[vidarh]

Do you use an agent harness to have it review code for you before you do?

If not, you don't know how to use it efficiently.

A large part of using AI efficiently is to significantly lower that review burden by having it do far more of the verification and cleanup itself before you even look at it.

[docmars]

This is correct, but part of the issue is that it significantly increases token usage costs. Some companies are doing:

- PRD and spec fulfillment review

- code review + correction loops

- security review + corrections

- addl. test coverage and tidying

- addl. type checks and tidying

- addl. lint checks and tidying

- maybe more I haven't listed

And these are run after each commit, so you can only imagine the costs per engineer doing this 10, 20, 50+ times per day depending on how much work they're knocking out.

[vidarh]

Sure, it adds tokens. I've burnt 200 million tokens today on a single project.

The question is what your time is worth for the company, and which tasks costs less to have an agent automate than having you do.

[docmars]

I think if you were to scale that kind of usage across a reasonable team size, costs would start to add up fast — and possibly beyond the cost of paying another engineer every year, especially if a lot of your teammates are new to AI, or aren't using it efficiently. Of course, it all depends on the appetite of the company.

The other constraint is, for those who are being laid off (maybe because of cost reduction to support an AI budget for a smaller team to use), engineers wanting to expand their skill set and practice these levels of usage + efficiency are effectively unable to with their own funding, making it more difficult to find employment as expectations heighten.

Prior to AI entering the fray, software development was largely free for everyone, allowing anyone with enough time and motivation to build the skills towards gainful employment. As AI becomes more prevalent and expectations around how it's used become higher, fewer and fewer applicants will be able to claim they have the experience necessary because it was out of reach due to costs.

[riskable]

> Do you use an agent harness to have it review code for you before you do?

Right now you need to be Uncle Moneybags to do this in your personal life.

If you're lucky, your employer is footing the bill but otherwise... Ugh. It's like converting your app running perfectly fine on a cheap VPS to AWS Lambda. In theory, it's fine but in reality the next bill you get could make you faint.

[vidarh]

It's down to how much you value your time. If your value your time low enough, it doesn't pay to make AI take over. If you value it high enough, it does.

[overgard]

I have it run tests and every few days I ask it to do a code quality analysis check on the codebase.

I'm unconvinced AI reviewing AI is the answer here, because all LLMs have the same flaws. To me, the harness/guard rails for AI should be different technologies that work differently and in a more formal sense. IE, static code analysis, linters, tests, etc.

(Linting has actually been, by far, the BEST code quality enforcers for the agents I've run so far, and it's a lot cheaper and more configurable than running more agents.)

[anukin]

What sort of agent harness setup do you recommend?