跟讀練習: My 17 Minute AI Workflow To Stand Out At Work - 通過影片學習英語口語
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In 2025, it will take you longer to read something and comprehend it than the amount of time it took to create it.
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So if you think finding the signal within all
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that noise is only going to get worse with all
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that AI generated regurgitation of posts on LinkedIn and all that SEO optimized blog posts that don't actually contain anything good.
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So we have to move up the knowledge work value chain and luckily we can do it with AI as well.
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So let's come back to the fundamentals of knowledge work and find where we can get leverage.
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Knowledge work can be broken down into four steps.
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We have our input, the data, the knowledge, the information that we get,
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and then we process it to get some sort of output.
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right and then from the feedback of the output we then improve our input right
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and over time we're going to spiral upwards we're going to
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improve the quality of our knowledge work now most people spend
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the majority of their time thinking about how can i outsource my thinking process to ai
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and so we're using claude we're using chat to pt or say okay you write this for me, you do that for me.
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But we realize the results are not really fantastic.
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And why is that?
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It's because the input that LLMs have are pretty average, right?
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We're averaging down to the level of the internet.
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It's got some gold in it, but the majority is pretty average.
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So what we want to do instead of focusing on process, we want to focus on using AI to improve our inputs.
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Even if nothing changes in the way that we process information, our outputs will be better because we won't have this garbage in garbage out problem.
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So let's focus our effort on using AI to help us improve our inputs.
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And the 8020 we're going to do here is to add academic papers and research into our input.
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Now you might think, okay, first of all, boring.
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Second of all, this is practical work, right?
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This is not some sort of academic research that we're conducting.
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We need practical things to happen.
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But think about it.
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Do you read Harvard Business Review or McKinsey Quarterly or the MIT Sloan Review?
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All of these are aimed to take boring, hard, complex academic papers, make it relevant to working professionals
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and deliver it in a way
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that we can get something actionable out of them we got
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to realize now we don't want to be readers of hbr right we read
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so slowly but if you just feed the entire archive to chat gpt immediately it will know
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so much more than you right
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and we don't want to even be the writer for hbr
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because people spend their entire life writing a few insights you know you can just leverage those insights
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if you don't want to why spend
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that time researching instead what you want to be is hbr itself for your team for your organization meaning
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that you are going through trusted resources that are complex
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that are nuanced take that translate it into the context
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that you're in create frameworks that make that theoretical knowledge
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and insight into something that's actionable
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and be able to share it deliver it in a way
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that busy people can understand so we gotta move up the value chain
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and look at the things that used to be reserved to academics scientists authors
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that had the resources had the time had the brain power
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to sit through long -winded papers now you can too
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and let's take an example and let me show you the three tools
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that i use to make sure i become hbr for my
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team for my organization all right let's use an example say one of the biggest things
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that managers face which is the problem of team underperform they are bright people
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but they seem like they don't want to do anything they're
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always complaining about stuff how do i improve team performance okay
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so usually if you get average input you might go to chat gpt
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and ask it this question
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which will give you some average results you might go to
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google it might give you some average inputs let's give it a try
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so you know how to improve team performance at work common
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question right oh gosh it tells you focus on goals focus
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on open communication i mean these are just such empty broad recommendations
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that is not going to lead to great output
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so what i like to do instead is to use the first tool of today elicit
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so this helps you find academic papers
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on the question that you ask so let's just copy
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and paste this
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and see what kind of results we get in elicit it's free you just have to sign up and you'll get
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something like this you get the summary of the top four papers that's for free
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and then you get a list of the papers
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that is relevant now what i like to do is just to make sure what i'm reading is
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well cited is peer -reviewed
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and not some random thing i like to sort by most
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cited i take a look for example team design features
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and team performance there seems to be a relationship let's take
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a look at this one all right what you can do is then click into semantic scholar
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which will usually lead you to the actual paper itself
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and in this case it is locked so
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if you don't have access you know to a university subscription
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or something you might not be able to see this
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but no problem we'll just copy and paste the paper name and go into google and see
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if we can find a pdf version okay here we go
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here's the pdf published by sage let's just double check
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that seems to be the right one okay so we'll download this
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and then we'll use the second tool of today
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which is notebook lm by google
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so it this tool unlike chat gpt unlike claude is not using ai on the internet's knowledge
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but it's only on the sources that you upload
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so you have less likely likelihood of hallucination sign up with your google account
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and you'll see something like this so you want to create a notebook
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and essentially that just houses your sources
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and since we downloaded a pdf we are going to just
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upload it here now we haven't even read the paper we don't really know what's in there
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so what i like to do is to use it as a table of content first, and this is automatically generated by Notebook LN.
