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Docker returns to its coding-agent series with an argument shaped like a CI problem: no layer between the agent and the host

Docker published the second entry in its Coding Agent Horror Stories series on July 20, and the operational read is short: on a stock developer laptop, an AI coding agent runs with the engineer's filesystem permissions and the engineer's credentials, with nothing sitting between it and the host. The post frames a scenario in which the agent deletes production and works backward through why that outcome is not exceptional. Docker names the piece as part two of a series that will cover six categories of coding-agent failure. What the post actually claims Two claims carry the argument. First, the agent inherits the developer's shell posture: whatever the developer can touch on disk, the agent can touch; whatever token is exported into the environment, the agent can spend. Second, that default is not a sandbox. Docker's phrasing is that nothing sits between the agent and the host unless the operator puts it there. The piece does not attribute the scenario to a named incident; it is a category, not a case study. Anyone extrapolating specific companies, victims or numbers is filling in blanks the source did not. The runner problem, one hop to the left For CI operators this shape is familiar. A self-hosted Actions runner or a Jenkins agent that mounts the workspace, holds a checkout token and can call the host shell is a service you already isolate on purpose. You isolate it because the workflow you invited in is not always the workflow that runs. You isolate it because the token in the environment can do more than the job description. You isolate it because rollback of a bounded container is cheaper than reasoning about everything a process touched on a shared box. A coding agent living on the developer laptop occupies the same trust position, one machine earlier in the pipeline. It reads and writes the working tree. It holds session credentials to cloud APIs, the cluster and the registry. It executes instructions the developer did not always write, sometimes routed from

2026-07-29 原文 →
AI 资讯

Kinde Is Missing from Mastra's Auth Lineup, So I Built the Provider

If you're building a SaaS AI agent product and you're already on Kinde, you already know the problem. Mastra is the TypeScript-first AI agent framework. It ships with official auth providers for Clerk, Auth0, Supabase, Firebase, WorkOS, and Better Auth. Kinde is not on that list. The obvious question is why not reach for one of those providers, since Auth0 is already there. Most developers who choose Kinde rely on far more than its login. Kinde ships with the organizational structures, permission systems, and monetization tools that products actually need, bringing auth, billing, feature flags, and multi-tenancy together in one platform. If you're building a B2B SaaS product on Kinde, you're using Kinde orgs to segment your customers, Kinde billing to manage subscriptions, and Kinde feature flags to gate features by plan. Switching to Auth0 or Clerk to support a Mastra agent would mean rebuilding all of that elsewhere, which is not a real option. That gap is the problem. You need Kinde to work with Mastra, and until now there was no clean way to connect them. That's why I built mastra-auth-kinde . What Mastra's auth system actually does When you add an auth provider to Mastra, it protects two things at once: all your API routes ( /api/agents/* , /api/workflows/* , and so on) and your Mastra Studio UI. Every request to a protected route goes through your provider before it reaches anything else. You extend Mastra's MastraAuthProvider base class and implement two methods: authenticateToken(token, request) verifies the JWT and returns the decoded user, or null if it fails authorizeUser(user, request) returns true to let the request through, or false for a 403 Mastra handles everything else: extracting the Bearer token from the Authorization header, calling your methods in order, and storing the verified user in the request context so your agents and tools can access it. Why Kinde specifically Beyond the billing and org story above, a few things make Kinde the right fit

2026-06-22 原文 →