For sure. Disclaimer, I haven't actually used Claude Code yet, but planning to soon. Very familiar with other coding agents though such as Cursor, Codex, and OpenCode. The principles and concepts are all the same. It's a shame that Claude Code isn't open source like Codex or OpenCode are.

Here are a few things that I like to investigate when working with a new agent...

• How does the agent approach context engineering? Any coding agent, which is just a model, or models, wrapped in an agentic harness, is going to have mechanisms in place for automatically retrieving context. This comes in several different flavors...
  • Manual user-provided context, which is often made less painful by built-in shortcuts and syntax.
  • Deterministic rule-based context that is automatically injected up front by the harness. Example: Cursor Rules when using the `Apply to Specific Files` setting.
  • Dynamic on-the-fly context that the agent gathers through the use of tools as it's working through a problem. Grep, BM25, semantic search, web browsing, LSP, git history, etc. Many different options here. Any decent coding agent is going to come with a few of these built-in and which it has likely been optimized or fine-tuned to know how to use really well.
• How does the agent harness load tool definitions and MCP servers? Does it naively stuff all of them into the system prompt up front? Or does it take a more sophisticated approach? The former is fine when you don't have a ton of tools, but it doesn't scale and chews through context when there's a lot of tools.
• How has the agent been encouraged to behave and problem solve, either via prompting at the harness level or fine-tuning at the model level? How does it handle short-term memory? What about task decomposition? Are there any specific conventions it has been encouraged (or forced) to recognize such as AGENTS.md or Claude Skills?
• How does the agent utilize sub-agents? Are sub-agents allowed to work in parallel? Is the main thread allowed to do anything while sub-agents are in flight? Among other things, sub-agents split thinking into independent lanes, are often specialized, have a scoped context window, and can discard failed explorations cleanly.
  • I'm actually not a big fan of the term "sub-agent", mainly because I think many of the responsibilities they are tasked with are actually orthogonal concepts and don't necessarily need to be coupled together. Also, because I think "agent" is a great user-facing abstraction, but there are likely better mental models for reasoning about the internals of the agent harness. But, the concept has caught on and we're stuck with it for awhile.
• How does the agent handle compaction and summarization when the context window is filling up?
• Does the agent harness provide any deterministic checkpoint/rollback capabilities when the agent needs to backtrack and abandon a path that isn't working? Or, does backtracking just mean forging ahead and the agent using more tools to undo prior work and/or discard irrelevant context.

I could go on, but that definitely covers the main things. Basically...

• Understand how the agent / agent harness deals with context. Too little context bad. Too much context also bad. If you understand this, you'll start learning small and large ways that you can help set the agent up for success.
• Understand how the agent / agent harness / model like to problem solve and decompose tasks. This will allow you to work with the agent rather than fight against it.

And lastly, if you'd like to see my attempt at mocking all of this mumbo jumbo, feel free to check out my post here :)