Long-running agent sessions usually fail the same way: context keeps growing, latency spikes, costs blow up, and answer quality gets worse. That is rarely a model-quality issue. It is almost always missing context governance. ...
When OpenAI API calls start timing out in production, the real problem is usually not “OpenAI is down.” The real problem is you don’t know which hop is failing: DNS, TLS handshake, proxy path, or your own connection pool. ...
Production streaming fails in two predictable ways: users wait while the stream silently drops, and your logs say “timeout” without telling you where it actually broke. This guide gives you a practical Go pattern for OpenAI Responses API streaming with strict timeout boundaries, safe retries, and useful telemetry. ...
If you use AI as a chatbot only, these tools feel similar. In real engineering workflows, they behave very differently. My conclusion first: use Codex for repo-native coding changes, Claude for deep reasoning and long-form planning, and OpenAI CLI for standardized automation pipelines. ...