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All right.
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So now we have a table of contents.
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Okay.
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Groups is important.
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There's classification theory.
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Looks like we have to look at characteristics, some team size, team level task design, leadership.
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Okay.
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Interesting.
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Now I don't want to read this yet it's a lot of text
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and really poorly formatted but you know notebook lm is still pretty much experimental
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so we will give them some time to figure this out but now we have a general idea
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let's click back on notebook guide
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and let's look at the suggested questions since we haven't read it
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but ai has processed it i usually like to use one
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of the questions just to give me the basic gist
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so here we go how to team design feature impact overall
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team performance let's see what it says all right well looks like there are about three components
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and we saw that in the table content as well right
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so there's team composition there's task design and then there's leadership
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and i love this val notebook lm
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which is you can click into this to find the actual
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place in the source where it talks about this idea
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so even though this giant paper is probably you know tens
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of thousands of words what i can do is figure out
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which parts are most relevant to me and actually find the citation of it
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so i can better understand what is it that they say
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and let's say you know i find i can't change the
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team composition i'm not going to fire anyone i'm not going to hire anyone new
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but i want to change task design and leadership i can focus on these cited areas first.
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Okay.
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So that's the first cool part about the Elicit to Notebook LM workflow, but this is only one paper, right?
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So what I would do again is go back to Elicit and now see if there's any other papers that are interesting.
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Well, leaders can learn about teamwork developing high -performance teams.
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That seems interesting.
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Let's take a look, see if we can find the paper oh here is pdf fantastic
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so now we don't have to oh no
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okay bad request that's all right it happens let's go back and let's see a via the publisher
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oh it's a wiley paper let's see
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if we can get the pdf all right we can't
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if you're at work i mean surely your work will help you subsidize getting this paper
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but even if they don't let's see if we can find it somewhere else
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let's see if this is the right one fantastic all right here's the second pdf we got
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We will head back to notebook .lm.
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and this time we're going to press on the plus sign
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and again upload it here once that's done processing you'll see down here
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that now you can chat with both sources but before we do
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that actually i want to uncheck the previous one
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because i just want to understand what this new paper is about
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so let me do a table of content for this one source
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and i will see that it's generating a new note let's wait for
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that all right here we go there are five essentials to building high performance teams leadership capable
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and committed members norms a team structure that has clear mission responsibility goal
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and framework to get results see this is already
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so much more clear and specific compared to the Google search results
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which just got diluted over time of everyone maybe one person starting from the source
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but eventually secondary sources just dilute the message okay a way to manage team processes
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and that's the fifth one okay great now let's select both and ask it to what are the key character components,
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key changes a leader can make in a team to improve performance.
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Now it will look through both sources and give us an answer.
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All right. So, okay.
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Focus on member selection.
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Let's say that's not relevant to us.
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Promote task meaningfulness.
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And this was mentioned in the first source, right?
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Empower the team with autonomy.
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I don't know if we've seen this.
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Okay.
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So this was in the first document.
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Great.
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And it gives us the exact things that we should be doing.
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Cultivate intra -team coordination.
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All right.
