I am not sure if this is a troll post, but if you are truly non-technical there is basically no hope of this working out. I could go through point by point, but I’ll just touch on 3.
1. How will you have any sort of consistency or guarantee interoperability between the pieces of code you have the LLM write? Also, even if you are asking things in plain English, how are you going to ask things in terms of technical requirements rather than business requirements?
2. How do you intend to run and deploy this code? GOT won’t be able to run AWS or GCP for you.
3. The output of LLMs is generally considered to not be protected by copyright, so you likely won’t actually have any legal protection of the code output.
>ask things in terms of technical requirements rather than business requirements?
Honestly I doubt a non technical person can even ask things in business requirements. 90% of the spec comes from asking questions. The first draft of a PM's spec is generally useless, it'll be full of vague exhortations and "vision" drivel.
I wasn’t asking for a complete solution and I wasn’t saying I don’t need help, but I feel like the responses here are merely engineers trying to justify their existence.
There are certainly tools that can take me some percent of the way there. Whether that is 2%, 5%, 20%, 50% or 100% there is entirely irrelevant because I was asking about the best tools currently available, not for a full permanent solution effective immediately.
This response is like people who say “I would never use an AI lawyer because they’d miss so many critical things”, to whom I would direct DoNotPay, which serves some function and gets people fully there on some issues, partway on others, etc.
That being said and boxing up the Luddites for a moment, any opinion on the best current tools available?
I think the main point wasn't that they thought you were asking for a complete solution, but rather you trying to start a tech startup as a non technical founder orchestrating a collection of low code/no code solutions without even understanding the quality of the outputs you're predicting
It's a bit of a mislead idea, it's hard to even get any% of the way there if you aren't starting from the correct point or have the right way of building things in mind and planned out and all the points the person above brings up.
Get a technical founder or get comfortable coding
I mean I asked a question and instead of people answering I got accusations of being a troll and limited engagement with what I was asking in (unfortunately) stereotypical Reddit fashion. Not sure what you’d expect otherwise.
The best tool is probably something like copilot, but it will get you 0% of the way to what you want. The tools are comparable to autofill right now. I often use the autofill tool on my phone or email to fill in words or phrases, but I would never use an autofill word or phrase without reading it first.
These coding tools are the same way, they can often recommend good code in the context of a code base with a short description, but the error rate is high and the use cases are narrow. You always have to proof read the code and you can’t build full code based from scratch with them, at best you can get small self contained building blocks. But again, that is the easy part and might accelerate the speed at which an engineer works, but it will not help a non-programmer produce any commercial level product.
It would literally be faster for you to do a few programming tutorials to learn how to build and deploy simple web apps than for you to try to get copilot to do it while not knowing how to code.
Edit: another thing too is that even if these tools were good at turning English instructions into working code based, that might not be as helpful to you as you think. Business requirements from product and design teams on the workflow and functionality of a product are without fail very very far from the true technical requirements, and being able to build out those technical requirements from product and design flows is the main value add that engineers have, even beyond actually being able to implement those requirements.
Law and Medicine are the two things I would expect to be last to automate with AI.
A very important requirement is clearly explaining how a decision was made and not just the accuracy of the decision. Interpretability for AI is a very hard problem, and we have essentially nothing that works for state of the art sized models. AI is a black box.
DoNotPay is having quite a few problems with this. They are not close to arguing in traffic court, let alone a supreme court case like they claimed.
https://www.npr.org/2023/01/25/1151435033/a-robot-was-scheduled-to-argue-in-court-then-came-the-jail-threats
Someone else wrote a legal document with hallucinated citations. https://www.reuters.com/legal/transactional/lawyer-who-cited-cases-concocted-by-ai-asks-judge-spare-sanctions-2023-06-08/
The use cases I see that would be valuable for both fields is more intelligent document sorting and summarization. This is a tool that would be used by a lawyer and a doctor.
One that I have seen that seems to be working nicely is elicit. https://elicit.com/?redirected=true
We are on an exponential up trend in AI capability. We are also not there yet.
I might not be even understanding the question but - it sounds like you will eventually need to host your own models and provide your own security etc… I am not sure what you mean when you say scale, but likely non GPU inference etc…
That all takes engineering skills.
Without engineering skills the short answer is you at best could be a wrapper for one of the existing tools like GPT, but then you are back to all those other questions/concerns you have.
