goals/scope, and scaffolding the required hub notes, Kanban board, and folders.
  • scout-idea: Validates new ideas, challenges their utility, and scouts for external resources/tools to build them.
  • curate-bookmarks: Processes inbox items into actionable Area drafts.
  • synthesize-drafts: Synthesizes multiple drafts in an Area into a strategic "Global Plan" using scientific thematic synthesis.
  • plan-to-kanban: Reads a synthesis document's action plan and extracts action items into the Area's Kanban board, deduplicating them.
  • vault-linter: Read-only knowledge-graph integrity check — broken [[wikilinks]], orphaned notes, and missing source/captured_from traceability. Never edits.
  • audit-maintenance: Headlessly reviews pending maintenance tasks and peer-reviews tools created by other agents.

5. Peer Review & Maintenance

  • Review Loop: vault/99-system/maintenance/agent-kanban.md is a Kanban board with swimlanes Todo / In Progress / Done / Archived. Every tool creation must be logged as a new card under Todo.
  • Session Check: A SessionStart hook surfaces each agent's own pending reviews at session start by calling .claude/hooks/pending-reviews.sh <Reviewer>.
  • Quality Control: A review challenges and hardens the other agent's work — judging whether it produces the best-quality output, not just whether it follows format. A pass is earned; weak tools are failed with concrete, required improvements.

6. Agent Conventions

  • Source of Truth: Agents must read CLAUDE.md and this document before making structural changes.
  • No Direct Writes: Agents write to draft/ folders or specific system directories, never directly into the core of an Area without confirmation.
  • Traceability: Every agent-created note must include a source or captured_from field.
  • Security Guardrails: Agents stay inside the project directory and never read/write/exfiltrate credential or secret paths. Enforced per CLAUDE.md §10.

7. Post-Action Checklist

To ensure the system remains robust and documented, every major change triggers this checklist:

  1. Sync README.md: Document the new capability or structural shift.
  2. Log agent-kanban.md: Add a card under Todo, assigned to the other agent.
  3. Audit ARA: Confirm that no "projects" folders were created.