<span class="vcard">/u/AdditionalWeb107</span>
/u/AdditionalWeb107

Moving the low-level plumbing work in AI to infrastructure

The agent frameworks we have today (like LangChain, LLamaIndex, etc) are helpful but implement a lot of the core infrastructure patterns in the framework itself – mixing concerns between the low-level work and business logic of agents. I think this bec…

Moving the low-level plumbing work in AI to infrastructure

The agent frameworks we have today (like LangChain, LLamaIndex, etc) are helpful but implement a lot of the core infrastructure patterns in the framework itself – mixing concerns between the low-level work and business logic of agents. I think this bec…

ArchGW 0.2.8 is out 🚀 – unifying repeat "low-level" functionality via an AI-native proxy

I am thrilled about our latest release: Arch 0.2.8. Initially we handled calls made to LLMs – to unify key management, track spending consistently, improve resiliency and improve model choice – but we just added support for an ingress listener (o…

I think small LLMs are underrated and overlooked. Exceptional speed without compromising performance.

In the race for ever-larger models, its easy to forget just how powerful small LLMs can be—blazingly fast, resource-efficient, and surprisingly capable. I am biased, because my team builds these small open source LLMs – but the potential to creat…

I built an LMM (logic mental model) for building AI apps.

I naturally post about models (have a bunch on HF) over tools in this sub, but I also use tools and LLMs to develop agentic systems, and find that there is this mad rush to use the latest agentic framework as if that's going to magically accelerate…