Agent Infrastructure: Sandboxes, Routing, and Ship‑Ready Agents

Port releases Port AI Builder vibe coding platform for dev and platform teams. Port ships an agentic SDLC for teams that composes natural‑language workflows with built‑in human approvals and governance. Outcome engineers should treat this as a template for embedding gates and audit points into delivery lanes — practical Orchestration and Gate design (Principle 09, 15).

Perplexity launches SPACE sandbox to make its AI agents secure and powerful. Perplexity opens a secure runtime that lets agents run at full capability while isolating risk and attack surface. Build your agent islands with the same isolation and capability tradeoffs to protect production services and enable safe experimentation (Principle 07, 14).

Model Routing Is Simple. Until It Isn’t.. IBM Research shows model routing requires multi‑dimensional optimization — caching, infra, and governance upend naive heuristics. If you own outcomes, design routing as an engineering problem across cost, latency, and provenance, not just a one‑line selector (Principle 06, 09, 11).

What building Shippy taught us about building agents. The Shippy case study documents trustworthy agents through versioned skills, deterministic tools, sandboxed hosting, and live‑data validation. Use it as a concrete blueprint for production agent architecture and outcome validation pipelines (Principle 07, 06, 16).

The Next Challenge for Coding Agents. The piece argues coding agents must graduate to owning production debugging and maintenance by surfacing huge logs and product‑specific context. Outcome engineers must build observability, context‑engineering pipelines, and clear human‑agent handoffs so agents can reliably close the loop in production (Principle 03, 06).