WEBVTT

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If you spend any serious time with advanced AI

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chatbots, you probably know the biggest headache.

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It's context drift. You spend ages detailing

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a marketing brief, defining your audience, setting

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the tone. Perfect. Then you ask a quick question

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about, say, weekend plans. And suddenly, the

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AI is suggesting beach resorts right in the middle

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of your formal client memo. You find yourself

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constantly repeating things, restarting chats.

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The AI forgets what you were doing just five

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minutes ago. Well, it's frustrating. Kills efficiency.

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It really does, yeah. And you feel like you're

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almost fighting the tool, instead of it helping

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you. But there is actually a surprisingly powerful

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solution, one that a lot of users, even experienced

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ones, seem to overlook completely. It's called

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Chat GPT Projects. Prolix, OK. Yeah, and this

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is, I think, genuinely the most effective way

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to get that consistency and generate really high

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quality results over the long term. And the great

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news, this is now available for everyone. Even

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if you're on a free account, you can use this.

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It is. So our mission today, it's pretty straightforward.

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We need to unpack what projects actually are,

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how they're fundamentally different from, say,

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custom GPTs, which people might know, and maybe

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most importantly, nail down the three essential

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parts you absolutely need to set up to create

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like a truly focused expert AI assistant just

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for your specific work. OK, that sounds exactly

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like what's needed. Let's dig into the mechanics

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then. How do they work? Let's do it. So the way

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I've started thinking about them is like private

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work rooms inside chat GPT, almost like custom

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-built spaces. They don't seem designed for just

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quick... one -off questions, you know, more for

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ongoing long -term work where the knowledge needs

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to build up. That's a perfect analogy. Yeah,

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a private workroom. Or think of them as dedicated

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AI assistants, each one totally focused on a

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single domain. Maybe one handles all your marketing

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copy, another manages your coding questions.

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And the key feature, the absolute core of it,

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is dedicated memory. Dedicated memory. Exactly.

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They remember everything within that project.

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All the past chats, every single file you've

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uploaded, all the instructions you've given it.

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It's all stored. neatly right there in that one

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space. And because that knowledge base is isolated,

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the AI stays laser focused, always on that specific

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topic. OK, so if these work rooms are meant to

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keep things separate, how do they actually stop

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that confusion? Like, how does it prevent my

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random search for a trip to Dalat from bleeding

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into my serious marketing strategy project? What's

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the barrier? Well, projects keep their knowledge

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totally separate. So you get focused, consistent

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results without that random contamination. Got

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it. That makes sense. Now, a lot of people listening

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might have used custom GPTs before to personalize

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things. So it's really important to understand

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the difference here. If a project is that workspace,

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that workroom, a custom GPT is more like a specialized

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tool. It's built for one specific repeated action.

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Like maybe it only generates email subject lines

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or it checks grammar in a very specific style.

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You kind of set it up once for that function,

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and it doesn't really change much after that.

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Right. OK, so GPTs are tools, but projects. They

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sound more like living documents or evolving

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workspaces. They grow and update as you use them

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more. You're not just doing one task in the project,

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you're managing a whole area of work. It's an

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ongoing thing. Exactly. Living documents is a

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great way to put it. And the core difference

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really comes down to where the intelligence comes

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from. A project's knowledge is based on your

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initial instructions, yes, and the files you

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upload, but also the entire history of every

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single chat within that specific project. custom

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GPTs. They pretty much just rely on how you set

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them up initially. That's their knowledge base.

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So the chat history itself becomes part of the

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project's brain, essentially. Precisely. Think

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about, say, managing a YouTube channel with a

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project. You go back to it every week, right?

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Brainstorming ideas, drafting scripts, because

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it's building that full history of every interaction,

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every decision, every script draft, the suggestions

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it gives you three months down the line. They'll

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be incredibly accurate because it knows your

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channel's whole journey, your style, your topics,

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what worked before. So if projects gain knowledge

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from the conversation history, does that mean

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they actually get smarter over time, more tuned

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in to my specific needs? Yes, they learn from

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every conversation, getting smarter and more

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precise about your task over time. Wow, OK. But

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that learning, that growth, it totally depends

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on keeping the data clean, isolated. Which brings

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us to, honestly, the first critical thing you

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need to do before anything else. The memory setting.

