I tried that. Pasted that exact prompt after the first response. It gave me a really long response picking out some specific technical aspects of my solutions mentioned in my blog article which kind of make sense but nothing that seems like a show-stopper IMO.
One of the points I totally disagree with:
> The Verdict: Developers are using AI to escape abstraction layers, not to find new ones. They want the AI to write the boilerplate they used to buy SaaS for.
I'm a developer. This is not what I see happening. Things like edge functions are more popular than ever. So are SaaS platforms like Lovable and Base44. Supabase is getting tons of traction. You need somewhere to host the back end/CRUD and use AI to generate the front end. The narrative of devs abandoning platform SaaS doesn't make sense. Most devs don't even know how to launch and access an EC2 instance these days.
It concluded with:
> the market stays irrational longer than you can stay solvent.
> the most rational move is to keep (project name) as a personal tool. Use it to build your own apps efficiently. Let it be your "secret weapon" that makes you 10x faster than the employees you work with. But do not try to sell the weapon to the army; they have already signed contracts with Lockheed Martin.
It's speaking figuratively here. I make no mention of the army or Lockheed Martin but the message is clear.
The sources it provided are basically competing startup websites... actually seem to support my work and direction, pointing to similar projects and trends that are successful and aligned with what I'm doing so it's confusing. My current project provides similar features as some mentioned here. The second one is basically exactly the problem that my current low-code project solves. I've built entire complex data-driven apps with it so I know it works and is secure. I have 15 years of software engineering experience working on top projects including backed by YCombinator...
[1] Supabase RLS Documentation: "Row Level Security (RLS) is a PostgreSQL feature...
[2] Chris Paik on "The End of Software": Discussion on how LLMs reduce the cost of creating software to zero, favoring standard/reproducible code over proprietary configurations. (common knowledge in VC circles, 2023-2024 discourse).
[3] Pinecone Multi-tenancy: "You can use namespaces to manage multi-tenancy... Queries in one namespace cannot access vectors in another." (docs.pinecone.io/guides/indexes/namespaces)
[4] pgvector & RLS: "pgvector integrates seamlessly with PostgreSQL's security features, including RLS." (github.com/pgvector/pgvector)
[5] OpenAI Realtime API: OpenAI's documentation on their WebSocket-based API for real-time speech and text. (platform.openai.com/docs/guides/realtime)
[6] Vercel AI SDK: "Build AI-powered applications with React, Svelte, Vue, and Solid... Streaming text responses." (sdk.vercel.ai/docs)
One of the points I totally disagree with:
> The Verdict: Developers are using AI to escape abstraction layers, not to find new ones. They want the AI to write the boilerplate they used to buy SaaS for.
I'm a developer. This is not what I see happening. Things like edge functions are more popular than ever. So are SaaS platforms like Lovable and Base44. Supabase is getting tons of traction. You need somewhere to host the back end/CRUD and use AI to generate the front end. The narrative of devs abandoning platform SaaS doesn't make sense. Most devs don't even know how to launch and access an EC2 instance these days.
It concluded with:
> the market stays irrational longer than you can stay solvent.
> the most rational move is to keep (project name) as a personal tool. Use it to build your own apps efficiently. Let it be your "secret weapon" that makes you 10x faster than the employees you work with. But do not try to sell the weapon to the army; they have already signed contracts with Lockheed Martin.
It's speaking figuratively here. I make no mention of the army or Lockheed Martin but the message is clear.
The sources it provided are basically competing startup websites... actually seem to support my work and direction, pointing to similar projects and trends that are successful and aligned with what I'm doing so it's confusing. My current project provides similar features as some mentioned here. The second one is basically exactly the problem that my current low-code project solves. I've built entire complex data-driven apps with it so I know it works and is secure. I have 15 years of software engineering experience working on top projects including backed by YCombinator...
[1] Supabase RLS Documentation: "Row Level Security (RLS) is a PostgreSQL feature...
[2] Chris Paik on "The End of Software": Discussion on how LLMs reduce the cost of creating software to zero, favoring standard/reproducible code over proprietary configurations. (common knowledge in VC circles, 2023-2024 discourse).
[3] Pinecone Multi-tenancy: "You can use namespaces to manage multi-tenancy... Queries in one namespace cannot access vectors in another." (docs.pinecone.io/guides/indexes/namespaces)
[4] pgvector & RLS: "pgvector integrates seamlessly with PostgreSQL's security features, including RLS." (github.com/pgvector/pgvector)
[5] OpenAI Realtime API: OpenAI's documentation on their WebSocket-based API for real-time speech and text. (platform.openai.com/docs/guides/realtime)
[6] Vercel AI SDK: "Build AI-powered applications with React, Svelte, Vue, and Solid... Streaming text responses." (sdk.vercel.ai/docs)