#benchmarking

While reading the draft Go 1.28 release notes, I noticed a change in the HTTP/2 server. With this...

A mechanism explainer of LFORLA's election forecasting benchmark: how models commit to concrete scenarios for the 2027 French presidential and 2026 US midterms, and how a fixed judge scores specificity, grounding, and calibration.

A mechanism explainer of the LFORLA LEGO Set Build benchmark: how agent capability is measured end to end with a deterministic construction oracle, plus the real leaderboard numbers and what they mean for model selection.

"One month behind" is a slogan, not a measurement. Here is what the scoreboards, the invoices and the hands-on tests actually show about the open-weights challenger.

Most agent benchmarks are not wrong on purpose. They are contaminated: the task set leaked into training, the fixtures moved between runs, the judge graded the producer's own claims, the good-looking samples got kept.

An S3 throughput benchmark is only as honest as its setup. Most published numbers hide three...

TL;DR: Use GPT-4o-mini as the cost baseline for an in-app B2B SaaS support triage chatbot, then keep...

Why this lesson exists In Slack threads you’ll often see two people paste a mean execution...

A browser assistant should be able to read an invoice, compare two offers, or find the right button...

I Built a Benchmark That Catches AI Models Cheating (And They All Failed) What...

A practical DEV.to-style walkthrough of how prompt caching, sticky routing, and workflow dedupe can fake LLM benchmark improvements. Covers what to lo

Why this lesson exists Unexplained variance in a csperf run often gets blamed on the...