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Provide effective leadership, which means guiding
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motivating
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and supporting the team let's see details now let's say out
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of all of this i think for my team the thing
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that makes sense the most is to promote task meaningfulness i want to empower the team
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and i want to facilitate team development and of course provide effective leadership so
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give me a detailed plan with three changes each
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so we can improve team performance now you have a high level plan of how to do this
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but it still feels somewhat vague even though we know
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that the input is good
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and we're focusing on what academics have found out now we want to do the next part
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which is we're going to copy this and i'm going to go into claude and say help me create a detailed
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plan to improve team performance using
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and i'm going to copy in what notebook lm has shared
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with me now two seconds we got a 12 month three phase like four module plan to improve team performance
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So just think about if you were HR or you were a team lead and you share this plan with management, they will be blown out of their socks,
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but that's not all we need.
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Let's say out of all of this still sounds like really a lot of complications.
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So let's ask it, what are the 80,
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20 changes I can make to my team to drive performance
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that is dependent on leaders and not the team members to make a change and refer to,
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and I'm going to ask it to refer to these two studies, which is called a meta -analytic review
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And now, Claude has a better idea of where I'm getting these things from.
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And so based on details that Ian knows about these two sources, it gave me the core leader action plan okay
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so task design optimization seems to be one of them authority distribution second highest impact
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and contextual support so now from 12 months we're down to three months And it gives us some expected results.
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If that's true or not, we can wait to see, but it helps us list out things like key successful factors, measurement frameworks.
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So let's say, help me create a matrix to better design tasks with clear goals
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and interdependence structures.
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Here we go.
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Now we've got a framework that we can use to assess goals, clarity level, we can use interdependence level, we can see where they intersect.
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And we can even show the team, hey, this is what I'm thinking about for changing how we think about tasks.
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What do you think and get feedback on it, right?
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Now, if we simply ask Claude, help me with what I need to improve my team's performance.
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let's see what we get.
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Alright, it's asking me a few questions that's actually already improvement since previous GPTS.
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So let's say work team with teams underperforming and unmotivated.
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Alright, and see, the plan it gives me is so much more vague, right?
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Communicate and feedback like I know this right having clear goals I know this I know all of this
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but it doesn't help help me help me create a framework to set goals let's say
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and yes smart is good monitoring is good but
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but as you can see
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because the input quality is not there we're stuck with these buzzwords that we hear all the time.
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I am excited and optimistic about the changes coming to knowledge work.
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We can critically think more.
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We can actually be more creative and associative and generalist.
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I think we'll have a great time in this era of AI.
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Let me know how you feel about it.
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Check out this video on how I use AI to create McKinsey style visuals and I'll see you in the next video.
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Bye!
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推薦影片
本課的詞彙與口語要點
這節 B2 級別的口語課以影片“My 17 Minute AI Workflow To Stand Out At Work”為素材。 影片中反覆出現的詞有:paper, performance, improve, input, source。 這段影片共有 215 個句子、2511 個單詞可供跟讀。 講話部分時長為 17:29。 說話人語速平穩,每分鐘約 144 個詞,很適合跟讀。 88% 的單詞屬於英語最常用的 3,000 詞,詞彙容易理解。
影片中的重點詞彙
影片中最難的 15 個單詞,附發音和釋義:
| 單詞 | 發音 | 釋義 |
|---|---|---|
| notebook 名詞 | /ˈnoʊtˌbʊk/ | 筆記本 /筆記本, 本子 |
| elicit 動詞 | /ɪˈlɪsɪt/ | 引出 |
| upload 動詞 | /ˈʌpˌloʊd/ | 上載 /上載, 上傳 /上傳 |
| insight 名詞 | /ˈɪnsaɪ̯t/ | 見地 /見地 |
| actionable 形容詞 | /ˈæk.ʃə.nə.bəl/ | 可行動的 /可行動的 |
| dilute 動詞 | /daɪˈljuːt/ | 稀釋 /稀釋 |
| underperform 動詞 | 表現不佳 /表現不佳 | |
| empower 動詞 | /ɪmˈpaʊ.ə/ | 授權 /授權 |
| vague 形容詞 | /veɪɡ/ | 模糊, 糢糊 |
| leverage 名詞 | /ˈlɛv.(ə.)ɹɪd͡ʒ/ | 槓桿 /槓桿 |
| pasta 名詞 | /ˈpɑ.stə/ | мянфан, 義大利麵 /義大利麵 |
| bore 動詞 | /boɹ/ | 煩擾 /煩擾 |
| garbage 名詞 | /ˈɡɑɹ.bɪd͡ʒ/ | 垃圾, 廢物 /廢物 |
| cultivate 動詞 | /ˈkʌltɪveɪt/ | 耕種 /耕種, 種植 /種植 |
| generalist 名詞 | /ˈd͡ʒɛn.(ə.)ɹə.lɪst/ | 通才 |
影片中出現的短語動詞
| 單詞 | 釋義 |
|---|---|
| check out 動詞 | 退房 |
| figure out 動詞 | 弄清楚 |
| find out 動詞 | 找出, 查明 |
| go back 動詞 | 回去, 返回 |
| go through 動詞 | 通過 /通過 |
| sign up 動詞 | 報名 /報名, 註冊 /註冊 |
值得反覆跟讀的句子
影片中簡短而完整的句子,可以直接用在日常對話裡:
- We're averaging down to the level of the internet.
