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How can I effectively manage LLM context and history for projects like Jaxon Inc?

Tired of Repeating Yourself? How to Master LLM Context and History

Let's be honest – constantly re-explaining your project, re-uploading files, and re-pasting code into your AI chats is a major time sink. I've been there. Nothing kills productivity faster than that repetitive process. It's like starting from scratch every single time. So, how do you actually solve this? Because, frankly, a new chat should know what you're working on, right?

The Core of the Challenge: LLM Context and What to Do About It

In my experience, efficiently managing LLM context and history comes down to a few key strategies:

  1. Project-Specific Setup: The best approach involves creating dedicated projects for each area. This means your AI knows the scope and has access to relevant data. Think of it like having your project's "brain" always ready to go.
  2. Data Persistence: Your AI needs to hold onto the context. So, you can load in website links, documentation, and anything else it needs.
  3. Clear Prompts: Always start with a clear project summary. A good prompt sets the stage, and you can build on it as you go.
  4. Model Flexibility: Experiment with different models (GPT-3, GPT-4, etc.). Sometimes, one is more suitable for a particular project.
  5. Cost Awareness: Track your API usage and costs. Understanding this can drastically improve efficiency. No one wants a bill they didn't expect!
  6. Organized Files: Centralize your files, links, and code snippets. It helps keep everything in one place.
  7. Iterate and Refine: Your system will evolve. So, test new ideas and adjust until it feels like it's working smoothly.

I found I'm able to produce more efficient results after taking this approach over time. For instance, I work with a client, "Jaxon Inc", and I create a whole context setup specific to them. It gives me a huge leg up.

The Secret Sauce: Making it Work for You

The real magic comes in when you start treating your AI chat like a long-term project. Each new chat builds on the previous one. The more context your LLM has, the smarter and more useful it becomes. It's like having a super-powered assistant that remembers everything.

Leveraging Specialized Tools

I've found that the right tools can make all the difference. It's not just about the AI itself but the entire workflow.

How Contextch.at Fits In

I recently started using Contextch.at, and honestly, it's a game-changer. When I work with Jaxon Inc., I can start a new chat knowing my data's already loaded. It's like having a whole project setup in advance. Having the right tools matters!

I like the fact that it handles multiple projects, has the tools to adjust models, and will calculate costs. You can bring in your website, all your crucial files, and Github repos. It has saved me a ton of time and energy. I highly recommend it.

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