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The memory setting. Okay, why is one setting

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so crucial right at the start? Because of that

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context contamination we talked about, it's a

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default setting issue, really. By default, when

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you create a new project, it can actually access

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memories from your other chats, your normal,

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everyday, random chat GPT conversations. Oh,

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really? Yeah. So it might remember you were looking

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up, I don't know, Italian seasoning recipes last

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Tuesday, and now it's trying to stick a weird

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spice metaphor into your serious corporate financial

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report. That's bad news for Focus. Definitely

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don't want that. No. So immediately, the first

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thing you do... Change the setting to Project

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can only access its own memories. Full stop.

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That stops it pulling in random stuff like your

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recipes or that Daylat trip plan. It keeps the

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project's brain focused only on the project job.

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And honestly, this is a bit of a vulnerability

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moment here, but I still wrestle with prompt

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drift myself sometimes, even after using these

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tools for ages. This setting. It's like your

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main defense. It stops those weird, irrelevant

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mistakes before they even happen. It ensures

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your specialized AI stays specialized. So just

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switching that memory setting to project only,

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does that significantly cut down the chances

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of the AI making those off -topic, irrelevant

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mistakes? Absolutely. Isolating the memory ensures

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the AI stays laser -focused on its job. No distraction.

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OK, crucial step number one. Isolate the memory.

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Got it. mid -roll sponsor, read placeholder.

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All right, we locked down the memory. Now let's

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talk about building the project itself. You mentioned

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three pillars for setup. What's the first one?

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The first pillar is custom instructions. And

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this is so much more than just telling it to

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be polite. This is basically where you write

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the job description for your AI assistant. You're

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setting the rules of engagement, eliminating

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ambiguity. You define its role, its primary goal,

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the format you want answers in, and the overall

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tone. Most people probably just put in something

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vague about tone, like be friendly. Yeah. But

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you're saying getting really specific here is

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key. That's what makes it a real assistant. Exactly.

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Specificity is power here. Let's say you're a

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writer planning social media. Define the goal

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clearly. Help me plan content for a Facebook

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fan page about pets. Simple. Define the format.

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Always answer using bullet points. Do not write

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paragraphs longer than five sentences. Super

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clear. And the tone. Friendly, fun, enthusiastic,

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clearly loves animals. And you can even add special

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requests. Like if my request isn't clear enough,

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please ask me clarifying questions before answering.

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That saves time. Right. Prevents bad outputs.

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Totally. And the poodle example really shows

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this power. You could define the role as content

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manager assistant for a poodle enthusiast fan

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page. Then you specify the format. Each post's

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idea needs a catchy title, three to four bullet

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points explaining the idea, a clear call to action,

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you know, a CTA, telling people what to do next,

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and always suggest a relevant picture or video

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type. That's incredibly detailed. But that detail

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is what gives you consistent high -quality output

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every single time. No guesswork for the AI. Okay,

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custom instructions is Pillar 1, what's Pillar

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2? Pillar 2 is the knowledge base. This is the

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project's brain, basically, where you feed it

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the specific data it needs. You upload your files

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here, PDFs, maybe text documents, transcripts,

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internal guides, whatever is relevant. But the

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key here is quality knowledge, not just dumping

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everything in. Relevance is crucial. And there

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are limits on files, right? Yeah, there are.

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It varies by plan. Free users get, I think, five

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files per project right now. Plus in education

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get 25. Pro and enterprise get up to 40. But

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honestly, Even five is plenty if they're the

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right five files. Five super relevant, high quality

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documents beat 40 random, vaguely related ones

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every single time. So be selective. Don't just

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upload your whole hard drive. Exactly. Quality

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over quantity. Focus. That limit kind of encourages

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you to think strategically about what knowledge

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is truly essential. Make sense. Okay. Instructions,

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knowledge base. What's the third pillar? The

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third pillar is tools. Projects can optionally

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access special tools to enhance their capabilities.

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To of like what? Well, there's Canvas, which

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is really cool. It lets the AI help you create

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documents, presentations, even quizzes right

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inside the chat interface. There's deep research,

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which can scan hundreds of websites to gather

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in -depth information on a topic. Very powerful.

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Then you have image generation for creating visuals

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and the standard web search for pulling in the

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latest real - time info. So should we just turn

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all those on? No, definitely not. Here's a critical

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tip. Don't turn these tools on by default. Only

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enable them when you specifically need that capability

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for a particular task. Why? Because you want

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the project to primarily rely on the custom instructions

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and the knowledge base you carefully curated.

