Grab's security team built Palana, a Kubernetes-native secure execution platform, to run autonomous AI agents safely. Unlike deterministic software, model-driven agents exhibit unpredictable tool-use, code-writing, and prompt injection risks. Palana contains these threats at the infrastructure level using isolated namespaces, out-of-process control planes, and proxy-mediated, Vault-backed secrets. By Patrick Farry

A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks and expanding productivity across roles.

Safe agent spend from the terminal Discussion | Link

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I 've been using Cursor on non-trivial repos and kept hitting the same issue: the agent finds a file but misses routes, shared modules, and tests that should run after a change. I built FlowIndex — a local CLI + MCP server that scans a repo and builds a behavior graph in SQLite (entrypoints, imports/calls, tests, git co-change). No embeddings, no SaaS, no LLM calls in the index itself. Setup: pip install "flowindex[mcp]" In your project: flowindex init flowindex scan Add to ~/.cursor/mcp.json (use your repo' s absolute path for cwd ) : { "mcpServers" : { "flowindex" : { "command" : "flowindex" , "args" : [ "mcp" ] , "cwd" : "/absolute/path/to/your/repo" } } } 4. Restart Cursor — you get tools like get_change_impact, suggest_tests, make_context_pack, explain_entrypoint, get_repo_overview. Example workflow: before editing payments/ledger code, ask the agent to use make_context_pack or get_change_impact on that file — it pulls from the local graph, not a generic file search. Honest limits: static analysis + git heuristics only. Call paths resolve via imports but aren 't compiler-grade. TS/JS is heuristic. Documented in the README. MIT · pip install flowindex · https://github.com/adu3110/flowIndex Curious if others use MCP for repo context and what tools you wish existed. Happy to fix setup issues if anyone tries it.

Exposing your app to an AI agent over MCP is basically handing someone a master keyring and trusting them to only open the doors they're supposed to. That trust is a bug waiting to happen. This week I wired up a batch of MCP tools over a multi-tenant Laravel app, and the whole exercise was really about one question: how do I let an agent drive the app without letting it drive someone else's data? Here's the thing about MCP tools — each one is an endpoint. An agent calls list_events , publish_event , check_in_participant , and your server runs code on the caller's behalf. The moment you have more than one tenant, every single tool needs to answer two questions before it does anything: are you allowed to do this , and are you allowed to do it *here *. Authorization and scope. Skip either and you've built a confused deputy. The trap: ambient scope doesn't exist under token auth In a normal web request, multi-tenancy is comfortable. You've got a logged-in user, a global scope on the model that quietly appends where organization_id = ? , and you mostly forget it's there. Everything Just Works because there's an ambient "current organization" sitting in the session. MCP tools don't have that. The caller authenticates with a token, there's no session, no middleware stack that set up a current-tenant context. If you lean on a global OrganizationScope that reads "the current org" from somewhere, it reads nothing — and a query you assumed was fenced returns every tenant's rows. That's the kind of bug that doesn't throw an error; it just silently leaks. So the rule I settled on: under token auth, never rely on ambient scope. Filter explicitly, every time, in one place. That "one place" is a small trait every event-scoped tool pulls in: trait ResolvesOrgEvents { protected function resolveOrgEvent ( Authenticatable $user , string $uuid ): ?Event { if ( empty ( $user -> organization_id )) { return null ; } return Event :: query () -> withOrganization ( $user -> organization_id )