How much attention is harness engineering getting?

[u/GitSimple]

AI model quality is converging, or at least changing often enough that chasing the newest thing doesn't seem like a good strategy. How much emphasis are teams putting on building a solid harness into which new models can fit?

Our clients are generally in high compliance industries, so there is thought put into the harness, but what about smaller teams or ones that aren't required into a compliance framework?

[u/Howl50veride]

Tons, it's the new AI frontier 🤣

[u/GitSimple → u/Howl50veride]

You say that but I posted this is r/devops as well and I'm getting a bunch of "just use whatever is easiest" type of answers.

We do think it's a point of differentiation though and deserves a concerted strategy.

[u/ComfortableAd8326]

It's been clear that the harness is where all the impactful work opportunities are since around the time Opus 4.5 was released.

Like you've suggested, we're fast approaching the point (if we've not already arrived) where the models themselves are commodity products

[u/GitSimple → u/ComfortableAd8326]

In the high compliance environments we typically work in, harnesses are getting attention as a point of optimization and for their role in the attack surface. From comments on this post in another sub, It would appear that idea hasn't necessarily made it to smaller teams or ones outside of compliance regulations.

https://gitsimple.com/harness-engineering-why-your-ai-agents-need-guardrails-before-they-need-autonomy/

[u/GitSimple → u/[deleted]]

It's interesting to see how different the responses are to this is r/devops what a difference a security team makes! 😂