pcalcado's comments

Congratulations! I wish I had this inside emacs so I can use paredit

From LinkedIn: For years, was an enthusiastic recommender of A Cloud Guru | A Pluralsight Company for folks looking to get into infrastructure engineering! Bought enterprise licenses and even bought the lifetime course access plan for myself.

And now, Pluralsight is revoking that lifetime access plan out of “convenience”.

Anyway: I no longer recommend Pluralsight if you are hoping to grow professionally. Hate seeing cash grabs like this.

https://media.licdn.com/dms/image/v2/D5622AQGl20RwjpA3kQ/fee...

Same here. I've had data-intensive systems and classifiers on critical paths for non-AI apps, and the same tools I used before seem to work fine with GenAI.

The primary real difference I've found has to do with when agents make decisions; this creates arbitrary call graphs in your distributed architecture and makes it harder to provision things, optimize, and do anomaly detection.

If only they embrace Pydantic and the libs Python people actually use >.<

By database layer, do you mean the RDS in the diagrams?

If so, they were logical diagrams; the deployment itself was more complicated to handle the realities of AWS and whatnot.

Still, having a single beefy RDS instance is a pretty common pattern for apps at this size. I've never experienced RDS postgres as a bottleneck for standard microservices architectures even at the 100-million-MAU scale.

Yes, that's what I meant.

There's a whole can of worms here around the "what is a microservice, anyway?" but I tried to avoid more philosophical questions and used the term as shorthand for "small deployable unit following some version of 12 factor for horizontal scalability." It's not super comprehensive but matches what I've seen in practice over the last decade+

This is good feedback; thanks both! Initially, this was a single article, and it started with an explanation of the system, but it was getting too long, so I decided to split it into three. In hindsight, I should have started with part II, where I wanted to talk about the features, but I thought that the most underserved part of the AI stack was the back-end architecture, so I tried to address it first.

Thanks! Honestly, I feel like my first year was a lot of just translating what those papers were trying to say—especially because often they talk a lot but don't say much. I am lucky that my cofounder has a background in ML/AI and could help me understand, but something else that helped me was to ask Claude/GPT to explain something I don't understand: "using analogies an experience back end developer understands".

Author here.

The deprecation comment refers to this: https://tools.ietf.org/html/rfc3986#section-1.1.3 we had been using URNs and URLs the old way.

But in any case the fact that we're having this conversation I had had to dig up some RFC from 2005 reflects the actual reason for not following any specific standard: I perceive them and their specifications to be confusing and full of historical context that has changed over time. Assuming that there are no other benefits to using the URN scheme specifically (maybe there are and I am not aware of them?) I'd rather use a simplified URI and custom schemes.

That's a great point, thanks.