News & guides
Latency-Adjusted Model Scoring: When Fast Beats Smart
Benchmarks measure what a model answers, never how long it took. How to weight latency into model selection for interactive and agentic workloads.
· 9 min read
Layer Normalisation: The Part That Keeps Training Stable
Why deep transformers need normalisation, what pre-norm changed, and why RMSNorm won. The connection to quantisation and low-precision serving.
· 8 min read
LlamaIndex Setup on a Custom OpenAI-Compatible Endpoint
Configure LlamaIndex against a non-OpenAI base URL, split the LLM from the embedding model, and avoid the defaults that silently call OpenAI anyway.
· 9 min read
LLM Classification: Fix the Taxonomy Before the Model
Most classification failures are label definition failures. How to design a taxonomy, handle abstention and imbalance, and check the model beats a cheap baseline.
· 9 min readLLM Data Extraction: Design the Schema Before the Prompt
Extraction failures are usually schema failures. How to model absent, ambiguous and multi-valued fields, attach provenance, and validate what comes back.
· 9 min read
LLM Summarisation: Omission Hurts More Than Invention
Summaries fail by leaving things out, not by making things up. How to control what gets kept, pick a chunking strategy, and evaluate faithfulness cheaply.
· 9 min read
LLM Translation: Placeholders, Glossaries and Register
Machine translation is solved enough. What breaks in software localisation is interpolation syntax, terminology drift and missing context, not language quality.
· 9 min read
LLM-Powered Search: The Model Is Not the Retriever
Adding a model to search usually means query rewriting and reranking, not generation. Where each stage helps, what it costs in latency, and how it fails.
· 9 min read
Load Balancing in MoE: Stopping Experts Going Idle
An MoE model only delivers its promised capacity if traffic spreads across experts. Collapse during training and skew during serving are both real risks.
· 9 min readLogging LLM Requests Safely Without Building a Liability
The fields that make a model request debuggable are mostly not the fields that make it risky. How to log traffic that stays useful and minimal by default.
· 9 min read
Logits and Softmax: What a Model Really Outputs
A model does not emit words, it emits a score for every token in its vocabulary. What softmax does to those scores and why probabilities are not confidence.
· 8 min read
Long Context Degradation: How Quality Falls Before the Limit
Accuracy does not hold flat and then fall off a cliff at the context limit. It declines gradually, and the decline starts far earlier than most teams assume.
· 9 min readReady to try it?
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