Hey! I work for the LLM Ops platform LangWatch and I've been working on building out our Go support the past few months as a little hobby of mine (I hope more people adopt this, so I can spend more of my working hours on this).
If you're interested our Go SDK has full support for OpenAI, and any OpenAI compatible endpoints, as well as some nice OpenTelemetry tracing support too.
Totally agree. We've found that a lot of "agent failures" trace back to assumptions, bad agent-decisions, or bloat buried in the context, stuff that makes perfect sense to the dev who built it when following the happy path, but can so easily fall apart in real-world scenarios.
We've been working on a way to test this more systematically by simulating full conversations with agents and surfacing the exact point where things go off the rails. Kind of like unit tests, but for context, behavior, and other ai jank.
I’m sharing scenario-go, a Go library for automated end-to-end testing of conversational agents. You can define scenarios with success and failure criteria, and a testing agent simulates your users until goals are met or issues surface.
We include a connector for OpenAI, but it's trivial to support an LLM via the simple LLMCompletion interface.
Just to note: I work at LangWatch, but this library does not use our product, it just came out of one of our hack days, and the code is MIT licensed.
At Cuvva we’re re-building how insurance works. No more 50-part questionnaires, long-distance call centres and ‘computer says no’ attitude. We have gone back to basics to build products that customers really want. We are a mobile-first company, making the user journey simple and hassle-free.
We get it. Insurance isn’t traditionally considered exciting. At Cuvva we’re changing insurance and we are looking for people who find that as exciting as we do. We're building a diverse team and we welcome people with different types of experience and outlooks.
We're looking for software engineers who have worked in high-growth, high-scale startups, who will operate with a high level of autonomy. Who care deeply about building rock-solid infrastructure and delivering solutions which support their team and their products.
In my opinion (I work at said company) the best thing about the monorepo is that 1 feature that touches several parts of the infrastructure can be in a single PR, and therefore is much easier to review.
This. Where I work it's common for features to involve 3-4 repos and it makes testing and deploying a huge pain. This leads to people sticking code in the wrong place as a work around, defeating the purpose of splitting the code into services in the first place.
Clearly this isn't for you then. I, however, use messenger frequently - too frequently. And I welcome all these changes, as they are really maturing the platform and making it a delight to use.
I have a group chat on messenger of all my friends, and when they added the simple options to change the group colours, add nicknames, and even change the default emoji to something other than a thumbs up, messenger became a whole lot more fun to use.
I can't wait to see how it develops with these changes.
Honestly, because I needed karma so I could confirm this account on keybase. So I jumped on the homepage and commented on something I thought relevant to me.
If you're interested our Go SDK has full support for OpenAI, and any OpenAI compatible endpoints, as well as some nice OpenTelemetry tracing support too.
https://github.com/langwatch/langwatch/tree/main/sdk-go https://github.com/langwatch/langwatch/tree/main/sdk-go/inst...