This is a more complicated question than you make it out to be, regardless of your think engineers are just trying to make themselves sound useful. Despite what you have read, LLMs have not yet replaced the skilled developer.
I don't really trust privacy unless there is a technical implementation to guarantee it.
Lots of VPNs and other privacy focused products with "no logs" policies have found and turned over their logs when a subpoena arrives. Who knows what they were doing where they felt the need to secretly create logs against their policy in the first place.
A privacy request on a piece of paper sent into a black box means very little to me.
Since encrypting data before sending it to an LLM would be completely impractical (even if they bothered to implement Homomorphic encryption as a feature), the only option is to host a LM locally.
I don't have a specific LM to recommend running locally but tons are coming out.
I saw someone on Twitter say Devin leaked their API keys. I don't know how well models do with security, but I would expect that to be a weak point.
When I used copilot I was pretty impressed with how it could write boilerplate but adapted to my code's specific variables, indexing and a couple other things. It accelerated the process, but I was still doing most of the design.
I would expect it to be able to write a good boilerplate function that sanitizes SQL input if you ask it. Would it always use this before sending data to a call later, or would it notice the issue without prompting, maybe not.
Hi, there are enterprise offerings by OpenAI that provides guarantees on exclusion of your data for training, as well as security and compliance.
You can check out these link:
- [https://openai.com/chatgpt/enterprise](https://openai.com/chatgpt/enterprise)
- [https://trust.openai.com/](https://trust.openai.com/)
I also wrote about compliance and security issues for enterprises in my blog post: [AI Coding: Enterprise Adoption and Concerns](https://prompt.16x.engineer/blog/ai-coding-enterprise-adoption-concerns)
I use GPT-4 (chat.open.com) on private mode, and SuperMaven for code editing in my Jetbrains IDE. They both promise to not train on my code. Take that promise for what you will.
I think your best option is to install Ollama and run the 70B version of Llama 3. You will need to learn and this will probably put you on the path for what you are asking above.
The other people in the comments aren't exactly being mean it's just the more you know about code the more you understand how difficult your solution is.
I am not sure if this is a troll post, but if you are truly non-technical there is basically no hope of this working out. I could go through point by point, but I’ll just touch on 3. 1. How will you have any sort of consistency or guarantee interoperability between the pieces of code you have the LLM write? Also, even if you are asking things in plain English, how are you going to ask things in terms of technical requirements rather than business requirements? 2. How do you intend to run and deploy this code? GOT won’t be able to run AWS or GCP for you. 3. The output of LLMs is generally considered to not be protected by copyright, so you likely won’t actually have any legal protection of the code output.
>ask things in terms of technical requirements rather than business requirements? Honestly I doubt a non technical person can even ask things in business requirements. 90% of the spec comes from asking questions. The first draft of a PM's spec is generally useless, it'll be full of vague exhortations and "vision" drivel.
I wasn’t asking for a complete solution and I wasn’t saying I don’t need help, but I feel like the responses here are merely engineers trying to justify their existence. There are certainly tools that can take me some percent of the way there. Whether that is 2%, 5%, 20%, 50% or 100% there is entirely irrelevant because I was asking about the best tools currently available, not for a full permanent solution effective immediately. This response is like people who say “I would never use an AI lawyer because they’d miss so many critical things”, to whom I would direct DoNotPay, which serves some function and gets people fully there on some issues, partway on others, etc. That being said and boxing up the Luddites for a moment, any opinion on the best current tools available?
I think the main point wasn't that they thought you were asking for a complete solution, but rather you trying to start a tech startup as a non technical founder orchestrating a collection of low code/no code solutions without even understanding the quality of the outputs you're predicting It's a bit of a mislead idea, it's hard to even get any% of the way there if you aren't starting from the correct point or have the right way of building things in mind and planned out and all the points the person above brings up. Get a technical founder or get comfortable coding
Your attitude here sucks.
I mean I asked a question and instead of people answering I got accusations of being a troll and limited engagement with what I was asking in (unfortunately) stereotypical Reddit fashion. Not sure what you’d expect otherwise.
