blef

I guess history repeat.

It changed the career pathway for junior but the biggest change i feel is about education. It completely emptied for a lot of people the principle of learning and building something.

This is a nice use of the Observable framework. Tbh I like, but I find the information difficult to read in a website organised this way when I'm used to dashboards.

Congrats and happy to see them keeping up (from a bit far away) with Anthropic and OpenAI fundraise rhythm.

Feels a bit weird to do a vs. when both are really not used for the same purpose. I know in the article you say it, but the title (?)

Consolidation was expected to happen in the ETL space, that one i did not see it coming but it makes sense, now Fivetran can load, transform and export (Census)

I would also add that context and tools are the product. This is super important to correctly tune the tools and details matter (ok you can also argue that tools are context in some way)

Never heard of it. Is API the thing we develop for MCPs to interact with?

I'm curious to understand why did you decided to develop a local app?

why is there a press kit for a clock app? also it triggers me a bit that the clock is not exactly aligned with the MacOS clock

I don't have my own music collection, but because of this I'd consider finding a way to have it to switch away from online providers.

This is cool, tho it's a bit sad that it does not understand when the game has ended

your pseudo makes sense—tho what's the issue with Greenpeace.de?

The Twitter post is way too long I can't even read it, and probably written by an AI

> - Code Chunking: Chunks code files by creating an AST and finding ideal split points.

I'd be interested to use it for SQL, did you try? Does it works well with it? I'm not familiar with the tree-sitter library

nao Labs | [Staff, Senior] AI Engineer | Paris or remote (Europe) | Python, Typescript, React

We are building Cursor for data teams. Using nao, data practitioners can work on data pipelines using AI faster without breaking stuff. nao connects to your data warehouse / lake and helps users give the correct data context to the AI so it does not hallucinate.

What we are looking for: an Senior AI engineer with proven experience on LLM training, fine-tuning, inference and deployment. We have codegen models dedicated for data code (Python and SQL) and we want to be the best at this. In nao, AI powers the chat experience (agent) and the Tab (autocomplete and next action).

We are a YC company and we want to be the next daily tool every data people are using. I can also be a Founding engineer position.

→ https://getnao.io

If interested reach out: christophe [at] getnao.io

We are using Relace in production to apply code for a month and this is crazy how easy it has been to integrate it (less than 30 minutes). The most impressive thing when you come from a general purpose LLM is the speed and the accuracy relace brings.

In the past we were using o4-mini which had an annoying issue at adding newline when not needed and was slow (5s+), relace fixed all these issues.

This is a cool thought exercise to think that everything that we do in the data world can be done in SQL, from SQL. In a sense this is the MCPs but for the DuckDB world.

I'm working on a repo listing this, I hope to finish it soon

*blushes*

Hey, I removed the freewall for everyone, sorry for that.

PS: I'm the original author of the article and got an alert of traffic spike. And it was a freewall, meaning it's accessible for free members.

Thanks.

Hey, OP here. I wasn't ready to get so much negativity from my post. OK the title was a bit clickbait but I just shared honest feedback because I was sure that a lot of people could recognize from my stories.

I never said I was an expert in the post, I never said I consider myself better than everyone, and moreover I'm 100% sure I can bet I've not impacted the life of one person that commented my post.

Is it my fault when I just graduated that I had been given the responsibility of building an Hadoop cluster for a +$100m revenue company? No, I just tried to do my best. I fucked up things and I fixed it. Period.

I'd love to work with all people telling me I was incompetent, but unfortunately you weren't here to bring me the light in 2014.

7 years after I can sleep at night and live with my mistakes. So, yeah, sorry for that.

I'm closing this, love.

I never said it was in the same company.

Yeah, fixed and oops too late because everyone read it.

Yeah I made some shortcuts about it in the post for the sake of trying to keep it short. But the biggest issue with sudo was the suid bit you're right.

You're totally right in your message. I did not had access to root password.

I was junior and while I was trying to fix stuff I was adding more problem to the initial one that was a disk space issue.

Yes, oops.

I really like the effort you made in following more than 2 links to see what I'm doing. The issue is that you also don't have the full context on everything that happened.

I don't know on which kind of teams you work in, but I personally worked a lot in teams where I was the only person responsible to do data related tech stuff for other people. I never said that I wasn't responsible but I was alone, so setuping backup was often the last of my priorities. I was and I did all my best to fix things as fast as possible and to remove any issues it could lead in the future.

When I was setuping Hadoop cluster in 2014, almost no-one knows what it was in my local market. So let us try, then fail and learn.

If you also think from 3 stories I'm writing on the internet that I'm careless so be it. But I also recommend you to fix your "router configuration" problem rather than ranting on posts on internet.

I share 3 stories about my previous experience when I deleted not on purpose data in my Hadoop clusters or when we ran terraform destroy over our GCP projects.

This is a personal post about what I learnt and some takeaways.

Did you ever feel the same way?