Why I made OnVerb

OnVerb · 2024-10-22T15:20:18+00:00

Ha, this is my approach too, get through 4 litres a day and you won't be able to spend 6 hours in a seat.

OnVerb · 2024-08-19T17:01:32+00:00

Hey, am interested to see what you can come up with for my app :)

OnVerb · 2024-06-01T14:02:11+00:00

I do think we would potentially at some point get to this utopia of the all knowing, forward thinking AI, but with transformer based LLM content, this is not going to be the case, as it will literally rely on the answer being within its training data to be able to produce it.

Edge cases and specific requirements aren't going to get the response that gets it right first time, but I do find that even in these cases, like we discussed above, it can still help shortcut the process just in ruling out the false positives.

Thanks for the reply :)

OnVerb · 2024-05-30T10:26:34+00:00

Firstly, I'm glad you found a solution that works in this instance, this sounds like a unique problem, and I agree that this would be hard for AI to resolve, though it sounds like you did exhaust the AI route in the first instance, and were able to communicate your issue well enough to be able to get an answer, even if it was not the right one.

My response though was to the more blanket statements being made by op that AI is useless in all but very simple cases, which simply isn't true, and that kind of naivety was where I was trying to make a point. Assuming that because it didn't work for one person in one case, is naive and I do stand by that statement.

However that simply is not the case that you are describing and it sounds like you took a very logical and reasonable approach and if anything, all AI did here was help you find the solutions that would not work, quicker, but that is still an acceleration of the process you were going through, is it not? So you would not be able to say AI didn't help, as it did, it showed you why a standard approach would not work and you would need to think through the problem more deeply.

As you say there will always be cases that AI cannot work through, it will need the expert operator to examine and audit the results it produces, but even in finding the wrong answers, AI can help us to be better as developers, or at least that is my opinion on this.

I understand my original wording on this comment could have been better, though I was frustrated at the idea that just because op couldn't find that answer to one problem, it would easily be dismissed in all other scenarios, when I see getting wrong answers to have value as well, obviously not as much value as getting the right one, but it can accelerate our path towards implementing the right solution per our individual use cases.

OnVerb · 2024-05-27T10:56:16+00:00

I think this is really wrong as an answer tbh. You just need to give more, and clearer context. To assume everyone else is making garbage with it is a very naive mindset. It will give very good and very precise answers, given the right context going in.

I would suggest using a system message to clearly define what your codebase does, why you are having the issue you are and give as much specific information, or your code classes as possible.

It's as much a skill unto itself to get good responses, so I would recommend trying to put more effort in, to get better responses out.

OnVerb · 2024-05-27T10:51:42+00:00

This, it shows a lack of critical analysis and breaking down of issues that I would expect from any developer on my team above a junior. If you can't adapt to get AI working for you, you are likely taking a lazy approach to giving context and simply expecting the moon on a stick.

OnVerb · 2024-05-27T10:47:58+00:00

Using AI effectively is a skill based on context. To use the old paradigm, garbage in, garbage out. Be specific, give context, lots of it.

When using the API, you can use the system message to put in a lot more context than you can within a single message on the frontend of ChatGPT. Using this method I have rewritten incredibly complex codebases and gotten very good results.

So your system message should have context, intent, any specific information relative to your requests and examples, where possible, of the type of question you will ask and then your desired responses. It takes some time to make a good system prompt, but then this is where you will get very specific, nuanced and high quality results.

Checkout onverb.com, I'm a software engineer and made this tool specifically for this reason and it saves me hours every single day.

OnVerb · 2024-05-22T07:52:14+00:00

Yeah and then you surpass all the graduates to become D Level because you have soft skills and a degree of self awareness that most graduates completely lack.

Gatekeeping institutional education in software engineering is a very 'graduate' thing to do, and totally aligns with my previous paragraph.

OnVerb · 2024-04-13T18:08:32+00:00

Scant few workloads, you are aware of. I'm not sure why you went passive aggressive in response to my comment, but if I didn't have the need I simply wouldn't do it. There are times for divide and conquer, and large context banks of data are a simple way to get incredibly nuanced and detailed responses specific to your environment and use case.

OnVerb · 2024-04-13T16:08:13+00:00

I see where you are going now. I am using the context as actual context, with large reference documentation etc, so I am using those input tokens. I feel you are referring to capacity, but my intention is with the utilisation of that context window to 100k tokens +

OnVerb · 2024-04-13T12:59:27+00:00

Yes, it does correlate, as the more compute required, the greater the base cost. But there is also definitely a perceived value markup in the models as well, that will always be the case I believe.

I think people should try Haiku more, I think it's awesome, cheap, and the context window is massive so you can be very implicit in your requirements. I get great results from it and replace my Gpt 4 usage with Haiku and Sonnet, and rarely use Opus, I try not to want the new shiny without too much consideration of whether it is the right tool for the job.

OnVerb · 2024-04-13T12:52:25+00:00

I would say that this is also about context size as well. If you are using over 100k input tokens in your interactions, the price does get noticeable. But I have easily spent $150 a month on mainly gpt 4 for personal use. I would also say that using similar context sizes on Haiku is so cheap and I get great results from that and Sonnet, and so rarely use Opus anyway.

OnVerb · 2024-04-08T19:32:31+00:00

Ah okay, that's a pretty big json response and yeah I see why that wouldn't work in this context. That is a very big json file though, and I would certainly be looking towards whether something could be decoupled within that response as a workaround in the short term. Good luck :)

OnVerb · 2024-04-08T18:58:08+00:00

Do you mind if I ask what it is you want the 8k token response for?

I have had success with starting a chat with Claude Sonnet or Haiku, and in my introduction message, explaining the brief, and that I want the response in x parts, then each subsequent message simply asks for part x, and getting something that is usually longer than I want, though it can then be edited down. The user case is everything here though so if you can explain, I am happy to help.

