WEBVTT

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Have you ever found yourself kind of caught in

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that loop with ChatGPT? You know, where you're

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starting a brand new conversation every single

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time. And all that valuable context you just

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built up just sort of vanishes. Oh, tell me about

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it. It's a bit like Groundhog Day for your digital

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workflow, isn't it? Absolutely. You're constantly

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re -explaining the background, re -uploading

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the same files, repeating preferences over and

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over again. It's a genuine productivity drain.

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It really is. It's frustrating. But what if there

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was a smarter way, a way to actually organize

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your AI work and consistently get really high

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-quality results back? Well, today, we're taking

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a deep dive into exactly that. We're going to

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unpack ChatGPT projects. We'll look at what they

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are, why they're actually pretty powerful, and

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how you can set them up to hopefully transform

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your productivity. Yeah, let's do it. We can

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walk through some real examples, too, step by

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step. Perfect. So let's unpack this. So thinking

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back, most of us, when we first started with

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ChatGPT, we probably used it like a simple Q

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&A tool, right? Yeah, basically. You type a question,

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you get an answer, maybe a follow -up. Exactly.

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But the frustration really kicks in when you

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move to the next task, even if it's closely related.

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You feel like you have to start all over. You

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do. You hit that reset button. You find yourself

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re -explaining the whole context, your business,

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the project, the audience you're talking to.

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Re -uploading documents. Re -uploading, yeah.

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Reiterating the formatting you want. And the

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AI just starts completely fresh. Zero memory.

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of what you just did. That starting from scratch

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problem, it's such a real bottleneck. We saw

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that a lot in the user feedback people shared.

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It wastes so much time and maybe even more importantly,

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it leads to really inconsistent results. Right.

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I mean, think about it. If the AI doesn't remember

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your brand specific tone or your clients unique

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needs, how can it possibly give you the right

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output every time? Exactly. It can't. And this

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is precisely the problem that chat GPT projects

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are trying to solve. They're not just, you know,

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glorified folders for storage. That's a common

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misconception, isn't it? Yeah, it really is.

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Instead think of them more like dedicated intelligent

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workspaces. Okay. Digital environments built

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specifically for that ongoing multi -step work

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where context is absolutely critical. So whether

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you're managing say content creation for a client

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or a big marketing campaign or even writing a

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book. Yeah, anything complex or ongoing. Projects

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aimed to keep everything organized and crucially,

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contextually aware. That's the key. Every new

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chat you start inside a project, it's already

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preloaded. How so? It gets immediate access to

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all the relevant past conversations within that

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project, all the files you've uploaded, like

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brand guidelines, research docs, customer data,

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and maybe most importantly, your custom instructions,

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which means you literally never start from zero

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again. every conversation builds on that foundation.

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Leading to better, more consistent results, presumably.

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Way more consistent, yeah. And just a quick practical

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note here, based on the articles we looked at,

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projects are currently only for chat GPT plus

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and pro users. Right, so if you don't see projects

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in your sidebar, that's probably why. Probably.

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So, okay, beyond just saving a few clicks here

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and there, what's the real, like, core difference

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this brings to how we use AI day to day? It's

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an intelligent workspace, no more starting over.

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Got it. Let's talk practical setup then, based

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on the guide. Step one seems simple enough. Just

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creating the project. Yeah, pretty straightforward.

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On the left side of your chat GPT screen, you'll

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see a new project button, usually with a little

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plus icon. Click that and it kicks things off.

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Yeah. Now, this next bit seems surprisingly important,

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but maybe easy to overlook, naming it. Oh, definitely.

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Give it a clear descriptive name. Don't just

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call it project one. Right. So like the example,

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if you're Momentum Digital working for TechUp,

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maybe Momentum Digital Marketing for Client TechUp.

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Exactly. Something where you can just glance

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at it and know exactly what's inside. Then just

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click Create Project. OK. Project created. It

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pops up in the sidebar. And then you mentioned

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a visual tip. Yeah. A simple but helpful one.

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You can change the folder color. Just click the

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little folder icon at the top of the project

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page. And you can color code things. Maybe blue

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for client work. green for internal stuff, red

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for urgent tasks, whatever system works for you.

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Nice visual cue. And then step three is choosing

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the AI model. Right. Projects let you use different

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models within the same workspace. You've got

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GPT -4 .0 for the complex, creative stuff, GPT

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-4 .0 mini for maybe quicker, simpler things,

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and GPT -3 .5 for really basic stuff. But for

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most serious business tasks, like marketing.

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Yeah, for that nuanced understanding and quality,

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GPT -4 was probably still your best bet. That's

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what we generally recommend sticking with for

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the core work in a project. OK, makes sense.