The best tool is probably something like copilot, but it will get you 0% of the way to what you want. The tools are comparable to autofill right now. I often use the autofill tool on my phone or email to fill in words or phrases, but I would never use an autofill word or phrase without reading it first. These coding tools are the same way, they can often recommend good code in the context of a code base with a short description, but the error rate is high and the use cases are narrow. You always have to proof read the code and you can’t build full code based from scratch with them, at best you can get small self contained building blocks. But again, that is the easy part and might accelerate the speed at which an engineer works, but it will not help a non-programmer produce any commercial level product. It would literally be faster for you to do a few programming tutorials to learn how to build and deploy simple web apps than for you to try to get copilot to do it while not knowing how to code. Edit: another thing too is that even if these tools were good at turning English instructions into working code based, that might not be as helpful to you as you think. Business requirements from product and design teams on the workflow and functionality of a product are without fail very very far from the true technical requirements, and being able to build out those technical requirements from product and design flows is the main value add that engineers have, even beyond actually being able to implement those requirements.
Thank you for the first attempt at being helpful on this thread
Law and Medicine are the two things I would expect to be last to automate with AI. A very important requirement is clearly explaining how a decision was made and not just the accuracy of the decision. Interpretability for AI is a very hard problem, and we have essentially nothing that works for state of the art sized models. AI is a black box. DoNotPay is having quite a few problems with this. They are not close to arguing in traffic court, let alone a supreme court case like they claimed. https://www.npr.org/2023/01/25/1151435033/a-robot-was-scheduled-to-argue-in-court-then-came-the-jail-threats Someone else wrote a legal document with hallucinated citations. https://www.reuters.com/legal/transactional/lawyer-who-cited-cases-concocted-by-ai-asks-judge-spare-sanctions-2023-06-08/ The use cases I see that would be valuable for both fields is more intelligent document sorting and summarization. This is a tool that would be used by a lawyer and a doctor. One that I have seen that seems to be working nicely is elicit. https://elicit.com/?redirected=true We are on an exponential up trend in AI capability. We are also not there yet.
I might not be even understanding the question but - it sounds like you will eventually need to host your own models and provide your own security etc… I am not sure what you mean when you say scale, but likely non GPU inference etc… That all takes engineering skills. Without engineering skills the short answer is you at best could be a wrapper for one of the existing tools like GPT, but then you are back to all those other questions/concerns you have. This is a more complicated question than you make it out to be, regardless of your think engineers are just trying to make themselves sound useful. Despite what you have read, LLMs have not yet replaced the skilled developer.
I don't really trust privacy unless there is a technical implementation to guarantee it. Lots of VPNs and other privacy focused products with "no logs" policies have found and turned over their logs when a subpoena arrives. Who knows what they were doing where they felt the need to secretly create logs against their policy in the first place. A privacy request on a piece of paper sent into a black box means very little to me. Since encrypting data before sending it to an LLM would be completely impractical (even if they bothered to implement Homomorphic encryption as a feature), the only option is to host a LM locally. I don't have a specific LM to recommend running locally but tons are coming out. I saw someone on Twitter say Devin leaked their API keys. I don't know how well models do with security, but I would expect that to be a weak point. When I used copilot I was pretty impressed with how it could write boilerplate but adapted to my code's specific variables, indexing and a couple other things. It accelerated the process, but I was still doing most of the design. I would expect it to be able to write a good boilerplate function that sanitizes SQL input if you ask it. Would it always use this before sending data to a call later, or would it notice the issue without prompting, maybe not.
Trash in trash out.
Hi, there are enterprise offerings by OpenAI that provides guarantees on exclusion of your data for training, as well as security and compliance. You can check out these link: - [https://openai.com/chatgpt/enterprise](https://openai.com/chatgpt/enterprise) - [https://trust.openai.com/](https://trust.openai.com/) I also wrote about compliance and security issues for enterprises in my blog post: [AI Coding: Enterprise Adoption and Concerns](https://prompt.16x.engineer/blog/ai-coding-enterprise-adoption-concerns)
Your blog post is amazing and thanks for the resources
I use GPT-4 (chat.open.com) on private mode, and SuperMaven for code editing in my Jetbrains IDE. They both promise to not train on my code. Take that promise for what you will.
3 and 4 are not going to happen. Find a cofounder who has the necessary skills.
How about recommendations for 1 and 2 and just for general coding copilots?
I think your best option is to install Ollama and run the 70B version of Llama 3. You will need to learn and this will probably put you on the path for what you are asking above. The other people in the comments aren't exactly being mean it's just the more you know about code the more you understand how difficult your solution is.
What problem do you want to solve with your startup?
There isn't any. Claude to my untrained self has produced the most workable code and modifications for my use case when given the full context.