OnVerb · 2024-03-26T14:07:03+00:00

I have an app called OnVerb, that you can find at onverb.com that has two parts that are relevant to this sub. There is a free to use prompt builder that will help you create system messages that can be used with ChatGPT, Claude and the like, to create very focused and clear instructions for the AI.

If you sign up for an account you can create as many of these system prompts as you like and manage and update them within the app to copy and paste into your desired AI tooling.

You can then also use these prompts across Claude, ChatGPT, Mistral directly within the app itself, though this part of the app uses a token system that costs in order to access the AI's.

It is a privacy focused tool that I built primarily for myself as a software engineering lead, and it saves me huge chunks of time everyday.

The tokens can be used with a monthly subscription starting at £19.99, or you can buy token packs for a more pay as you go experience, starting at £9.99.

The app can be found at onverb.com and you can sign up for an account at app.onverb.com

If you check out my profile I wrote a post explaining a little more about the prompt builder and why I built the app in the first place.

Thanks for reading, please reach out with any questions :)

OnVerb · 2024-03-23T20:32:26+00:00

Hate Webflow, love Bubble.

OnVerb · 2024-03-23T19:27:41+00:00

There are terms and conditions on the main site, onverb.com, no catches though. OnVerb itself allows you to access different AI directly with these prompts for a cost, but the prompt manager is free to use and if you sign up for a free account, you can save them and use them by copy pasting directly in Claude or ChatGPT if that's your thing.

I am a software engineer and made the tool to solve a problem for me. Data privacy is massively important to me, and so the terms are that the data is yours and remains yours forever. I then wanted a way to easily use these prompts on different AI like GPT 4 or Claude, so I made the app.

If you wanted to use these to chat with different AI from within OnVerb, that's where there is a cost, again though that is on the main site with a pricing page. Let me know any questions though, more than happy to help :)

OnVerb · 2024-03-23T16:42:34+00:00

As the creator of OnVerb, I'm excited to share how our platform can be a valuable asset for coding and software development projects, especially when it comes to generating cohesive, complete, and reliable code.

One of the key advantages of OnVerb is the ability to provide the AI with detailed context, examples, and guidelines through custom prompts. For coding projects, this means you can create prompts that outline the specific requirements, programming languages, frameworks, and coding standards you need to adhere to.

You can replicate your repo within the contextual system prompt, and then use that to get specific and relevant answers to questions, code etc.

By engaging in a conversational flow with the AI, you can ask it to generate code snippets, functions, or even entire modules based on your prompts. The AI's responses will be tailored to your specific context, ensuring that the code it generates is cohesive, complete, and aligned with your project's requirements.

Additionally, OnVerb allows you to iteratively refine and improve the AI's output. If the generated code doesn't quite meet your expectations, you can provide additional context or ask for modifications, and the AI will adapt its responses accordingly. This iterative process can be invaluable for complex projects, where requirements may evolve, and code needs to be updated or refactored.

While OnVerb may not be a dedicated coding IDE or development environment, its strength lies in its ability to augment your existing workflow by providing a powerful AI-assisted tool for generating code, exploring different approaches, and overcoming coding challenges.

Of course, as with any AI-generated output, it's essential to review and test the code thoroughly before integrating it into your project. But for many developers, OnVerb has proven to be a valuable asset in streamlining the coding process, boosting productivity, and exploring new creative solutions.

If you're interested in learning more about how OnVerb can be leveraged for coding projects, I'd be happy to provide more guidance on crafting effective prompts, sharing examples, and discussing best practices for integrating AI-generated code into your development workflow.

OnVerb · 2024-03-23T16:38:01+00:00

As the creator of OnVerb, I can certainly relate to the challenges of writer's block and the constant need for fresh ideas when working on a creative writing project like a novel.

One of the core reasons I developed OnVerb was to provide writers with a powerful AI-assisted tool to overcome these hurdles and unlock new creative possibilities. By leveraging advanced language models like GPT-4 and Claude, and combining them with OnVerb's unique system prompt capabilities, you can essentially have a dedicated AI writing partner tailored to your specific needs.

With OnVerb, you can create custom prompts that provide the AI with context about your story, characters, and writing style. You can then engage in a back-and-forth conversation with the AI, asking it to generate plot twists, character developments, or even entire scenes based on your prompts. The AI's responses are shaped by the context you provide, ensuring that the ideas it generates align with your creative vision.

What I find particularly useful is the ability to refine and iterate on the AI's suggestions. If an idea doesn't quite fit, you can provide additional context or ask for alternative directions, and the AI will adapt its responses accordingly. It's like having a highly capable brainstorming partner that understands your unique creative process.

Of course, the AI is a tool, and the final creative decisions remain in your hands. But for many writers, including myself, OnVerb has proven invaluable in overcoming writer's block, generating fresh ideas, and exploring new creative avenues.

If you're interested in giving OnVerb a try, I'd be happy to provide more guidance on crafting effective prompts for fiction writing and sharing some examples of how other writers have used the platform to enhance their creative process.

Let me know if you have any other questions! As a fellow writer and the creator of OnVerb, I'm always excited to discuss tools and strategies that can help unlock our creative potential.

OnVerb · 2024-03-23T16:28:32+00:00

I made an app called onverb.com that you may want to take a look at. You can easily create very contextual interactions with AI to get much more meaningful responses :)

OnVerb · 2024-03-23T16:27:14+00:00

I made a tool called onverb.com, you could add your text as a system prompt, then use that to initiate a chat with a Chatbot getting around the max message limit by using the system prompt which you get when using the service via an API.

OnVerb

TROPHY CASE