GPT-5.5 prompting guide

The buried detail here is the status-update pattern itself: by having the model emit a user-visible message before each tool call rather than after, developers can mask latency that would otherwise feel like a frozen interface. This is less about capability and more about engineering perception in agentic workflows.

GPT-5.5 is arriving at a moment when the practical infrastructure around large models is under real strain. The RAM shortage story from The Verge in mid-April noted that DRAM suppliers will cover only 60% of global demand by end-2027, and agentic, multi-step workloads of exactly the kind this guide describes are among the heaviest consumers of memory bandwidth. Better prompting patterns help developers squeeze more usable performance from constrained deployments, which makes guidance like this more consequential than it might appear in a looser supply environment. The related coverage from that period is otherwise focused on hardware and policy, not model-level technique, so this story sits in its own lane.

Watch whether competing providers, particularly Anthropic, publish equivalent agentic-workflow guidance within the next 60 days. If they do, this pattern is becoming a de facto standard; if not, it may reflect a genuine architectural difference in how the two companies expect developers to build on their APIs.