[xrd]

This article is written by an engineer, first and foremost.

Many of the APIs or LLM extensions provided by AI companies are written by ML engineers that do not have Phil's decades of experience in distributed systems, databases and networking. That is evident after reading this article; the first time I've seen a coherent discussion of the tools and tradeoffs when building agentic systems.

I've struggled to actually build something useful with the "agentic" systems and tools out there (and I've tried a lot). Deep down I've felt intimidated by the dozens of new terms the docs use, and after reflection, those tech marketing pieces give the vibe that they are written primarily by AI and told to be colorful and not clear and precise. These solutions from billion dollar valued companies must to present "brand new" ideas to justify their valuations. We should know better: everything builds on the shoulders of decades of research and discovery. If you see something flying high in the clouds (and not standing on the shoulders of giants), it is sure to fall back to earth soon.

A great read. I'm very excited about Outropy.

[pcalcado]

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".

[bsenftner]

Yeah, it's really clear it's an engineer, what the software does is never even mentioned, the purposes and tasks that it performs: what are they? And how is hallucination managed? This reads to me like a complexity soup, where they just started without a clear idea of purpose or goal. Perhaps if the article mentioned what the software does, the purpose, it might be more clear. It sounds like a replacement for the entire management layer of a company...

[NeutralCrane]

Agreed. This could be a very intelligent implementation, or it could be an over-engineered mess. It certainly seems like overkill for my experiences with agents, but problem applications can vary wildly. It is impossible to tell how to evaluate these design choices without more concrete details.

[pcalcado]

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.

[pixelsort]

Manager need to replace engineers with AI faster than engineers use AI to replace their managers. In the end, nobody wins except OpenAI.