I Can't Believe NO ONE Is Talking About ChatGPT Assistants

In this video, we explore the **Assistant API**—a game-changer that simplifies the way developers handle continuous, context-rich conversations with large language models (LLMs) like ChatGPT. Rather than constantly passing previous responses as inputs, the Assistant API allows you to maintain an **ongoing thread of dialogue**, automatically handling truncation and context retention without relying on retrieval augmentation (RAG) or cumbersome prompt chaining techniques.

If you’ve ever struggled with preserving context across multiple prompts or building complex applications that require consistent state, the Assistant API could revolutionize your workflow. Learn how it’s possible to create intelligent, multi-step conversations that feel just like chatting with ChatGPT’s frontend—only this time, it’s all happening through the API, making it easier to scale and integrate into your applications. We’ll cover the benefits, potential use cases, and how this approach compares to traditional prompt-chaining methods. Whether you’re an AI developer, product manager, or curious enthusiast, this deep dive will help you understand why the Assistant API might be the most underrated tool in your AI arsenal.

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**Chapters:**
**0:00 – Introduction & Overview**
Discover why the Assistant API offers a more “human” style of conversation with LLMs, preserving context without manual prompt chaining.

**1:00 – The Limitations of Traditional Prompting**
Learn how developers have been forced to repeat past responses or rely on RAG solutions to simulate memory, and why this is inefficient.

**2:00 – How the Assistant API’s Threads Work**
See how threads maintain conversation continuity automatically, so every message builds on the last without extra code or storage layers.

**3:00 – Automatic Context & Truncation**
Find out how Assistant API handles large conversations, managing token limits behind the scenes to keep your sessions flowing smoothly.

**4:00 – Potential Use Cases & Applications**
Explore how continuous threads can enhance complex workflows, from building advanced chatbots to automated content generation and beyond.

**5:00 – Comparing Against Traditional Approaches**
Understand why the Assistant API might outperform the old “prompt + output” chaining method, saving you time, complexity, and tokens.

**6:00 – Conclusion & Next Steps**
We wrap up with final insights, empowering you to start using the Assistant API in your own projects and unlock its full potential.

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**Keywords & Topics:**
- Assistant API
- ChatGPT API
- Conversation context
- Continuous conversation
- Thread-based dialogue
- AI memory management
- Prompt chaining
- Retrieval augmentation (RAG)
- LLM best practices
- Developer tools
- AI integration
- HarborSEO

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**Hashtags:**
#AssistantAPI #ChatGPT #OpenAI #LLM #AIConversations #PromptEngineering #RAG #AIIntegration #ContextRetention #DeveloperTools #TechInnovation #HarborSEO #MachineLearning #ArtificialIntelligence

[nobotty]

Don't know if anyone else has to do this, but.If you are using the GPT web page for projects. Delete your previous (NOT CHATS) project threads (memories) . AS you only have so many that it will hold and you previous project data can interfere with your new project. It will not matter if you start a new chat or not. Your project Will bleed through to the others.

[most]

I still think you should be able to organize and consolidate chats so your convos stay relevant and your not having to constantly read old wall of text to make sure chart gpt is up to date on what you're currently chatting/requesting about

[BlueJDev]

One of the reasons I don't use assistant is from what I read (mind it was many months ago) that it's quite costly, especially when you introduce files into the convo/thread. I think it said at the time they charge per GB per hour or day that the thread is stored, meaning if you forget to drop a thread you would continue to get charged for a GB of storage, regardless of usage, constantly until files are deleted... They may have updated since though..

[ic_jason]

I agree this would be nice, but one thing to keep in mind is that you may want your system to be LLM-agnostic, in which case it might be best to continue to manage the context yourself using your own structured data. That way you're only ever tapping into the raw LLM brain, and any suitable model can be swapped out.

[ecomcavalry]

Where is thread stashed at? As all of my ai personas work great as an assistant as i have been using them it would be good to know where the threads are stashed at

[antoniox]

Don't Projects do the same thing?

[Brodielegget]

Also functions inside assistant is very useful as well

[MyUpsideDownLife-SKR]

Yep.. been driving me nuts for ages.. thanks Hamish! This is great!

[jmg]

I don't fully understand what's the difference between threads and just chainning every message and sending that back. Maybe it's like a storage unit of the conversation that's stored on OpenAi's end, similar to a regular chatGPT conversation history.

Anyway side thought: isn't the problem with bundling all the previous messages in the new prompt to be sent to a model, is that if the conversation history gets too large you're going to be paying exponentially more per prompt submitted because its an enormous corpus of words from both you and the model combined for the entire chat history. Because I understand it, every word or partial word is a token you're being charged for.

[calvincrane]

You can't always trust what people think they know even on official forums. I have seen some incorrect information in this group.

[rldays]

PI can have an ongoing conversation. I know this because I tested it.

[Adam-yfss]

This video came at the right moment when I had this question.

[isaac_lopes_seo]

Thanks again man. I'm stalking all your videos =]

[Swooshii-ue]

Thumbs down because it was not dark mode the screen was too bright to be watching this video right now in the dark

[kd-zqoq]

"INSANE" !!!! lol everything is INSANE on this channel ...