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That maintains focus. Use the tool selectively

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as needed. Given those file limits, especially

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for free users, is the best strategy really just

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picking the absolute most vital documents for

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that knowledge base? Absolutely. Quality, focus,

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and relevance are the deciding factors for useful

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AI output. Five great files beat 40 mediocre

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ones. Got it. Let's make this concrete. Can you

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walk us through setting up a project for a real

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world task? Sure. Let's take learning English.

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We'll build an English learning plan assistant.

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So, for custom instructions, the goal might be,

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help me improve my English listening and speaking

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skills. Format. Provide weekly plans in a simple,

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clear table. Tone. Encouraging and patient. And

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a crucial special request. Before creating the

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new week's plan, always ask me if I completed

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last week's goals and what challenges I faced.

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That builds in accountability. Nice touch. Okay,

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what about the knowledge base? What files go

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in there? We need actionable data for the AI,

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so maybe upload. A list of 500 common English

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vocabulary words the learner wants to master.

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A short document listing the learner's most common

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grammar mistakes may be based on feedback from

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a teacher, a transcript from an English podcast

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they like, to analyze style and phrasing. And

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maybe there's score report from a recent English

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test to show baseline weaknesses. OK, specific

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relevant data. Exactly. And here's that smart

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tip you mentioned earlier, a really useful technique.

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Before you even upload files to the project,

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go into a normal, separate chat GPT chat, turn

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on the deep research tool there, ask it something

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like, generate a detailed report on the most

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effective methods for an intermediate learner

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to improve English listening skills. Ah. Let

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it run. Do its thing. Generate that report. Then

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download that report as a PDF or text file. Then

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you upload that curated report into your English

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learning project's knowledge base. Ah, so you're

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using the AI's research capability to create

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high -quality knowledge for your project's brain.

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Precisely. You're feeding it expert -level information

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sourced from the web, but curated and focused.

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Okay, so instructions set, knowledge uploaded.

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What happens next? Then you just ask for your

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plan. Generate my English learning plan for this

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week. The projects looks at your goal, your common

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mistakes file, the vocabulary list, that research

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report, and it creates a specific personalized

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table like day one, watch this specific five

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minute Ted Ed video on topic X, summarize it

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aloud in three sentences, review vocabulary words

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10, 15 from the list focusing on pronunciation

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because it knows that's a weakness from your

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files. The level of personalization sounds incredible.

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It really is because it's all based on your specific

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data and goals stored right there. Okay, let's

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try another one. Marketing. Say we have a new

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product, a smart thermos. Create example. So

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knowledge base first. We upload maybe a PDF with

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all the product features, keeps drinks hot or

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cold for 24 hours, LED temperature display, uses

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316 stainless steel, and maybe another file defining

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our target customer. Office workers, gym goers,

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maybe age 22 to 35. Perfect. Clear product info,

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clear audience info. Now, this is where a tool

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like Canvas could be really useful. You could

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ask the project right in the chat. Create an

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introduction flyer for my new smart thermos using

00:12:24.559 --> 00:12:27.899
the Canvas tool. Use the features from the uploaded

00:12:27.899 --> 00:12:31.450
PDF. And it will build a draft flyer. Yeah. It'll

00:12:31.450 --> 00:12:34.190
pull those features, the 24 -hour stat, the LED

00:12:34.190 --> 00:12:36.049
screen, directly from the file you uploaded.

00:12:36.389 --> 00:12:38.190
It ensures the marketing content is accurate

00:12:38.190 --> 00:12:40.409
and based on the facts you provided. You can

00:12:40.409 --> 00:12:42.730
edit it right there. Yep. You can tweak the layout,

00:12:42.970 --> 00:12:45.899
change text, then share it instantly. get a public

00:12:45.899 --> 00:12:48.480
link, or download it as a PDF, all within that

00:12:48.480 --> 00:12:50.700
dedicated project workspace. That's efficient.

00:12:50.879 --> 00:12:53.500
And what about images? Easy. In the same project

00:12:53.500 --> 00:12:56.259
chat, you could then say, now, generate an Instagram

00:12:56.259 --> 00:12:59.200
ad image for this thermos, include the text,

00:12:59.419 --> 00:13:01.799
keep the taste all day long, and it'll create

00:13:01.799 --> 00:13:04.200
image options for you. Wow, OK. Instructions,

00:13:04.580 --> 00:13:07.899
knowledge, tools, all working together. Exactly.

