Entering the agent harness era

We’re quietly entering the agent harness era of AI, and it’s way more interesting than just throwing a bigger model at the problem. Things like: - Parallel tools and API calls - Hierarchical sub‑agents that own specific workflows - Procedural memory so your system actually “remembers” what it’s doing - Context compaction so prompts don’t become 200k-token fanfic - Visual graphs to debug and reason about flows are becoming the real performance frontier. The fun part is that when you get orchestration right, you can often ship a system where a cheaper, “weaker” base model outperforms SOTA weights in practice. Not on a leaderboard, but where it actually matters to you: - Lower latency - Fewer random failures in edge cases - A nicer “trust UX” for users, where they understand what’s going on and feel safe relying on it The stack is starting to look less like “call LLM, pray” and more like a serious runtime. The model is becoming a component. The orchestration is becoming the product.