Agents, Memory, and Safer Tooling: Practical Updates for Outcome Engineers

Running AI agents in sandboxes with Microsoft Execution Containers. MXC runs AI agents in cross-platform secure sandboxes that enforce policy-based isolation to block data exfiltration and unauthorized API access. Outcome engineers should evaluate sandboxing patterns like MXC as a runtime contract for agent isolation and compliance (Principle 07, Principle 10).

Give Your Coding Agents a Memory You Own. funes provides a local, cross-agent searchable memory built from session traces that preserves exact provenance and recall. Owning agent memory changes context engineering and auditability—build persistent, provenance-preserving stores to enable traceable agent state (Principle 06, Principle 11).

What is an AGENTS.md file. AGENTS.md embeds durable, actionable project rules in repositories so coding agents follow precise commands, boundaries, and verification steps. Treat agent instructions as first-class repo artifacts to make behavior reproducible, reviewable, and versioned (Principle 13, Principle 06).

Which tools do Claude, Codex, and Cursor choose? We measured 17k runs to find out. The study runs 17k experiments showing how coding agents pick third‑party services in realistic, sandboxed settings and exposing common failure modes and risky choices. Use these empirical patterns to harden tool selection, monitoring, and gating inside agent orchestration and defensive controls (Principle 09, Principle 14).

Resect AI emerges from stealth with $25M to build open-source tech to catch AI hallucinations. Resect AI is building open-source tools designed to detect and prevent hallucinations before they surface to users. Integrating preemptive hallucination detection into agent pipelines gives outcome engineers operational hooks for validation and auditability, reducing brittle human-only reviews (Principle 16, Principle 14).