Agentic Engineering Patterns

>It feels a little tricky to square these up sometimes.

I don’t think you have to square them because those sentiments are coming from different people. They are also coming from people at different points along the adoption curve. If you are struggling and you see other people struggling at the beginning of the adoption curve it can be quite difficult difficult to understand someone who is further along and does not appear to be struggling.

I think a lot of folks who have struggled with these tools do so because both critics and boosters create unrealistic expectations.

What I recommend is you keep trying. This is a new skill set. It is a different skill set. Which other skills that existed in the past remain necessary is not known.

Worse yet, the problems are going to be real.

There's a lifecycle to these hype runs, even when the thing behind the hype is plenty real. We're still in the phase where if you criticize AI you get told you don't "get it", so people are holding back some of their criticisms because they won't be received well. In this case, I'm not talking about the criticisms of the people standing back and taking shots at the tech, I'm talking about the criticisms of those heavily using it.

At some point, the dam will break, and it will become acceptable, if not fashionable, to talk about the real problems the tech is creating. Right now there is only the tiniest trickle from the folk who just don't care how they are perceived, but once it becomes acceptable it'll be a flood.

And there are going to be problems that come from using vast quantities of AI on a code base, especially of the form "created so much code my AI couldn't handle it anymore and neither could any of the humans involved". There's going to need to be a discussion on techniques on how to handle this. There's going to be characteristic problems and solutions.

The thing that really makes this hard to track though is the tech itself is moving faster than this cycle does. But if the exponential curve turns into a sigmoid curve, we're going to start hearing about these problems. If we just get a few more incremental improvements on what we have now, there absolutely are going to be patterns as to how to use AI and some very strong anti-patterns that we'll discover, and there will be consultants, and little companies that will specialize in fixing the problems, and people who propose buzzword solutions and give lots of talks about it and attract an annoying following online, and all that jazz. Unless AI proceeds to the point that it can completely replace a senior engineer from top to bottom, this is inevitable.

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> And there are going to be problems that come from using vast quantities of AI on a code base, especially of the form "created so much code my AI couldn't handle it anymore and neither could any of the humans involved". There's going to need to be a discussion on techniques on how to handle this. There's going to be characteristic problems and solutions.

That's essentially the thing we are calling "cognitive debt".

I have a chapter with one small thing to help address that here - https://simonwillison.net/guides/agentic-engineering-pattern... - but it's a much bigger topic and will require extensive exploration by the whole industry to figure out.

> I think most of these writeups are packaging familiar engineering moves into LLM-shaped language.

They are, and that's deliberate.

Something I'm finding neat about working with coding agents is that most of the techniques that get better results out of agents are techniques that work for larger teams of humans too.

If you've already got great habits around automated testing, documentation, linting, red/green TDD, code review, clean atomic commits etc - you're going to get much better results out of coding agents as well.

My devious plan here is to teach people good software engineering while tricking them into thinking the book is about AI.