Why I Use ChatGPT

Big Idea

The best AI tool is the one you actually learn to use deeply enough that it becomes part of how you work.

This lesson explains why ChatGPT is the primary tool used in this course. The point is not that every person must use only ChatGPT. The point is that the tool becomes more valuable when it carries context, remembers preferences, works with your content, and supports ongoing projects.

Why ChatGPT

There are many large language models available, and new ones are being introduced all the time. Some users may prefer one tool for research, another for writing, and another for editing or coding.

That is fine once you are comfortable. But when you are still learning, it is often better to go deep with one tool first. This course uses ChatGPT because it combines several useful capabilities in one place: memory, context, file uploads, projects, custom GPTs, image generation, voice capture, and coding help.

The main reason is practical. It is not only a writing tool. It can become a system partner.

Memory and Context

One reason ChatGPT is useful is memory. It can learn certain preferences and adapt to how you work. Over time, it starts to understand recurring terms, projects, and expectations.

For example, if you repeatedly talk about atomic chunks or WorkFlowy format, the tool begins to understand those ideas. You do not have to explain them from scratch every time.

That makes the tool more useful for ongoing work. It is not just a one-time response generator. It becomes something closer to a working relationship, where each new conversation can build on prior work.

Projects and Custom GPTs

ChatGPT also lets you organize work through projects and custom GPTs.

A project gives you a defined space for related files, conversations, and instructions. If you are building a tool, developing a course, or organizing a larger workflow, a project keeps the source materials together so separate chats can still work from the same context.

A custom GPT is more like a small purpose-built assistant. You give it instructions for a specific recurring task and then refine it until the output becomes more consistent.

The lesson used a recommendation-letter example. A high school counselor could collect student brag sheets, upload the information, and use a custom GPT to draft individualized letters. The same concept could apply to insurance FAQs, renewal explanations, proposal language, onboarding notes, or other repeatable agency tasks.

Working With Your Content and Images

ChatGPT can work with your own files, outlines, spreadsheets, transcripts, and project materials. That matters because the tool is no longer limited to general internet-style knowledge. It can help with your actual work.

It can also generate images. That is useful for presentations, blog posts, course materials, and visual explanations. You may not need images every day, but when you do, having image generation connected to the same tool can save time.

The broader point is that AI becomes more useful when it can operate inside your world instead of only answering general questions.

Building Tools With AI

ChatGPT can also help build things. The renewal extractor shown earlier in the course was created with AI assistance, even without a traditional coding background.

This does not mean AI does everything instantly. Building tools still requires testing, correction, setup, and patience. There will be errors. You will need to give feedback and refine the result. But the barrier is much lower than it used to be.

This style of building is often called vibe coding. You describe the desired result in plain language, AI helps write code, you test it, and then you continue the cycle. For agents who have ideas for internal tools, calculators, extractors, or workflow aids, that is a major shift.

Iteration Is the Skill

The most important skill is not asking the perfect question. The most important skill is learning how to iterate.

The first answer is rarely the final answer. You ask a question, review the response, clarify what you meant, ask for changes, and keep improving it. That process is how the tool becomes useful.

Talk to it like a smart assistant. Give context. Explain what you are trying to accomplish. Tell it what is wrong with the answer. Ask for a different structure, tone, length, or audience. That is where the quality improves.

Use Voice and Use It for Thinking

Voice input can make AI much more useful. Speaking is often more natural than typing because you are less likely to over-edit yourself before the idea is out of your head.

The phone microphone can be especially useful for capturing ideas, brainstorming, and rough drafting. You can speak naturally, even if the idea is messy. Then AI can help organize it.

This is one of the most valuable uses of AI: thinking. Use it to brainstorm, challenge assumptions, explore options, summarize what you decided, and turn the result into notes you can store.

Judgment Still Matters

AI is useful, but it is not always correct. You still need to proofread, verify, and apply judgment, especially when the answer is based on general knowledge or current facts.

The quality improves when the tool works from your curated information. That is why the course keeps returning to knowledge bases, structure, and capture. The better your inputs, the better the outputs can become.

This lesson leads directly to the next one: the limitations of ordinary LLM use. Public AI tools are powerful, but they do not automatically know your agency, your clients, or your processes. That is the gap RAG is designed to close.