00:13:08.679 --> 00:13:11.220
Whoa, just thinking about this. Imagine scaling

00:13:11.220 --> 00:13:14.799
this, like an entire company using projects.

00:13:15.179 --> 00:13:18.299
Every team, every department having these dedicated

00:13:18.299 --> 00:13:22.220
expert AI assistants all adhering to the company's

00:13:22.220 --> 00:13:24.220
internal standards using only approved knowledge

00:13:24.220 --> 00:13:27.600
bases. The level of consistency, the domain specificity

00:13:27.600 --> 00:13:31.080
across an entire enterprise. That's genuinely

00:13:31.080 --> 00:13:33.299
transformative potential right there. That is

00:13:33.299 --> 00:13:35.919
a big thought. OK, so these projects are powerful

00:13:35.919 --> 00:13:37.899
because they're focused on their internal knowledge.

00:13:38.200 --> 00:13:40.679
But do they have to be completely cut off from

00:13:40.679 --> 00:13:42.980
the outside world forever? What about new trends?

00:13:43.320 --> 00:13:45.659
Good question. No, they don't have to be totally

00:13:45.659 --> 00:13:48.360
isolated You can smartly combine that internal

00:13:48.360 --> 00:13:51.059
knowledge with fresh online information when

00:13:51.059 --> 00:13:53.360
needed So you're in your smart thermos marketing

00:13:53.360 --> 00:13:55.120
project, right? You've got your features PDF

00:13:55.120 --> 00:13:57.399
your customer profile, but you need the latest

00:13:57.399 --> 00:13:59.620
trends What's hot right now in that market? You

00:13:59.620 --> 00:14:01.279
don't leave the project. You just click that

00:14:01.279 --> 00:14:04.179
little plus icon in the chat input box Temporarily

00:14:04.179 --> 00:14:06.340
enable the web search tool just for that one

00:14:06.340 --> 00:14:09.679
query Exactly. Then you ask, what are the latest

00:14:09.679 --> 00:14:12.080
marketing trends for stainless steel lifestyle

00:14:12.080 --> 00:14:14.159
products relevant to my target audience this

00:14:14.159 --> 00:14:17.279
year? Chat GPT goes out, searches the web, and

00:14:17.279 --> 00:14:19.980
comes back with current insights. Maybe it says,

00:14:20.279 --> 00:14:22.940
focus on sustainability narratives or collaborate

00:14:22.940 --> 00:14:26.220
with KOCs. KOCs. Oh, right. Key opinion consumers

00:14:26.220 --> 00:14:29.539
or key opinion leaders. Basically, real customers

00:14:29.539 --> 00:14:33.000
or influential users who genuinely use and love

00:14:33.000 --> 00:14:36.039
the product rather than just paid celebs. Their

00:14:36.039 --> 00:14:38.120
recommendations carry a lot of weight. Got it.

00:14:38.139 --> 00:14:41.480
So the project finds these new trends. And that

00:14:41.480 --> 00:14:43.639
new information, those trends, that insight about

00:14:43.639 --> 00:14:46.299
KOCs, it gets added automatically right into

00:14:46.299 --> 00:14:48.360
that project's memory, its conversation history.

00:14:48.720 --> 00:14:50.720
So you're efficiently updating your project's

00:14:50.720 --> 00:14:52.679
knowledge with fresh, relevant data from the

00:14:52.679 --> 00:14:54.840
outside world. But you did it strategically.

00:14:55.200 --> 00:14:57.379
Then you just turn web search off again, and

00:14:57.379 --> 00:14:59.820
the focus snaps back to your core internal knowledge

00:14:59.820 --> 00:15:02.100
base. Best of both worlds. That's a smart way

00:15:02.100 --> 00:15:04.600
to keep it current without losing focus. What

00:15:04.600 --> 00:15:06.620
about other, maybe less obvious features? Any

00:15:06.620 --> 00:15:08.779
efficiency boosters people miss? Yeah, a couple

00:15:08.779 --> 00:15:10.799
of good ones. If you have a really great conversation

