Understand large language models, fine-tuning, prompt engineering, and model selection.
Fable 5 hits 80.3% on SWE-Bench Pro vs Opus 4.8's 69.2% but costs 2x and lacks zero data retention. The task-routing rule for when the premium pays off.
Constrained decoding makes LLM output schema-valid 100% of the time. When to use native structured outputs vs Instructor, Outlines, or BAML, plus safe streaming.
A UC Berkeley team hit 100% on SWE-Bench Verified, Pro, Terminal-Bench, and 9 more benchmarks by hacking, not coding. Here's how, and how to vet vendor scores.
Frontier models score ~80% on SWE-Bench Verified and crater to 23% on SWE-Bench Pro. Here's what multi-file PRs actually expose, and how to pick a coding agent that survives them.
Three open-weight coding models shipped in 18 days of April 2026. We ran the same SWE-Bench tickets through DeepSeek V4-Pro, Kimi K2.6, and GLM-5.1 to find which actually replaces Opus.
You can't cut costs you can't attribute. Here's the metadata + gateway pattern that pins every OpenAI dollar to a tenant, including the streaming usage bug LiteLLM users keep hitting.
MiniMax M2.7 hits 78% SWE-Bench Verified with 10B active params and 3x Opus throughput. Here's when it wins, when Opus still does, and how it was trained.
SGLang delivers 29% higher throughput than vLLM on H100s and 3.1x faster DeepSeek V3 inference. Here's the architecture breakdown and decision framework for picking the right engine.
Xiaomi's MiMo-V2-Pro secretly topped OpenRouter as 'Hunter Alpha' before anyone knew it existed. 1T params, 42B active, near-Opus performance at $1/$3 per M tokens.
