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Embeddings and Vector Databases – Lance + DuckDB + LangChain

It’s an interesting time to be in software and data; the world of generative AI is changing the landscape beneath our feet. I don’t see this as a bad thing for software folk, but as an opportunity to learn new technologies and BUILD / UNDERSTAND the technologies used in an LLM and AI context.

You can’t expect an LLM trained two years ago to be up-to-date on what the new and best approaches are for X, Y, Z tech.

Sure, they can do a decent job given enough context, Agents, etc, but if you’re working on the cutting edge of AI and LLM infrastructure, you are going to have to be active in the community and reading about what others are doing, who’s releasing new tools, and what those tools do.

Don’t forget, there is the whole architectural and systems design piece. One part of the LLM and AI infrastructure is vector and embedding representations.

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The Age of Agentic AI | LangChain and LangGraph style.

It’s a fast-paced and ever-changing world we live in; nothing we can do about it. I grew up in the middle of the prairie, when the internet became mainstream, the age of Doom, Myst, MSN Messenger, Yahoo Pool, and that irreplaceable Goldeneye, let’s be honest, World of Warcraft on a PC was game-changing. I suppose you could chalk up half my feelings as nostalgia and old-person hum-drum, I won’t deny it.

I see the current Agentic AI confusion in the software community as something similar to the old days when I split my time between being a river rat and playing Battlefield 1942 all night long, enraptured by new tech, yet drawn to the old ways.

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Running Llama 3.1 8B Locally (LangChain and SQLite)

Things have changed a lot in the last year related to LLMs and AI; on the one hand, it seems the AI skeptics for coding are increasingly confined to the corners of the internet. Everyone is dancing around in the middle, not sure of where everything should fall. Clearly, if we don’t use AI at all, we will become coding dinosaurs. But a sea of junior devs relying too much on Cursor has created a knowledge crisis, and demand for Senior+ devs has skyrocketed.

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Polars on GPU: Blazing Fast DataFrames for Engineers

Did you know that Polars, that Rust based DataFrame tool that is one the fastest tools on the market today, just got faster?? There is now GPU execution on available on Polars that makes it 70% faster than before!!

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Becoming a Senior+ Engineer in the Age of AI

I don’t know about you, but I grew up and cut my teeth in what feels like a special and Golden age of software engineering that is now relegated to the history books, a true onetime Renaissance of coding that was beautiful, bright, full of laughter and wonder, a time which has passed and will never return.

Or will it?

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AI (LLMs) and Software Engineering (Writing Code)

I recently wrote on my Substack (Data Engineering Central) about how I used the new OpenAI o1 model to do some basic Data Engineering tasks surrounding PostgreSQL. It did ok. I’ve also been using CoPilot and ChatGPT for over a year now to assist me with my daily code that I have to write for one reason or another.

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Is Devin Going To Take My Software Engineering Job?

Unless you’ve been hiding a rock you’ve probably heard the hubbub over Devin the new AI Software Engineer that is going to take your job.

While this is a genius piece of marketing … it’s a bunch of crud.

Never fear, you are in no more danger of losing your job in Software than when ChatGPT and CoPilot hit the market. In fact, the opposite is true, there will be more Software jobs than ever, not less.

AI tools might look pretty in a video, but in reality, by those who use them, the are very bad at programming still and don’t do a very good job. Most of what a Senior Engineer does that makes them Senior is not that spitting out of gobs of code. Any dingdong can do that.

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Future Proof Yourself Against AI.