00:15:10.799 --> 00:15:13.200
going in your regular chat, GPT chat, and you

00:15:13.200 --> 00:15:15.320
suddenly realize, wow, this should be a project,

00:15:15.659 --> 00:15:18.139
you can actually move that entire existing chat

00:15:18.139 --> 00:15:21.519
conversation with all its context directly into

00:15:21.519 --> 00:15:24.039
one of your projects, or start a new project

00:15:24.039 --> 00:15:26.259
from that. Oh, that's handy. Instead of copy

00:15:26.259 --> 00:15:28.899
pasting. Exactly. Keeps the history intact. Saves

00:15:28.899 --> 00:15:31.480
a ton of time if you realize mid conversation

00:15:31.480 --> 00:15:34.179
that it's becoming a long term thing. And another

00:15:34.179 --> 00:15:37.360
one, especially for the mobile app users, voice

00:15:37.360 --> 00:15:40.580
input. Having a spoken back and forth conversation

00:15:40.580 --> 00:15:43.159
with your dedicated project assistant using voice,

00:15:44.019 --> 00:15:46.360
it feels incredibly natural. Almost like talking

00:15:46.360 --> 00:15:49.059
to a real specialist assistant. Really good for

00:15:49.059 --> 00:15:51.019
brainstorming on the go. OK, those are useful

00:15:51.019 --> 00:15:54.129
tips. Now, on the flip side. What are the big

00:15:54.129 --> 00:15:56.470
mistakes people make when they first start using

00:15:56.470 --> 00:15:58.570
projects? Where do they usually go wrong? Good

00:15:58.570 --> 00:16:01.309
question. There are a few common pitfalls. Number

00:16:01.309 --> 00:16:04.190
one, trying to cram everything into a single

00:16:04.190 --> 00:16:07.269
project. Don't create one massive, my whole life

00:16:07.269 --> 00:16:10.429
project. Keep them hyper -focused. One for marketing,

00:16:10.649 --> 00:16:12.990
one for coding help, one for learning Spanish.

00:16:13.509 --> 00:16:17.289
Specific domains. So specialization is key. Absolutely.

00:16:17.970 --> 00:16:21.389
Mistake number two. Rushing through or completely

00:16:21.389 --> 00:16:23.649
ignoring the custom instructions set up, people

00:16:23.649 --> 00:16:25.870
skip this, just give it a name, and wonder why

00:16:25.870 --> 00:16:28.570
it's not very helpful. Those detailed instructions

00:16:28.570 --> 00:16:31.710
are vital. They tell the AI how to be useful

00:16:31.710 --> 00:16:34.169
for you. Right. The job description. Exactly.

00:16:34.870 --> 00:16:38.240
Mistake three. The opposite of being selective

00:16:38.240 --> 00:16:40.659
with the knowledge base, just uploading tons

00:16:40.659 --> 00:16:43.820
of unrelated files. Garbage in, garbage out,

00:16:44.379 --> 00:16:47.120
basically. Quality and relevance matter way more

00:16:47.120 --> 00:16:49.580
than volume. Right. Focus, instructions, quality

00:16:49.580 --> 00:16:52.220
knowledge. What else? The big one we already

00:16:52.220 --> 00:16:54.419
covered. Forgetting to change that memory setting

00:16:54.419 --> 00:16:56.899
to project can only access its own memories.

00:16:57.240 --> 00:16:59.700
That causes instant chaos and undermines the

00:16:59.700 --> 00:17:01.840
whole point. Isolate the memory. Got it. And

00:17:01.840 --> 00:17:04.589
maybe one last thing. Starting a brand new chat

00:17:04.589 --> 00:17:06.970
inside the project every time you use it. The

00:17:06.970 --> 00:17:08.930
real power comes from building on the history.

00:17:09.369 --> 00:17:11.450
Continue the existing conversation thread so

00:17:11.450 --> 00:17:13.829
it learns and remembers context over time. Don't

00:17:13.829 --> 00:17:15.609
keep starting from scratch within the project.

00:17:15.769 --> 00:17:17.609
Okay, that makes sense. Build on the history.

00:17:18.390 --> 00:17:21.190
So let's try to wrap this up. The big idea here

00:17:21.190 --> 00:17:24.029
seems really clear now. Projects are essentially

00:17:24.029 --> 00:17:27.009
about creating expert AI assistants. defined

00:17:27.009 --> 00:17:29.950
by those three key things, your custom instructions,

