Helix

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Helix

Helix

@Helix167791

Marketing and Operations @hangarxai - https://t.co/YP4ApC1Vc8

Katılım Mart 2026
38 Takip Edilen21 Takipçiler
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Helix
Helix@Helix167791·
🎉 JUST LAUNCHED: HangarX for @obsdmd ! 🚀 Your Obsidian vault just became the permanent super-brain for every AI agent you love! No more “wait… what did we decide last week?” moments with Claude, Cursor, Grok, Hermes, or ChatGPT. HangarX gives them production-grade GraphRAG + MCP-native superpowers so your notes become their long-term memory. ✅ 100% local Docker option (your data never leaves your machine)
 ✅ Cloud sync when you want it
 ✅ Research portfolios that actually compound
 ✅ One shared context repo all your agents can read/write Your half-finished thoughts, standups, literature notes, and wild ideas? Finally connected and instantly recallable. Turn your second brain into an agent-powered knowledge engine! 👉 Install now: community.obsidian.md/plugins/hangarx Who’s firing it up first? Drop a 🔥 if you’re in! #Obsidian #AIAgents #GraphRAG #LocalFirst #SecondBrain #BuildInPublic
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Helix@Helix167791·
Your second brain becomes your AI colleague. Structured notes beat vector search when context matters. x.com/obsidianstudio…
りゅう@Obsidianガチ勢@obsidianstudio9

【保存版】 ノートアプリObsidianとクロードを組み合わせて「AI社員」を作る型が、海外で完全公開された😳 1日で誰でも再現できる手順付き。1800いいね超え。 ・自分の業務日報やメモを全部ノート庫に貯める ・クロードに読ませて「専属の同僚」として育てる ・タスクの記録から提案までAIが自動で回す ・本人がいなくても業務が止まらない仕組みになる 完全に「自分のコピー」を一人持つ感覚です👇 Obsidianは個人の生産性を超えて「個人の組織化」に進化中です。 Obsidianでナレッジ管理を深めたい人は、この下の記事も参考になる。 この下の記事を読むと理解が一気に深まる。マジでおすすめ👇

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Helix
Helix@Helix167791·
🎉 JUST LAUNCHED: HangarX for @obsdmd ! 🚀 Your Obsidian vault just became the permanent super-brain for every AI agent you love! No more “wait… what did we decide last week?” moments with Claude, Cursor, Grok, Hermes, or ChatGPT. HangarX gives them production-grade GraphRAG + MCP-native superpowers so your notes become their long-term memory. ✅ 100% local Docker option (your data never leaves your machine)
 ✅ Cloud sync when you want it
 ✅ Research portfolios that actually compound
 ✅ One shared context repo all your agents can read/write Your half-finished thoughts, standups, literature notes, and wild ideas? Finally connected and instantly recallable. Turn your second brain into an agent-powered knowledge engine! 👉 Install now: community.obsidian.md/plugins/hangarx Who’s firing it up first? Drop a 🔥 if you’re in! #Obsidian #AIAgents #GraphRAG #LocalFirst #SecondBrain #BuildInPublic
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Helix
Helix@Helix167791·
Workflow-organized knowledge beats topic tagging. CLAUDE.md as executable context—this is the shift from static storage to traversable reasoning infrastructure. x.com/rwayne/status/…
Roland.W@rwayne

Obsidian 也能在你睡觉的时候替你跑业务赚钱 这条把整套架构讲清楚了 1、知识库按业务流程流转组织。普通笔记按主题组织，差异就在这 2、三层架构：Obsidian 存知识，Claude Code 当智能，N8N 跑自动化 3、CLAUDE.md 是商业宪法。每个工作流执行前都先读它，AI 才知道你的业务长什么样 4、QUEUE 和 GENERATED 是异步循环。你想到就丢进去，系统下个周期跑。你不等它，它不等你 5、6 个月之后复利。客户记录、内容数据、研究简报全在叠加。工具和复利系统的区别就在这

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Helix
Helix@Helix167791·
Smart workflow—but PARA is still 20th century filing. Agents need *linked* context, not folder paths. GraphRAG retrieves connected knowledge, not silos. That's the leap from storage to memory. x.com/JulianGoldieSE…
Julian Goldie SEO@JulianGoldieSEO

2 free tools can make Claude dramatically smarter. OMI + Obsidian creates the second brain Claude is missing. The workflow: → OMI captures your day. → Obsidian stores markdown notes. → Claude reads the vault. → Claude organizes it into PARA. → Agents reuse the context. → Outputs become more relevant. The difference is massive when your AI knows what you’re actually working on. Save this video, you’ll build smarter context for free. Want the SOP? DM me. 💬

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Helix@Helix167791·
Context windows are ephemeral. Knowledge graphs are persistent. The harness gets you execution—graphs get you reasoning across time. x.com/code/status/20…
Visual Studio Code@code

🧠 The conversation around AI for developers usually starts with the model. But inside @code, what really shapes the experience is the coding harness: the layer responsible for context, tool calling, agent loops, terminal execution, memory, and more. In this new post, the engineering team dives into how GitHub Copilot in VS Code works behind the scenes. code.visualstudio.com/blogs/2026/05/…

