Most "AI news" is recycled press releases. Here's what actually matters if you write software for a living.

1. Attention sink pruning — Researchers found you can remove 40% of attention heads in large transformers with zero accuracy loss by identifying "sink" tokens that absorb unused attention. If you're fine-tuning models, this cuts your VRAM bill almost in half.

2. Compiler-aware code generation — A new approach feeds LLVM IR back into the generation loop, so the model actually understands what the compiler will do with its output. Early results show 23% fewer runtime errors in generated C++ code.

3. Streaming RAG with sliding context — Instead of chunking documents into fixed windows, this paper proposes a sliding attention mechanism that maintains cross-chunk coherence. If you've built RAG pipelines, you know how painful chunk boundaries are — this might finally fix it.

I break stuff like this down every week in Byteline. No hype, just what matters for engineers who ship code.