- Let's say that's not relevant to us.
- I don't know if we've seen this.
影片中的語法
說話人最常用的結構,並附上影片中的原話:
| 結構 | 影片中的用法 |
|---|---|
| 被動語態 be + 過去分詞 — 強調發生了什麼,而不是誰做的 | can be broken · are aimed · are nuanced |
| 現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事 | haven't even read · haven't read · has processed |
| 定語從句 who / which + 從句 — 補充說明人或事物 | face which is · leadership, which means · studies, which is |
需要注意的發音
說話人用了 51 次縮略和弱讀形式,例如 we're, don't, I'm。請按聽到的簡短形式來說。
- “sh” 和 “zh” 音: actionable /ˈæk.ʃə.nə.bəl/, associative /əˈsoʊ.ʃi.ə.tɪv/, complication /ˌkɑm.pləˈkeɪ.ʃən/, hallucination /həˌluːsɪˈneɪʃən/, optimization /ˌɑptəmaɪˈzeɪʃən/
- 長單詞——注意重音位置: actionable /ˈæk.ʃə.nə.bəl/, analytic /ˌænəˈlɪtɪk/, associative /əˈsoʊ.ʃi.ə.tɪv/, complication /ˌkɑm.pləˈkeɪ.ʃən/, generalist /ˈd͡ʒɛn.(ə.)ɹə.lɪst/
中文母語者容易讀錯的音:
- /v/ — 不要讀成 /w/,上齒輕觸下唇: vague /veɪɡ/, leverage /ˈlɛv.(ə.)ɹɪd͡ʒ/, associative /əˈsoʊ.ʃi.ə.tɪv/, cultivate /ˈkʌltɪveɪt/, motivate /ˈmoʊ.tɪ.veɪt/
- 詞尾子音 — 要讀清楚,後面不要加母音: notebook /ˈnoʊtˌbʊk/, elicit /ɪˈlɪsɪt/, cite /saɪt/, upload /ˈʌpˌloʊd/, insight /ˈɪnsaɪ̯t/
- /r/ 和 /l/ 的區別: leverage /ˈlɛv.(ə.)ɹɪd͡ʒ/, generalist /ˈd͡ʒɛn.(ə.)ɹə.lɪst/, spiral /ˈspaɪɹəl/, critically /ˈkɹɪt.ɪ.kə.li/, clarity /ˈklæɹ.ɪ.ti/
如何用這段影片練習
- 先完整聽一遍影片,不要開口,記下不認識的單詞。
- 用正常速度逐句跟讀,每句重複到你的節奏與說話人一致為止。
- 錄下自己的聲音並與原聲對比,特別注意 notebook, elicit, upload 這類單詞。
什麼是跟讀法?
跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧,最初開發用於專業口譯員的培訓,並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大:您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同,跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性,語調,節奏,連讀,聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。













