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One thing that keeps coming up is that SQL equals low productivity. I don't think this is true. I think the culprit is that most developers are using to heavily abstracting SQL using ORMs like Prisma that hides the database and SQL logic. Since building a SQL generator (https://aihelperbot.com) as a side project, I have become much more proficient in SQL and even though I am also locked into Prisma, I use the... - Source: Hacker News / 7 months ago
A few things I have learned over the years and in particular launching and growing my latest project[1]: 1) Track everything including errors. Know what users are using and what they aren't. Remove or rebuild less used features. 2) Find out who your users are and what they value. Ignore non-payers. 3) Economize, market, and document features. You not only need to develop and deploy features, but also to price them... - Source: Hacker News / 7 months ago
It started with me working on a hobby project, aihelperbot.com which enables users to generate SQL using AI. It was build using the comprehensive Prisma ORM. I always found Prisma bloated and it requires almost constantly that you lookup their API for even trivial usage. Source: 8 months ago
Sounds like a combination of an unpolished product with insufficient demand and wrong business model. Users today don't want to pay XXX up front for a complicated product, they want a free tier where they incrementally learn about features. I just looked up what I spend on Google Ads for a small campaign on SQL/AI related keywords for https://aihelperbot.com: - $699.95 (part of a spend $400 to get $400 deal) -... - Source: Hacker News / 9 months ago
Neat setup. Regarding the deploy script. I have just setup a separate VPS for proxying database queries using various Node database drivers for my own project[1] and only used Github Actions managing it[2]: - add build script using Github Action that fails the entire build pipeline if code doesn't build - add deploy script (essentially a few commands ssh into your VPS and pulling, install, building and restarting)... - Source: Hacker News / 10 months ago
I often heard data scientists having to run various queries on the database for teams with little or no SQL knowledge. It is a cumbersome process for everyone and it is one of the main problems I am solving with my small business undertaking. Everything can be safely managed by a technical user and other users can simply generate SQL via AI and run them directly on the database. Source: 11 months ago
It is my own tool that generates SQL using AI and runs the SQL on the connected database as a business intelligence tool. It adds the database schema in the context, which can be large. I have tried other ways to mitigate this but all of them regresses usability of the application (at least slightly). Source: 11 months ago
If you want a more specialised AI-powered SQL builder where you can import database schemas and run generated SQL queries, check this out. Source: about 1 year ago
Plenty of users on my site bumped up their SQL proficiency including myself in a short time. You can bing me if you want want a live database to test your SQL against. Source: about 1 year ago
If you have some really complex queries that you want to test to see if AI (GPT-4) can generate you are welcome to try: https://aihelperbot.com. After upgrading to GPT-4 I haven't had a single miss so far (when adding database for context). - Source: Hacker News / about 1 year ago
I think this is the case for many larger companies (or at least they need to explicitly allow a particular IP). Would it work for you to simply export the database schema and use that or is that still an issue? Many of my users either export the database schema as CSV and use it. Source: about 1 year ago
I re-taught myself SQL after a long detour in ORMs land using AI. It is hyped I know, but being able to formulate what you what to see and have AI build the SQL query is a powerful way to learn. You can see my side project here, has a few other features as well. Source: about 1 year ago
> trivially solved with one or two dedicated servers... For many even lot less than that. I run a small side project[1] that went viral a few times (30K views in 24 hours or so) and it is running on a single core CPU web server and a managed Postgres likewise on a single CPU core. It hasn't even been close to full utilization. 1: https://aihelperbot.com/. - Source: Hacker News / over 1 year ago
I agree that this blog post is part "orm" and part "lead gen for my saas app which helps you write sql queries". I think a blog title which reflects this, ORM and AiHelperBot, would be more helpful. That being said - the faq's on https://aihelperbot.com/ don't answer the main questions I have:. - Source: Hacker News / over 1 year ago
I partly agree. It is still very early application of AI. Most AI/SQL builder are rather simple and target beginners. But I reckon more experienced SQL users can benefit as well (I did so myself). With my side project I distinguish between 2 modes:. Source: over 1 year ago
I you like a hands on approach to learning, this tool might be helpful to you. Improved my SQL skills. Source: over 1 year ago
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