Method Drift
Which methods have been superseded
A living systematic review per builder-problem. For each problem below we track which methods have become superseded baselines, what sits on the live frontier, and the grounded receipts— verbatim critique quotes and benchmark numbers, each traced to the paper it came from — behind every “X superseded by Y” claim.
10 builder-problems3,164 papers6,756 critique receipts26,480 benchmark results
Stack check
Is your agent stack out of date?
Pick your method for retrieval, memory, tool use, and long context — see what's superseding each.
Parameter-efficient fine-tuning (LoRA family)
Adapting big models without touching every weight — LoRA and the variants chasing it.
Retrieval-augmented generation
Grounding generation in retrieved context — the architectures replacing naive RAG.
LLM reasoning / chain-of-thought
Teaching models to think before answering — chain-of-thought and what came after.
Mixture-of-experts routing
Scaling capacity without the compute — sparse experts and how they are routed.
KV-cache compression
Shrinking the attention KV cache for long context — eviction, quantization, and reuse.
Speculative decoding
Drafting tokens ahead to speed up inference — the EAGLE/Medusa lineage.
LLM quantization
Running large models in low precision — post-training quantization methods.
Agent / long-term memory
What an agent remembers across a session — long-term memory systems.
Long-context / context-window extension
Reading past the training length — positional tricks that extend context.
Tool use / function calling
Teaching models to call APIs and tools — function-calling and agent toolkits.