Also, the premise that it took each of them a year to do the project means Bob was slacking because he probably could've done it in less than a month.

I built a full stack app in Python+typescript where AI agents process 10k+ near-real-time decisions and executions per day.

I have never done full stack development and I would not have been able to do it without GitHub Copilot, but I have worked in IT (data) for 15 years including 6 in leadership. I have built many systems and teams from scratch, set up processes to ensure accuracy and minimize mistakes, and so on.

I have learned a ton about full stack development by asking the coding agent questions about the app, bouncing ideas off of it, planning together, and so on.

So yes, you need to have an idea of what you're doing if you want to build anything bigger than a cheap one shot throwaway project that sort of works, but brings no value and nobody is actually gonna use.

This is how it is right now, but at the same time AI coding agents have come an incredibly long way since 2022! I do think they will improve but it can't exactly know what you want to build. It's making an educated guess. An approximation of what you're asking it to do. You ask the same thing twice and it will have two slightly different results (assuming it's a big one shot).

This is the fundamental reality of LLMs, sort of like having a human walking (where we were before AI), a human using a car to get to places (where we are now) and FSD (this is future, look how long this took compared to the first cars).

I made my Restailor project open source. You're welcome to use the code in case you're looking for a new job or just want to play around with an LLM integration for this purpose. You're also welcome to use my prompts.

It's working end-to-end and I built the infra to scale and support a lot of users using it (Next.js + FastAPI + Redis + Postgres). It also has applied job tracking and analytics.

LLM integrations are with Anthropic, Google, OpenAI, and xAI.

Please let me know if you have any questions.

Thanks!

Comments URL: https://news.ycombinator.com/item?id=47346676

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Most of your programming should be DAX plus a bit of worksheet functions. Some SQL to filter your data before loading into Power Pivot.

SQL yes, of course. You run SQL queries to load data into Power Pivot through a native SQL Server driver or native drivers for your DB or worst case ODBC.

Then you do all the BI analytics in DAX and show results in pivot tables. DAX is a very fast, concise and very, very powerful language for analytics. This is the whole purpose of OLAP.

Check out this video when you have time :)

https://www.youtube.com/watch?v=0WwFJ0Zg3d8

At the same time, it can all be done in Power Pivot and Power Query as long as you know how to use them.

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I don't see anything objective about that article, it looks like an opinion piece.

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However, in practice, there are signs as to whether you have good insulin sensitivity or not and possibly whether you over-secrete insulin. Here’s two very simple questions to ask yourself regarding your response to diet.

1. On high-carbohydrate intakes, do you find yourself getting pumped and full or sloppy and bloated? If the former, you have good insulin sensitivity; if the latter, you don’t.

2. When you eat a large carbohydrate meal, do you find that you have steady and stable energy levels or do you get an energy crash/sleep and get hungry about an hour later? If the former, you probably have normal/low levels of insulin secretion; if the latter, you probably tend to over-secrete insulin which is causing blood glucose to crash which is making you sleepy and hungry.

http://www.bodyrecomposition.com/fat-loss/insulin-sensitivit...