menu_book Engineering Journal
Insights & Research
Exploring the confluence of frontier AI theory and the engineering realities of shipping it. Field notes, benchmarks, and the occasional opinion.
Research 13 min
DFlash explained: how block-diffusion drafting makes LLMs generate faster
A visual walkthrough of DFlash architecture, Apple Silicon and RTX execution, and what a Muse Spark integration would actually require.
person Latentsig AI Research
Engineering 16 min
INT8 post-training quantization without tears: a production checklist
INT8 PTQ in prod is a workflow, not a switch. The six steps we run before any model ships at reduced precision.
person Latentsig AI Eng
Strategy 6 min
Why your AI roadmap should be three lanes, not one
Research, integration, and operations move on different clocks. Treating them as one program is how teams stall.
person Latentsig AI Advisory
Research 12 min
Evaluating retrieval: beyond top-k accuracy
The metrics that actually correlate with downstream LLM quality, and the ones the leaderboards keep rewarding instead.
person Latentsig AI Research
Notes from the lab, in your inbox.
Roughly monthly. Engineering, no marketing.