00:17:30.650 --> 00:17:32.809
the specific knowledge base you feed it, and

00:17:32.809 --> 00:17:34.869
the cumulative conversation history that builds

00:17:34.869 --> 00:17:37.710
up over time. That's it. Instructions, knowledge,

00:17:38.089 --> 00:17:40.819
history. The three pillars. And the main benefit

00:17:40.819 --> 00:17:44.000
is getting consistent, reliable, high -quality

00:17:44.000 --> 00:17:46.819
results that are specifically tailored to your

00:17:46.819 --> 00:17:50.000
long -term tasks or areas of work. Exactly. So

00:17:50.000 --> 00:17:52.460
just to summarize the when to use what's question,

00:17:52.779 --> 00:17:55.200
use projects for anything that's a repeated task,

00:17:55.400 --> 00:17:58.160
requires long -term context, or needs a special

00:17:58.160 --> 00:18:00.819
dedicated knowledge base that you provide and

00:18:00.819 --> 00:18:02.900
control. Your goal with projects is building

00:18:02.900 --> 00:18:05.319
that expert AI assistant that grows and learns

00:18:05.319 --> 00:18:08.150
alongside you for a specific domain. regular

00:18:08.150 --> 00:18:10.809
chats are still great use them for quick one

00:18:10.809 --> 00:18:12.630
-off questions things that don't need history

00:18:12.630 --> 00:18:14.250
or special knowledge you know what's the capital

00:18:14.250 --> 00:18:16.450
of Australia or convert these measurements quick

00:18:16.450 --> 00:18:20.049
in quick out got it projects for depth and consistency

00:18:20.049 --> 00:18:22.930
regular chat for quick hits okay here's a final

00:18:22.930 --> 00:18:24.769
thought something that really struck me about

00:18:24.769 --> 00:18:28.869
this memory system the truly mind -bending power

00:18:28.869 --> 00:18:32.509
maybe months down the line is the project's ability

00:18:32.509 --> 00:18:36.039
to gently correct you based on some detail from

00:18:36.039 --> 00:18:38.559
a conversation you've completely forgotten. Like

00:18:38.559 --> 00:18:40.339
take that English learning system we talked about.

00:18:40.579 --> 00:18:42.940
Maybe you're drafting something and you use the

00:18:42.940 --> 00:18:46.940
word effect when it should be effect. The project

00:18:46.940 --> 00:18:48.660
could potentially say, hang on, remember back

00:18:48.660 --> 00:18:50.500
in week three, we discussed the difference between

00:18:50.500 --> 00:18:53.619
affect and effect. Based on our conversation

00:18:53.619 --> 00:18:56.299
then, you determined effect is the noun you need

00:18:56.299 --> 00:18:59.119
here. Wow. That correction didn't come from the

00:18:59.119 --> 00:19:01.200
grammar file you uploaded initially. It came

00:19:01.200 --> 00:19:03.319
purely from the memory of your past conversations

00:19:03.319 --> 00:19:07.000
within that project. Well, that's a true assistant.

00:19:07.460 --> 00:19:09.920
That is powerful. It's not just recalling files.

00:19:10.079 --> 00:19:13.079
It's recalling the learning process itself. OK,

00:19:13.079 --> 00:19:15.019
so your action plan, if you're listening, it's

00:19:15.019 --> 00:19:17.680
simple. Don't overthink it. Just create one project

00:19:17.680 --> 00:19:19.900
today. Call it something simple and actionable,

00:19:20.359 --> 00:19:23.059
like my blog post ideas or meeting notes analysis.

00:19:23.400 --> 00:19:27.210
Set just three basic custom instructions. Maybe

00:19:27.210 --> 00:19:30.029
it's role, main goal, and preferred output format.

00:19:30.349 --> 00:19:32.509
Add only one or two key files to the knowledge

00:19:32.509 --> 00:19:35.289
base, maybe your brand style guide or notes from

00:19:35.289 --> 00:19:37.430
a recent important meeting, and then just commit

00:19:37.430 --> 00:19:39.769
to using that project consistently for one week.

00:19:39.990 --> 00:19:42.750
For anything related to that topic, see how that

00:19:42.750 --> 00:19:45.329
isolated memory, that growing history, starts

00:19:45.329 --> 00:19:47.509
to actually serve you, how the outputs get better,

00:19:47.789 --> 00:19:50.529
more tailored. Great starting point. Apply this

00:19:50.529 --> 00:19:52.789
knowledge. Set up that first some project today.

00:19:52.950 --> 00:19:55.269
Don't wait. See for yourself how quickly it can

00:19:55.269 --> 00:19:57.349
improve your consistency and the quality of what

00:19:57.349 --> 00:19:59.430
you get back from the AI. It really can make

00:19:59.430 --> 00:20:00.630
a difference. Out to your own music.
