The 10 Questions Every Team Actually Asks When Shipping AI-Assisted Development — From a Course That Has Seen 500+ Students Do It
Eleanor Berger and Isaac Flath, creators of the "Elite AI Assisted Coding" course with over 500 students, have distilled the questions that surface most reliably when engineering teams move from AI coding demos to real production workflows. The result is a practical top-ten list that skips benchmark discussion entirely and focuses on what actually causes teams to stall: why real projects feel much harder than demos, how to package context so an agent actually uses it, what distinguishes a task that's suitable for an agent from one that isn't, and how to tell when an agent session is drifting before it goes off the rails. The "context validation" technique they describe is particularly concrete — interrogate the agent with questions it could only answer correctly if it had genuinely loaded your materials, and write automated checks that verify the agent is following your documented conventions rather than pattern-matching on training data.
What makes this piece useful beyond its format is the data behind it. These aren't thought-experiment questions — they're the ones that 500+ students asked repeatedly when doing real work with real codebases. The sub-agent decomposition question (when to split a task across multiple agents versus keeping it in a single loop) is often the tipping point between basic assistant use and functional agentic architecture, and the course instructors offer the clearest practical guidance available on where that line actually sits. For teams onboarding developers to AI-assisted workflows, the tenth question — how to avoid creating a two-tier workforce — is worth the read on its own.