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So how does this initial setup, these first few

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steps, really benefit our overall workflow in

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the long run? Visual cues and model choice streamline

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your process. OK, now we get to what the guides

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and articles. really highlight as the core components.

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The real magic, as some put it. Yeah, this is

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what turns it from just a folder into that intelligent

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workspace we talk about. And that's files and

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custom instructions. Exactly. The two pillars.

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Let's start with files. Uploading relevant files.

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You said these become like a dedicated knowledge

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base. Precisely. It's like giving ChatGPT its

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own private library just for this project. Only

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the relevant info. So for that marketing project

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example, what kind of files are we talking about?

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OK, so for our momentum digital tech up example,

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you definitely want client documents, things

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like detailed target audience personas, user

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pain point analysis, market research, competitor

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analysis. Absolutely. Then you layer on your

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brand materials, the detailed guidelines, tone

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of voice docs, maybe even examples of past successful

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campaigns. Got it. And don't forget product or

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service info, feature descriptions, pricing,

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technical docs maybe so the AI really gets what

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you're selling. And social proof, testimonials,

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case studies. Super valuable, yeah. Ads credibility.

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And uploading is easy. Just click add files,

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grab your documents. You can do multiple at once.

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Build up that knowledge base. OK, that's the

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files foundation. Now, custom instructions. You

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said this is where the magic really happens.

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Yeah, I think so. This is like giving ChatGPT

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its detailed brief, almost its personality for

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this specific project. So what makes for great

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custom instructions? It can't just be, be helpful.

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No, definitely not. You need specifics. First,

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assign it a clear role. Tell it who it should

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be. expert consultant, a creative copywriter.

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OK. Then specify the response format you want.

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Define the tone and style really clearly. Include

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any unique guidelines just for this project.

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Reference points, too, like specific authors

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or styles to emulate. Yeah, exactly. So for our

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TechUp B2B example, the instructions might be

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something like, core role, you are a growth marketing

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consultant for B2B tech startups. OK, very specific.

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Focusing on attracting technical audiences for

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style. Inspired by Seth Godin, professional,

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tech savvy, focused on benefits, not just features.

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Nice format. Structured recommendations, use

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bullet points, headings, always suggest a title

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and a call to action for content. And the business

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context. Client is tech up, saws for developers.

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Target, devs, tech leads, CTOs, goal, increase

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trial signups, avoid cliche marketing jargon,

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be authentic. That's pretty detailed. It needs

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to be. You know, I still wrestle with prompt

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drift myself sometimes. Yeah, where it kind of

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loses focus. Exactly. It starts to wander off

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from the original instructions over a long chat.

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Getting these custom instructions really dialed

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in is, it's an art, beat, but when you nail it,

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wow, it makes such a difference. It really sounds

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like these two things, the file providing the

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knowledge, the instructions providing the personality

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and direction are the absolute heart of it. Why

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are they so fundamentally critical together?

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They provide the core brain and personality for

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your AI. Okay, let's make this concrete. A real

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world use case, like the ones in the studies,

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say creating an outline and intro for a technical

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blog post. Alright. For our TechUp example, maybe

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the task is detailed outline and intro for automating

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your API testing workflow with TechUp's new feature.

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So instead of just that generic prompt, you'd

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leverage the project context. Right. Specify

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the target devs, QA engineers. Address their

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specific pain points with manual testing. Introduce

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the new feature as the solution. Right. Build

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credibility. Maintain that tech savvy tone from

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the instructions. And maybe specify the format

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detailed outline with HUSH3s and like a 150 -200

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word. And with a well set up project, the output

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should be pretty impressive. You'd get that detailed

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outline, H2s like the problem with manual API

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testing, H3s like time drain, scaling issues,

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and then a solid intro. Something like, if you're

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a developer, you know the pain. Hours on repetitive

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API tests. It's a bottleneck. What if you could

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automate it? TechUp's new auto -test feature

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makes that real, you know, something engaging

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like that. And it works well because the AI has

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all that context from the start. Exactly. It

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knows the audience, the product, the desired

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tone from the files and instructions, so it maintains

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consistency, delivers professional quality, it

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has guardrails. That's pretty efficient. OK,

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now let's take that blog post and promote it.

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OK. Use case hashtag two, a LinkedIn post series.

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Good one. Now, this is a related task, but different

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social media, not long -form content. So key

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step. Start a new chat within the same project,

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right? Crucial step. Yep. Keeps things organized.

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But you still get all that lovely context. Tech

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up, the product, the audience, the tone. It's

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all still there. Okay, so the prompt for the

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LinkedIn series might detail, say, a three -post

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strategy. Yeah, like, post one is a hook about

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the pain points. Post 2 introduces the blog feature

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with benefits and a CTA. Post 3 offers social

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proof or a future vision. Makes sense. And it

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would generate those posts. Yep. Like Post 1

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might be. Still manually testing APIs, flaky

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tests, regressions. It's a productivity killer.

