OpenAI Agents API

I launched Epho a few weeks ago as an API like this but for all harnesses: https://epho.io

I built it primarily for ourselves: we are building an AI data engineer, and we need a way to run many of them in parallel securely. An API for this seemed like the most obvious path forward. It makes it trivial to bring agentic capabilities into any product surface without having to deal with sandboxes, reliability issues, compatibility problems, and more.

I think it also makes sense from OpenAI's perspective to do this, but also we did find ourselves needing to change models and harnesses quite a bit, which is why I think this needs to be a layer of its own above the labs. It also needs to be a layer above the sandboxes, since many of them are quite brittle.

Overall, I expect a lot of the agent implementations to move in this direction. I think this is a lot saner for engineers to implement and maintain, and it makes it trivial to build agentic stuff into products.

100% every professional developer at some point should build its own harness as daily driver

A lot of what a custom harness does isn't necessarily interacting with a model, it's the framework around it. Part of harness engineering is figuring out what can be done deterministically to avoid calling an LLM. A generational jump doesn't obsolete those areas, it just means you get the right answer (maybe) faster and easier when you do call the model.

There's a difference between their harness and your harness. The latter can be tuned to your preferences, while the former cannot. A custom harness can do everything that a packaged harness cannot. Good luck getting Claude Code to coordinate with multiple model providers or deeply integrate with your environment.

The point you're making is to be a consumer, which admittedly, is probably best for most people, but it's not going to satisfy the hacker. Normies aren't building custom harnesses, so your argument is DOA for the target demographic.

Also, vendor lock-in. No thanks.

I've commented about this before, I think many LLM based apps nowadays are at risk of being replaced by a product straight from the labs once they prove to be successful.

We've seen this pattern with Apple making their own version of an app that was previously popular on the app store.

The labs are in a perfect position to do this - they have a bunch of data on what's being used and they have direct access to their own models/compute. If an external service is popular, it's relatively trivial for them to estimate how much additional profit they're leaving on the table.

If the usecase isn't far from their core business (and things like this absolutely aren't), with their size, why wouldn't they eat other people's lunches?

Sorry, I didn’t mean to imply that what you’re doing is wrong, although re-reading my own comment sounds like so.

The capabilities of a model unlocks certain harness behaviour, and in its terms might be beneficial to automate more of your x, y, z.

I guess computer use would be an example I was thinking about. Certain models are not as good as some current models (Astra/Fable) in understanding through screenshots, or going through some hoops in some environments. As models evolve, they unlock new capabilities, that you either have to keep implementing in your harness, or using an existing one. I’m pro-using existing just because it doesn’t make sense for my org to support another dev tool internally, when there is heavy better development happening by people who focus on that.

The reason why i said cc-derivative, as far as I can see, cc was the one that convinced people “it might be a good idea to dev this way”. Sure you had some lesser known harnesses around, but a year+ ago, nobody really cared.

I don’t think, at least as of now, anything is really much of a lock in. We switch out between cc/codex/cursor and it takes trivial amount of time to set stuff up, depended on how your dev loop goes.

Again, it really depends on one’s conviction of “how fast things will develop from now on”. I personally think stuff will keep changing very fast. In a year what we think of harnesses will be different. Investing in custom tooling might be bad, as that is basically a lock-in. But again, I don’t know the future, but that’s my bet. Hovering around the edges and using what others battle test is an easy way out right now.

Also in some larger orgs, there is more friction in model choices. So you slowly start losing the benefits of model-swapping. Obviously different for personal projects.