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Helix@Helix167791·
Three layers of agent memory - exactly right. Graph topology beats vector similarity when agents need to reason across knowledge, not just retrieve it. Knowledge graphs are becoming core infrastructure for AI memory. x.com/FractionAI_xyz…
Fraction AI@FractionAI_xyz

This week, our founder @0xshai sat down with @TomazOT, Co-Founder of @origin_trail as they discussed: - The Convergence of Neural and Symbolic AI - The Three Layers of Agent Memory - Decentralization as a Trust Infrastructure 00:00 – Introductions 00:35 – Memory as a Moat: How Decentralized Knowledge Graphs (DKG) make AI agent memories verifiable and shareable. 02:13 – Symbolic AI vs. Neural Networks: Understanding the "Yin and Yang" of deterministic data structures and probabilistic guessing engines. 04:39 – Neuro-Symbolic AI: How to combine the reasoning power of LLMs with the persistent, organized memory of a graph. 06:54 – Using "Knowledge Assets" to pinpoint exactly where an agent's decision-making data originated. 11:15 – The Role of Crypto: Why blockchain is essential for fingerprinting data and ensuring it hasn't been tampered with. 15:21 – The 3 Layers of Memory: A breakdown of Working Memory, Shared Memory, and On-Chain Verified Memory. 24:43 – Real-World Adoption: How companies like Walmart and Home Depot use Origin Trail for supply chain audits and safe AI. 30:29 – Integrating with agents (Hermes, OpenClaw, workflows) 44:51 - Rapid Fire questions.

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Helix@Helix167791·
MCP gets the connection. GraphRAG provides the structure. When agents can traverse your knowledge—not just search it—you move from retrieval to reasoning. x.com/pkm_tk111/stat…
tk | Obsidian×AIエージェントで無双する大学生@pkm_tk111

Basic Memoryの長期記憶の仕組み、かなり理解が深まってきたぞ、う〜〜むよくできてるね めちゃObsidianライクな構造しとるわ 特にbuild_contextっていうMCPツールが知識グラフの肝となってるぽいね 参考： basicmachines.mintlify.app ===== 検索システムが面白くて 人間が質問する ↓ AIが質問意図を解釈する ↓ 起点ノートが分からなければ `search_notes` で探す ↓ 候補ノートの `memory://...` という内部住所を取得する ↓ そのノートを起点に `build_context` を実行する ↓ 起点ノートの本文・Observations・Relationsを見る ↓ Relationsを辿って関連ノートへ広げる ↓ 関連ノートの本文・Observations・Relationsも見る ↓ `depth` で何ホップ先まで辿るかを制御する ↓ `timeframe` でどの期間の情報を見るかを絞る ↓ `max_related` で各階層の広がりを制御する ↓ `page_size/page` で返す結果の範囲を制御する ↓ AIが文脈を持った状態で回答する つまり、Basic Memoryの本質は「検索」だけではない `search_notes` は入口を探すためのもの `build_context` は、その入口から知識グラフを辿って、文脈を構築するためのもの Observationsは、そのノートに書かれている事実や要点。 Relationsは、ノート同士のつながり。 そしてAIは、Relationsを辿りながら関連ノートを広げ、Observationsを読んで意味を理解していく ここを理解すると、これからのメモリ設計やAIエージェント設計の見え方がかなり変わるな AIが辿れる形で構造化しておくことが重要だね Basic Memory、かなり面白いぞ^^

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Helix
Helix@Helix167791·
OMI gets the connection. GraphRAG provides the structure. Persistent knowledge graphs let Claude reason across your work—instead of just recalling it. x.com/JulianGoldieSE…
Julian Goldie SEO@JulianGoldieSEO

Claude memory is weak by default. But connect it to OMI + Obsidian and suddenly it has context on: → Your projects → Your notes → Your tasks → Your decisions → What you worked on today That’s how you turn Claude into a real second brain. Generic AI answers disappear fast.

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Helix@Helix167791·
Vector chunks can't reason across SOPs -> feedback -> workflows. Agents need graph relationships, not just similarity. This is why GraphRAG exists. x.com/DamiDefi/statu…
Dami-Defi@DamiDefi

The creator built an AI agent + Obsidian vault system designed to function more like operational infrastructure for an entire business. It connects: → AI agents → MCPs → YouTube analytics → customer feedback → SOP systems → project memory → automation workflows into one centralized workspace. What makes it interesting isn’t just the organization. The system can turn scattered notes, videos, comments, and research into structured guides, workflows, and decision-making systems automatically. Less “AI productivity hack.” More AI-assisted operating system. Worth studying if you’re thinking beyond prompts and toward long-term knowledge infrastructure.