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There is a better way. TechUp's working on something.

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Stay tuned. You know, with tailored hashtags,

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too. And the power here is that consistency.

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Absolutely. The project continuity. The whole

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series sounds like it came from the same brand

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as the blog post. Unified voice, coherent message,

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totally brand aligned with TechUp's goals in

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the project. Wow. Think about scaling that unified

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voice. Whoa. Imagine scaling that across hundreds

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of campaigns without re -briefing every time.

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That's the real power. So it's not just faster

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content. How does this process really save us

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significant time and, frankly, mental energy?

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AI understands your brand, generating consistent

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tailored content faster and smarter. Okay, so

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to really get the most out of this, we need to

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avoid some common mistakes. Based on what we've

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seen in forums and guides, what are the big pitfalls?

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I think the biggest one is just treating projects

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like basic folders. You know, creating one, but

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then not actually using the files and custom

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instructions. Right. If you don't feed it that

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context, it's basically just an empty box. No

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different from a regular chat. Exactly. It defeats

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the whole purpose. Another one is uploading too

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many irrelevant files. Ah, information overload

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for the AI. Yeah, basically. If you just dump

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everything in there, it kind of dilutes the context.

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The AI struggles to figure out what's actually

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important for this specific task. So be selective.

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Curate the knowledge base. Definitely. Choose

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only the critical, relevant docs for that project's

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goal. And we absolutely have to talk about vague,

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custom instructions again. That seems like a

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major issue. Huge. Just saying, be professional

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or write well, that gives the AI almost nothing

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to work with. Useless. Pretty much. You need

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those hyper -specific details. The role, the

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audience, the tone, the business context, like

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we talked about, precision is key. Got it. Anything

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else? Yeah. One more big one. Trying to do too

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many different things in the same chat window?

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The kitchen sink approach. Exactly. Don't ask

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it to write a blog post, then immediately draft

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an email, then do social posts all in one continuous

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thread. Why not? Because the context gets modeled.

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Each task really benefits from a focused conversation.

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So start a new chat within the project for each

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distinct task, even if they're related. Keeps

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things clean and effective. Right. Otherwise,

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it's like trying to bake a cake, fix a car, and

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write a novel all in the same kitchen sink. It

00:12:24.240 --> 00:12:26.139
just gets messy and nothing turns out quite right.

00:12:26.399 --> 00:12:28.620
That kitchen sink analogy definitely sticks.

00:12:28.820 --> 00:12:30.980
Yeah. So if there's one big takeaway for listeners

00:12:30.980 --> 00:12:34.000
to avoid these traps, what is it? Be present

00:12:34.000 --> 00:12:36.639
with context and keep your AI tasks focused.

00:12:36.879 --> 00:12:39.500
Okay, one area of confusion that often pops up

00:12:39.500 --> 00:12:42.259
is the difference between chat GPT projects and

00:12:42.259 --> 00:12:44.600
custom GPTs. Let's try and clarify that. Yeah,

00:12:44.639 --> 00:12:46.879
good idea. They sound similar, but serve different

00:12:46.879 --> 00:12:50.320
purposes. Think of custom GPTs as specialized

00:12:50.320 --> 00:12:53.679
tools. They're built for specific, often repetitive

00:12:53.679 --> 00:12:56.039
tasks. They can have a unique personality, they're

00:12:56.039 --> 00:12:58.620
easily shareable, and they can even connect to

00:12:58.620 --> 00:13:01.899
external things like APIs. More like single purpose

00:13:01.899 --> 00:13:05.360
apps and projects. Projects are more about organizing

00:13:05.360 --> 00:13:08.019
ongoing evolving work. They're your personal

00:13:08.019 --> 00:13:11.120
workspaces. Their main job is storing files,

00:13:11.600 --> 00:13:14.299
remembering instructions, and keeping that rich

00:13:14.299 --> 00:13:17.100
chat history going over time for a broader initiative.

00:13:17.289 --> 00:13:20.210
So give us the when to use which breakdown. OK.

00:13:20.549 --> 00:13:22.990
Use projects for managing complex client work,

00:13:23.289 --> 00:13:25.529
multi -step content creation, needing a consistent

00:13:25.529 --> 00:13:28.090
voice, or any long -term thing where context

00:13:28.090 --> 00:13:31.590
builds up. And custom GPTs. Use custom GPTs when

00:13:31.590 --> 00:13:34.049
you want to build a specific repeatable tool,

00:13:34.250 --> 00:13:37.129
like an expert ad copywriter GPT that always

00:13:37.129 --> 00:13:39.750
uses a certain framework, or an AI assistant

00:13:39.750 --> 00:13:42.090
for your team that does one specific task often.

