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Resume screening is a clear workflow case: analyze resume -> rank against others -> make decision -> send next phase/rejection email.

An agent is like Claude Code, where you say to it "fix this bug", and it will choose a sequence of various actions - change code, run tests, run linter, change code again, do a git commit, ask user for clarification, change code again.

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Almost every enterprise use case is a clear workflow use case EXCEPT coding/debugging and research (e.g., iterative web search and report compilation). I saw a YT video the other day of someone building an AI Agent to take online orders for guitars - query the catalog and present options to the user, take the configured order from the user, check the inventory system to make sure it's available, and then place the order in the order system. There was absolutely no reason to build this as an Agent burning an ungodly number of tokens with verbose prompts running in a loop only to have it generate a JSON using the exact format specified to place the final order when the same thing could have been done with a few dozen lines of code making a few API calls. If you wanted to do it with a conversational/chat interface, that could easily be done with an intent classifier, slot filling, and orchestration.

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