In other words, “Agentic engineering” feels like the response of engineers who use AI to write code, but want to maintain the skill distinction to the pure “vibe coders.”
If there's such. The border is vague at most.
There're "known unknowns" and "unknown unknowns" when working with systems. In this terms, there's no distinction between vibe-coding and agentic engineering.
Software engineering is the application of an empirical, scientific approach to finding efficient, economic solutions to practical problems in software.
As for the practitioner, he said that they: …must become experts at learning and experts at managing complexity
For the learning part, that means Iteration
Feedback
Incrementalism
Experimentation
Empiricism
For the complexity part, that means Modularity
Cohesion
Separation of Concerns
Abstraction
Loose Coupling
Anyone that advocates for agentic engineering has been very silent about the above points. Even for the very first definition, it seems that we’re no longer seeking to solve practical problems, nor proposing economical solutions for them.Using coding agents to responsibly and productively build good software benefits from all of those characteristics.
The challenge I'm interested in is how we professionalize the way we use these new tools. I want to figure out how to use them to write better software than we were writing without them.
See my definition of "good code" in a subsequent chapter: https://simonwillison.net/guides/agentic-engineering-pattern...
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.
You're not the engineer anymore, but you're still responsible for creating software. Why drop the most important word and keep the ego stroking word?
At the very least, agentic systems must have distinct coders and verifiers. Context rot is very real, and I've found with some modern prompting systems there are severe alignment failures (literally 2023 LLM RL levels of stubbing out and hacking tests just to get tests "passing"). It's kind of absurd.
I would rather an agent make 10 TODO's and loudly fail than make 1 silent fallback or sloppy architectural decision or outright malicious compliance.
This wouldn't work in a real company because this would devolve into office politics and drudgery. But agents don't have feelings and are excellent at synthesis. Have them generate their own (TEMPORARY) data.
Agents can be spun off to do so many experiments and create so many artifacts, and furthermore, a lot more (TEMPORARY) artifacts is ripe for analysis by other agents. Is the theory, anyways.
The effectively platonic view that we just need to keep specifying more and more formal requirements is not sustainable. Many top labs are already doing code review with AI because of code output.
What makes a human a suitable source of accountability and an AI agent an unsuitable one? What is the quantity and quality of value in a "throat to choke", a human soul who is dependent on employment for income and social stature and is motivated to keep things from going wrong by threat of termination?
From Kai Lentit’s most recent video: https://youtu.be/xE9W9Ghe4Jk?t=260
Agents are coming for the other engineering disciplines as well.
Kind of like these HTML demos, but more compact and card-like. Exciting the possibilities for responsive human-readable information display and wiki-like natural language exploration as models get cheaper.
Spot on.
"Prompt engineering" is a relic of the early hypothesis that how you talk to the LLM is gonna matter a lot.
Agentic coding highlights letting the model directly code on your codebase. I guess its the next level forward.
I keep seeing agentic engineering more even in job postings, so I think this will be the terminology used to describe someone building software whilst letting an AI model output the code. Its not to be confused with vibe coding which is possible with coding agents.
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..
But to your point I think this year it's quite likely we'll see at least 1 or 2 major AI-related security incidents..
LLMs are for sure useful and a productivity boost but generating 99% of your code with it is way overdoing it.
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 just bulked up that section by adding a couple of extra sentences, since you're right that I didn't actually define "agent" there clearly: https://simonwillison.net/guides/agentic-engineering-pattern...
Now that we have software that can write working code ...
While there are other points made which are worth consideration on their own, it is difficult to take this post seriously given the above.This is not an attack on the tech as junk or useless, but rather that it is a useful tech within its limits being promoted as snake oil which can only end in disaster.
If you believe coding agents produce working code, why was the decision below made?
Amazon orders 90-day reset after code mishaps cause
millions of lost orders[0]
0 - https://www.businessinsider.com/amazon-tightens-code-control...