00:13:42.309 --> 00:13:44.289
They're for narrow specialized capabilities.

00:13:44.769 --> 00:13:47.639
Gotcha. But they aren't mutually exclusive not

00:13:47.639 --> 00:13:49.840
at all and this is where it gets really powerful.

00:13:49.899 --> 00:13:52.509
You can absolutely use them together How would

00:13:52.509 --> 00:13:55.190
that work? Well, our agency, Momentum Digital,

00:13:55.429 --> 00:13:57.490
could use a project for all the work for the

00:13:57.490 --> 00:14:00.210
TechUp client blogs, social strategy, everything.

00:14:00.950 --> 00:14:04.009
But they could also have a custom GPT, maybe

00:14:04.009 --> 00:14:06.789
called LinkedIn Post Optimizer, that the whole

00:14:06.789 --> 00:14:09.490
marketing team uses across all clients, including

00:14:09.490 --> 00:14:12.830
TechUp, just to refine those posts. Ah, so the

00:14:12.830 --> 00:14:16.690
Cumptive GPT is a tool used within or alongside

00:14:17.200 --> 00:14:20.059
the broader project structure. Exactly. It lets

00:14:20.059 --> 00:14:22.500
you layer workflows in a really advanced way.

00:14:22.639 --> 00:14:24.720
So these two powerful features, projects and

00:14:24.720 --> 00:14:27.059
custom GPTs, they can actually work together,

00:14:27.340 --> 00:14:29.240
complementing each other. Absolutely. They complement

00:14:29.240 --> 00:14:31.539
each other perfectly for advanced workflows.

00:14:31.960 --> 00:14:34.220
OK, let's wrap this up. What does this all really

00:14:34.220 --> 00:14:36.440
mean for your day -to -day workflow with AI?

00:14:36.960 --> 00:14:38.980
What are the big ideas? Well, first, I'd say

00:14:38.980 --> 00:14:42.379
setup is everything. Really take that time upfront

00:14:42.379 --> 00:14:44.940
to configure your project with detailed instructions

00:14:44.940 --> 00:14:47.360
and truly relevant files. That's the foundation,

00:14:47.460 --> 00:14:49.879
isn't it? It absolutely is. And that leads to

00:14:49.879 --> 00:14:53.580
the second point. Context is king. The more relevant,

00:14:53.740 --> 00:14:56.100
thoughtful context you provide, the better and

00:14:56.100 --> 00:14:58.279
more precise your results will be. The AI just

00:14:58.279 --> 00:15:00.919
gets smarter about your needs. And third? Organization

00:15:00.919 --> 00:15:03.980
pays off. A good project structure isn't just

00:15:03.980 --> 00:15:07.700
about tidiness. It genuinely saves hours and

00:15:07.700 --> 00:15:10.500
massively improves consistency, reduces that

00:15:10.500 --> 00:15:14.460
mental load. Always be improving. Your projects

00:15:14.460 --> 00:15:17.799
shouldn't be static. Review them, optimize them.

00:15:18.200 --> 00:15:20.100
They're living workspaces, right? They should

00:15:20.100 --> 00:15:23.259
evolve. This whole feature. It really feels like

00:15:23.259 --> 00:15:26.620
a leap. Moving from just basic AI chats to something

00:15:26.620 --> 00:15:30.700
much more like sophisticated context -aware collaboration.

00:15:31.120 --> 00:15:33.279
The time you invest in really getting the hang

00:15:33.279 --> 00:15:35.960
of chat GPT projects today, it seems like it

00:15:35.960 --> 00:15:38.639
will genuinely pay off down the line. Maybe the

00:15:38.639 --> 00:15:40.759
best advice is just start small. Totally. Start

00:15:40.759 --> 00:15:42.820
with one project right now. Upload just a few

00:15:42.820 --> 00:15:45.620
key files. Write your first clear set of instructions.

00:15:45.820 --> 00:15:47.679
And just see the difference it makes. Exactly.

00:15:47.820 --> 00:15:50.059
Experience it. Your productivity and honestly

00:15:50.059 --> 00:15:52.759
the quality of what you create. It probably won't

00:15:52.759 --> 00:15:55.559
be the same. Yeah. This feels like the point

00:15:55.559 --> 00:15:59.480
where you shift from just talking to AI to really,

00:15:59.519 --> 00:16:02.240
truly collaborating with it. Reflective, calm.

00:16:02.580 --> 00:16:04.679
Yeah. Just consider how much more deeply the

00:16:04.679 --> 00:16:06.600
AI can understand you, understand your goals

00:16:06.600 --> 00:16:08.419
as they evolve, when you actually give it a dedicated,

00:16:08.639 --> 00:16:10.820
persistent home for your work. Two secs silence.

00:16:10.840 --> 00:16:11.919
I've got it. Have too many music.
