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The term feels broken when adhering to standard naming conventions, such as Mechanical Engineering or Electrical Engineering, where "Agentic Engineering" would logically refer to the engineering of agents
I’ve been using the term “agentic coding” more often, because I am always shy to claim that our field rises to the level of the engineers that build bridges and rockets. I’m happy to use “agentic engineering” however, and if Simon coins it, it just might stick. :) Thanks for sharing your best practices, Simon!
After three months of seeing what agentic engineering produces first-hand, I think there's going to be a pretty big correction. Not saying that AI doesn't have a place, and that models aren't getting better, but there is a seriously delusional state in this industry right now..
How is this different than Prompt Engineering?
Claude gave a spot on description a few months back,
The honest framing would be: “We finally have a reasoning module flexible enough to make the old agent architectures practical for general-purpose tasks.” But that doesn’t generate VC funding or Twitter engagement, so instead we get breathless announcements about “agentic AI” as if the concept just landed from space.
I don't think we should be making this distinction. We're still engaged in software engineering. This isn't a new discipline, it's a new technique. We're still using testing, requirements gathering, etc. to ensure we've produced the correct product and that the product is correct. Just with more automation.
I entirely agree that engineering practices still matter. It has been fascinating to watch how so many of the techniques associated with high-quality software engineering - automated tests and linting and clear documentation and CI and CD and cleanly factored code and so on - turn out to help coding agents produce better results as well.
I don't think we should be making this distinction. We're still engaged in software engineering. This isn't a new discipline, it's a new technique. We're still using testing, requirements gathering, etc. to ensure we've produced the correct product and that the product is correct. Just with more automation.
Software engineering is the application of an empirical, scientific approach to finding efficient, economic solutions to practical problems in software.
…must become experts at learning and experts at managing complexity
Iteration
Feedback
Incrementalism
Experimentation
Empiricism
Modularity
Cohesion
Separation of Concerns
Abstraction
Loose Coupling