Alternatives
Products that do what Lean customer development methodology simulated by AutoGPT does
Provide an elevator pitch and target customer, and GPT generates personas to interview, with catchy names like Serverless Sarah. Then simulate user interviews, summarize the outputs and provide follow-ups. It's inspired by the legendary startup book Four Steps to the Epiphany by Steve Blank. I am building a new database (I was one of the creators of CouchDB / PouchDB) and wanted an example app that more fun than just database crud operations. Fireproof is designed to be the easiest way to add dynamic data to any app or page. It uses IPFS multiformat blocks for content addressing (and…
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As a solo developer on a sizeable project, I found myself facing the challenge of creating documentation, a task I admittedly do not enjoy. Fortunately, ChatGPT arrived just in time. After experimenting with it, I discovered that it generates high-quality documentation for code files, even better than what I could produce manually. This realization led me to develop Code-Narrator, a client that simplifies the documentation process. Code-Narrator (https://github.com/ingig/code-narrator) utilizes GPT-4 to analyze your code files and automatically generate documentation. The…
2023 · github.com
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2023 · gptappstore.com
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2021 · youtube.com
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Hi, everyone! Lately, I've been working on quite a few applications that require a database, and as a result, I need some data to test everything. It has always taken me a lot of time to ask ChatGPT to generate fake data for me, so I decided to create a tool for developers called FakeData. FakeData allows developers to generate fake data easily with a simple UI/UX and customizable fields. This data can be used in their applications to test various functionalities. P.S. The app is not yet finished, and I would love to hear your honest feedback on it. Please be brutally honest about what…
2025 · fakedata-mu.vercel.app
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I'm building an AI platform, FlowChai and found a neat use case for it today that I thought would be useful to HN readers. I use GPT4 heavily for writing / editing code, but a major downside is that it doesn't know about new projects. I made the connection today that I could upload the zip file of a Github repo to FlowChai and then write prompts just like with ChatGPT with code questions. While the original intent for this platform is more around natural language, it's neat how this works so well. It's powered underneath by pgvector and OpenAI embeddings.
2023 · flowch.ai
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I’m Abhilash, one of founders of CompanyGPT. Our mission is simple - let investors and sales teams build list of companies using plain English Example: "Find companies building video editing tools using generative AI, that have raised more than $2M, that have headcount growing more than 20%" — Why CompanyGPT? Ever tried finding companies based on the description of what they do? Eg: "Companies building robots for fighting forest fire" Google search returns content marketing articles around forest fire and climate change Crunchbase doesn't have a category for these companies Linkedin…
2023
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A couple of years ago, we had an interesting idea. When a development team within an organization consists of around 10 members or fewer, controlling the risks associated with database changes might be achieved through trust and real-time communication. However, as the team grows, the responsibilities within the team become more specialized. Imagine a scenario where different branches of the business exist, each with its own set of developers, team leads, testers, testing leads, DBAs, and more. Relying solely on traditional communication methods becomes increasingly challenging when it comes…
2023 · github.com
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Hi HN! Last night, I live streamed myself coding this Llama 2 Agent on a Single GPU (Colab). After 6 hours it actually has some good results. How it works is it takes in your intuition (e.g. "I think x would be cool") and develops a business idea (with a name and branding colors) and a business plan. After the business plan is developed, it criticizes this plan recursively until the "Investor" prompt is satisfied with the plan. After all this it will generate the final MVP idea and pass it to a the React Engineer Agent I live coded 2 days ago…
2023 · github.com
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Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
2024 · dorik.com
- 22IG
This holiday weekend, I created a GPT for Instabooks, which allows you to instantly generate textbooks on any topic within ChatGPT. Why? ChatGPT is great for learning stuff, but sometimes you just want to go deep and read an entire book about something. For example, there's a great talk by Stephen Wolfram that just goes over my head (https://www.youtube.com/watch?v=fLMZAHyrpyo), so I copy/pasted the transcript into the GPT and it generated a textbook that goes deep into all the topics from that video…
2023 · chat.openai.com
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I've never used .NET, know nothing about .NET or vb, or anything outside vc++ & MFC. Recently I gave GPT a try, guiding it step by step, and asking it to help me rebuild a tool I originally wrote in MFC. To my surprise, it worked: a full Excel-to-PDF automation app, done in 30 minutes; including a small algorithm I thought would be too tricky for AI to handle. I didn't understand even a single line of the code, I just kept asking, copying, and running. It felt amazing… but also terrifying.If AI can do this now, what happens 5 years from now? Here's a 5-min video I made showing the full…
2025
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Scaling data teams today means dealing with the complexity of the modern data stack. While DBT has become a core tool for transforming raw data into structured, analytics-ready tables, most teams are using it in ways that lead to chaos: duplicated models, inconsistent metrics, and inefficient SQL that directly impacts cloud spend. The real issue isn’t with DBT itself—it’s in how it’s applied across teams. Here’s the typical setup: Finance defines a revenue model, Marketing calculates customer lifetime value, and Product defines churn. All in DBT, but all with slightly different logic,…
2024 · github.com
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