A developer has created a full LLM inference engine from scratch in C#/.NET, featuring native GGUF loading and an OpenAI-compatible API. This could be of interest to engineers looking for robust, low-level AI infrastructure solutions.
I've built a full LLM inference engine in C#/.NET 10. From scratch. Not a wrapper - native GGUF loading, BPE tokenizer, attention, KV-cache, SIMD-vectorized CPU kernels, CUDA GPU backend, OpenAI-compatible API. Solo dev, ~2 months, AI-assisted (not vibe-coded!). First preview is
This tweet discusses architectural patterns for building production-grade AI agents, emphasizing the importance of architecture over prompts. Senior engineers may find value in the insights derived from the Google AI Bake-Off, particularly regarding multi-agent systems and deterministic execution.
Building production-grade AI agents? It's not about better prompts, it's about better architecture.
Learn five patterns from the Google AI Bake-Off, from multi-agent systems to deterministic execution.
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AI agentsarchitectureGoogle AI Bake-Offmulti-agent systemsdeterministic execution