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Víctor Busqué.

Software engineer in Barcelona. I build AI platforms and agents that run at production scale — and I learn by making things run.

BARCELONA · SPAIN 8+ YEARS · NLP & GEN AI FOCUS AGENT SYSTEMS
victorbusque@gmail.com linkedin.com/in/vbusque victorbusque.com Barcelona, Spain

01Who I am

I'm Víctor Busqué, a software engineer in Barcelona. For the last eight years I've worked on NLP and generative AI in production — LLM gateways, agent runtimes, platforms that hundreds of engineers depend on. That part of my life is a job. This site is something else.

I'm an avid visual learner. I love reading, but I understand the most when there's a simulation, a visual demonstration, an animation that shows the thing clearly. I built this blog to learn that way — and to present things in the form that's easiest for me to ingest. If it helps someone else too, even better.

02How I learn

Take one idea — prompt caching. I can read about it, look at a diagram, or watch it happen across requests. Same idea, three media. Switch the tabs and watch where it sticks.

FIG. 01 THE SAME IDEA, THREE WAYS
MEDIUM
An agent conversation resends the whole history with every request. The first time, every token is new: keys and values are computed in full — the full price (×1.0). Providers keep them in a KV cache. Next request, the repeated prefix is served from cache at ×0.1 — a fraction of the price. New messages are not cached yet: full price once, then cached for the one after.
UNDERSTANDING
24%
What to watchThe meter and the cost panel beside the animation. Watch each request: what you would pay without the cache versus what you pay with it — and how each new message becomes cheap the moment it joins the cache.
The meter is the point of this site: I don't really get an idea until I can switch to the medium that runs and watch it myself.

03Why the blog exists

So this is the loop I run. I take a question, build a figure that runs the real process, and step through it until it's mine. That's why nothing here is faked — if I can't make it run, I can't explain it.

FIG. 02 THE LOOP I RUN CSS LOOP · PERIOD 4.0s
What to watchThe dot orbits the loop. Question, build, step through, it's mine — then the next question. Each pill lights as the dot passes it.

04What backs me up

My experience has brought me to a NASDAQ-listed fintech from Uruguay. Large-scale operations mean scalability, robustness, security are not optional. Here are some numbers of what I've delivered thus far.

AGENTIC PLATFORM
0+ENGINEERS SERVED
0+AGENTS AUTOMATING WORK
0+AGENT INVOCATIONS / MONTH
AI INFRASTRUCTURE
0MREQUESTS / MONTH
0BTOKENS / MONTH

Counted, not estimated — from the platforms I ran.