ChatGPT

ChatGPT is still the default AI assistant for an enormous number of engineers, and the ecosystem advantage is real. If you’ve built a workflow around custom GPTs, integrations, or shared team prompts, the moat is meaningful.

Where it shines for DevOps

• First-draft IaC — generating an initial Terraform module, Ansible role, or Helm chart. The output is usually structurally sound, and any rough edges are easy to clean up.
• Quick Python or Bash one-liners — pasting “give me an awk that…” returns reliably correct output.
• Conceptual explanations — “explain why this PromQL is producing this shape” gets you a clear answer.
• Image input — paste a Grafana screenshot and ask “what does this trend suggest?”

Where to be careful

• The default tone is less cautious about destructive commands. Use a system prompt that explicitly requires safety flagging.
• For diagnostic sessions that span many turns and many context chunks (paste log → paste output → paste manifest), it’s slightly easier to lose continuity than with longer-context-optimized alternatives.

How to get the most out of it

• Create a Custom GPT or save a system prompt that anchors it as a “senior infrastructure engineer” with explicit safety constraints.
• Use the Bash Script Code Review Prompt and Prometheus Alert Rule Generator Prompt — both work very well here.
• Take advantage of image input for dashboards and screenshots, not just text.

Combine it with

Many engineers use ChatGPT for first drafts (fast generation), then move to Claude for production-sensitive review (cautious reading). Both subscriptions together still cost less than a single Stack Overflow Teams seat.

Pricing notes

Free tier has tighter model access. Plus at $20/mo unlocks the strongest models, image input, and higher rate limits — that’s the tier most engineers will want.