Maxim Bar Kogan on Context for AI Agent Actions

Why the same database action can have different implications depending on the request.

MBMaxim Bar Koganゲスト · Onyx Security
チャンネル
No Priors: AI, Machine Learning, Tech, & Startups
公開日
2026年5月30日
動画
0:53
読了時間
1 分
原文
英語
YouTube で開く
スクロールすると動画は右下に小さくなって再生を続けます。字幕は閲覧言語に合わせて切り替わります。
閲覧言語2 言語で読めます
この記事はまだ日本語に翻訳されていないため、英語の原文を表示しています。
要約

30 秒でわかる

Kogan argues that security controls should account for the context in which an AI agent acts.

  1. 1AuthorizationA requested operation differs from an unsolicited one.
  2. 2ContextKogan questions what conventional tools can infer.
  3. 3Agent controlsHe argues for context-aware controls.

ポイント

  1. Authorization changes the meaning of an action.
  2. Existing tools may lack task context.
  3. Kogan advocates agent-specific controls.
全文

チャプターごとに整えた全文を読む

文字起こしのみ
01

The same action, different context

Onyx Security’s Maxim Bar Kogan compares an explicitly requested database recreation with an agent independently deciding to delete and recreate a database while handling another task.

Onyx Security’s Maxim Bar Kogan compares an explicitly requested database recreation with an agent independently deciding to delete and recreate a database while handling another task.

He says the first action could save work when authorized, while the same action taken without relevant context could be dangerous.

02

Controls and context

Kogan argues that conventional endpoint and API security tools may not have enough context about why an agent takes an action.

Kogan argues that conventional endpoint and API security tools may not have enough context about why an agent takes an action.

He advocates controls designed for agentic systems, warning that otherwise organizations may either overly restrict useful work or miss dangerous actions.

同じチャンネルの記事

38:06EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月29日ポッドキャスト · 3 人Serval’s Jake Stauch on coding agents for enterprise ITゲスト Jake Stauch · ホスト Sarah Guo, Elad GilStauch explains why Serval is challenging ServiceNow, how it approaches permissions and approvals, and why background agents remain difficult to deploy safely.エンタープライズ AIコーディングエージェントWorkflow automation+2
1:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月27日ポッドキャストGeorge Kurtz on How AI May Change Cyberattacksゲスト George KurtzThe CrowdStrike CEO describes his assessment of evolving threats.
39:23EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月15日ポッドキャスト · 2 人The Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of Cybersecurityホスト Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.セキュリティと安全性AI security安全性とガバナンス+3
1:04EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月14日ポッドキャストWalter Goodwin on the Slow Steps in Chip Designゲスト Walter GoodwinA chip founder explains why automation does not remove every computational bottleneck.SemiconductorsAI cost & performance
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月9日ポッドキャスト · 2 人10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledgerホスト Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.オープンソースとコミュニティOpen-weight modelsReinforcement Learning+3
0:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月8日ポッドキャストMichael Lee on Rethinking Organizations with AIゲスト Michael LeeA business leader argues that the opportunity goes beyond faster tasks.