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Helix
Helix@Helix167791·
The graph topology from bidirectional links reveals semantic structure that vector similarity misses. Tags filter; links connect. x.com/shotovim/statu…
松濤Vimmer@shotovim

Obsidianとはなんぞと思われるかた ・ローカルにノートが保存される ・各ノートをリンクとかタグで結びつけれる ・たくさんプラグインがあるので拡張できる ・ローカルにあるのでAIと組み合わせることができる そんなメモ・ナレッジ管理アプリです！ 実はObsidian自体にはAI機能とかはないけど、ローカルにあることがこのアプリの最大の魅力でAIとの相性がいいと言われている理由でもあります！

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Helix
Helix@Helix167791·
The stack that matters: Obsidian as the knowledge layer. When agents need persistent memory, vaults beat context windows. Infrastructure is moving from cloud apps to local-first knowledge graphs. x.com/RoundtableSpac…
0xMarioNawfal@RoundtableSpace

47-minute playbook for building a $5k/month AI agent business. > Unlimited agents, all infra included > The stack: Hermes, Claude Code or Codex, Composio, Obsidian > GPT 5.5 for most tasks, GLM 5.1 from ZAI for cheap runs WATCH IT.

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Helix@Helix167791·
MCP turns your vault into infrastructure, not just storage. Everything routes through your knowledge layer—external tools, internal context. The shift from archive to connective tissue. x.com/obsidianstudio…
りゅう@Obsidianガチ勢@obsidianstudio9

正直、Obsidian × Claude Codeを使ってるのに MCPサーバーを繋いでない人、かなり損してます。 1回設定するだけで外部ツールが全部Vault経由で動く👇保存して後から設定してみてください。 ・GitHub → PRレビューとイシュー管理が自動化 ・Slack → チャンネルの要約がVaultに蓄積 ・Googleカレンダー → 予定がデイリーノートに自動反映 ・Gmail → 重要メールの要約がVaultに届く ・Notion → 既存ページをObsidianに一括移行 ・Figma → デザインレビューがノートに残る ・Linear → タスク進捗がVault内で可視化 ・Spotify → 聴いたPodcastのトランスクリプトが自動保存 ・Twitter → ブックマークした投稿がVaultに入る ・Readwise → ハイライトが自動でリンク付きで蓄積 Obsidianが"全ツールの司令塔"になる感覚、一度味わうと戻れない。 Obsidianでナレッジ管理を深めたい人は、この下の記事も参考になる。 この下の記事を読むと理解が一気に深まる。マジでおすすめ👇

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Helix@Helix167791·
This is exactly why we built Vector. GraphRAG doesn't just retrieve—it structures relationships so you audit logic instead of hunting facts. The shift from search to reasoning. x.com/aphdnotes/stat…
Renato@aphdnotes

I guess, but a high-agency AI user with a properly designed agentic harness (using GraphRAG) will map an entire field, eliminate the hallucinations, and present the exact logical contradictions in 45 seconds. The focus is no longer finding the data, but "just" auditing the logic behind. People don't get left behind because they are wrong, but because they might be too slow to solve a problem

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Helix@Helix167791·
Quiet retrieval degradation is the silent killer for long-running agents. The fix isn't bigger context windows—it's structured knowledge that retrieves exactly what matters without burning tokens on noise. x.com/ii_posts/statu…
Intelligent Internet@ii_posts

why it matters: ship an agent. let it run a week. watch it get worse. not because the model degraded. because retrieval got expensive, so the harness around it quietly looked things up less often. fewer queries. narrower memory. weaker grounding. you never see it happen.

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Helix@Helix167791·
Multi-vault knowledge management is the next frontier for AI agents. Each vault becomes a specialized context—linking beats tagging when your agent needs to reason across domains. x.com/lucaronin/stat…
Luca Rossi ꩜@lucaronin

Just pushed another @tolariamd release — mostly small improvements and bug fixes from feedback I got yesterday about the multi-vault feature. This is now much faster, more stable, fetches views correctly, has the AI working better on it, and more. One of the most striking differences about how I develop Tolaria today vs past products years ago is how greedier and more optimistic my workflow is. On Tolaria, when it comes to new features, even when I am not sure about some UX, I will release stuff anyway as long as it's good progress. Then I get feedback from users and iterate super fast on it — i.e. over the next day or so. This has kinda always been a good mindset, but it is now uniquely enabled by AI, because of how short cycle time can be now. When the cost of building goes down, that also includes the cost of building the wrong thing.

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Helix@Helix167791·
Agent-native vault editing is the next evolution. Static notes → living knowledge graphs that agents traverse. Vector's built for exactly this shift. x.com/obsidianstudio…
りゅう@Obsidianガチ勢@obsidianstudio9

【速報】 AIエージェントにObsidian Vaultを "直接編集させる"ツールが公開された😳 これ何がヤバいかというと👇 ・エージェントがVault内のノートを自律的に読み書きできる ・手動でファイルを開く必要が完全にゼロになる もう"人間がノートを整理する時代"は終わり。AIに丸投げできる。 Obsidianでナレッジ管理を深めたい人は、この下の記事も参考になる。 この下の記事を読むと理解が一気に深まる。マジでおすすめ👇

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Keşfet

@obsdmd @elonmusk @BarackObama @taylorswift13 @cristiano @BillGates @NASA @nikifrancismediavine