posted #datamachine to hackernews

get ahmed the things he needs to make a product video for #datamachine

Launch #datamachine on product hunt. www.producthunt.com/posts/dat…

include a demo for #datamachine

Day 2: A Blog Post a Day for 90 days #datamachine

content marketing has really started to work. With the release of #datamachine we're now going to focus on iterations and marketing on our existing product suite for the remainder of the year to see if we can grow these business. Day 1: One Blog Post a Day ✅ #sveltelaunch

setup intercom, domain names, emails, etc for launch of #datamachine

deployed DataMachine to production for the first time #datamachine

continue prepping for launch #datamachine

finish landing page #datamachine

create discord bot that connects to my apps and receives notices when someone subscribes or makes a purchase of one of my products #datamachine #sveltelaunch

test that upgrading and downgrading of plans is working correctly across all plans(weekly,monthly,yearly) and that the correct number of tokens is assigned at change #datamachine

implement weekly subscription option to generate higher conversions(and probably higher churn on the weeklies, but the app has a use case for it where I can see people needing it for 1 off data cleanings and the cheaper weekly price point might encourage more people to try it out). #datamachine

implement "document mining" as a feature — extracting statistical, trend, tabular, and analytical data from PDF documents and converting it into tabular data #datamachine Based on this post x.com/dvassallo/status/183154…

Claude 3.5 just blows my mind sometimes. It's incredibly intelligent naturally. I am going through final tests on a new App I'm building to generate, clean, and enrich datasets. I was testing the enrichment portion last night and it just knows things. Like it understands when cleaning data and I'm asking it to add thousand separators that some of the data may not be a number in the traditional sense. I had a dataset that has population, median_income, and zip codes in it, but it only modified the population and median_income data without the need to specifically prompt for it. This might seem trivial, but its ability to reason without guidance amongst large sets of data is quite remarkable. #datamachine

implement credit costs when cleaning or enriching data with AI #datamachine

test stripe subscription renewals and make sure everything is handled correctly #datamachine

implement a basic dashboard for launch #datamachine

implemented credit costs when generating datasets #datamachine

implement plan scoped features #datamachine