The Future of Work · 2026-05-21 · 52 min
Key moments - from our scoring
Substance score
44 / 100
Five dimensions, 20 points each
Dr. Sara Faragi, technical communications strategist and writing instructor at UC Berkeley Extension, discusses how communicators in cybersecurity, product development, and marketing can leverage AI as a writing partner without sacrificing authenticity or accuracy. Rather than treating AI as a simple output generator, Faragi advocates for a three-part rhetorical toolkit grounded in Aristotelian principles: stasis theory (inquiry-based questioning about facts, definitions, quality, and policy), rhetorical appeals (establishing ethos, pathos, and audience understanding), and exigence (understanding the situational "so what" driving the writing). She emphasizes that effective AI collaboration requires treating prompts as turn-based conversations with built-in constraints, style guides, and verification steps - especially critical in cybersecurity where misconfiguration can cause serious harm. Faragi shares early mistakes (uploading raw documents without context) and demonstrates how role-playing personas, asking AI to identify flaws, and iteratively training the tool on verified information creates a mutual learning relationship. The episode addresses why AI onboarding feels slower initially but yields long-term efficiency gains, and why critical thinking remains non-negotiable when using AI for high-stakes technical writing.
Stasis theory involves four types of questions: conjecture (what are the facts?), definition (what kind of thing is this?), quality (is this good or bad?), and policy (what should be done?). When prompting AI, ask yourself these questions first to ensure you're not getting hallucinated answers and to identify gaps in what the AI needs to produce better output.
Training an AI writing partner takes upfront time because it only knows what you explicitly provide - your style guide, audience context, constraints, and role. Faragi compares it to training a baby; the investment pays off as the tool learns your preferences and can be reused across projects, eventually turbocharging workflows.
Don't offload all technical thinking to AI. Use it for first drafts based on your style guide and templates, then ask it targeted questions (e.g., what questions should I ask product managers or CISOs?). Verify all unconfirmed information, flag gaps, and train the tool on verified answers so it learns your domain.
Exigence is the situational "so what" - the specific problem you're solving and why you're writing. Including this context in prompts prevents AI from making assumptions and helps it produce more relevant, purposeful output than generic prompts alone.
AI tools are more effective at identifying what's wrong and self-correcting than at evaluating overall quality. Framing questions negatively (what could be better, what errors exist, what contradicts this?) yields more impressive and thorough outputs than asking for validation.
Our reviewer’s read on each dimension, with quotes from the episode.
The episode contains a handful of genuinely useful frameworks - applying classical stasis theory and rhetorical appeals (ethos, pathos, exigence) to AI prompting is non-obvious and actionable - but these ideas are surrounded by significant padding, repetition, and platitudes about fact-checking and treating AI as a conversation. Over 52 minutes, the substantive content could be condensed to roughly 12-15 minutes.
the stasis of definition. And then look at this. Is this good, is this bad? That's about the stasis of quality. And then there's also a stasis of policy, uh, what should be done.
I am now in a place where I don't just write the information all on my own and then have a long list of questions for a SME, I have very focused questions that I might ask certain stakeholders who know more.
The application of Aristotelian rhetoric and stasis theory to AI prompt engineering is a genuinely fresh lens not commonly articulated in AI productivity content, and the argument that AI tools are better at finding flaws than validating work is moderately contrarian. However, the majority of the episode recycles well-circulated advice - treat AI as a conversation, fact-check outputs, domain expertise matters - without adding meaningfully new angles.
understanding the question of stasis theory. And so what this is, is it's looking at writing in a way that is question and inquiry oriented.
the AI tools are a lot better at finding what's wrong and they, they're good at self correcting too.
Dr. Faragi is a credible practitioner - she writes technical documentation in cybersecurity and teaches at Maryland and UC Berkeley Extension - but she is primarily an academic writing instructor, not a senior B2B operator who has scaled a function or driven measurable business outcomes. