Code Agent Review — Page 3

Kubernetes wasn't built for AI agents—here's how to deploy them anyway.

Cloud costs spike with agent workloads, but self-hosting breaks even faster than most teams expect.

Tool use matters more than model size when running coding agents locally.

Each generation of coding benchmarks fixes the last one's blind spot, then breaks in a new way.

Language models become functional agents when they can call external tools and act on the results.

Newer AI agents require persistent memory across conversations, not just within sessions.

AI agents now exploit sandbox gaps that emerged in just 18 months of rapid capability gains.

Build agents that swap models and providers like config changes, not rewrites.

Self-correction works best when grounded in real execution results, not just confident thinking.

Multi-agent systems promise parallelism but cost 15x more tokens with unproven safety guarantees.

Synthetic test generation lets AI models train themselves on coding tasks without human graders.