Can the presence of a URL in an LLM prompt influence the output based on the content of that URL?
I think, yes! But it took me weeks of experimentation and I learnt a lot about what User Agents do and what data is in the models
One thing that I've been doing for nearly all my LLM based projects is getting runtime observability built in (or more importantly as a constraint in my initial prompt) - it feels like it's almost free to do now.
It started with extensive console logs in the client and on the
I was listening to a transcription of anthropic.com/research/self-… and it made me think about hardware os heterogeneity and the fact that so many hardware devices build upon the back of ASOP. I was thinking back to the Google IO demo of anti-gravity and how they built an OS and how
Synthetic perf testing was valuable for low-noise dev testing and regression detection but lost favor as RUM metrics improved.
With AI, accurate, representative, low-noise lab testing is THE unlock to being able to have an agent hill-climb on perf improvements.
I've been building a lot recently through some automated tooling pipelines. One annecdote that I will write about soon: Kimi, Qwen and Z.ai subscription plans limits make them almost useless for all but the most basic tasks.
DeepSeek doesn't have a coding
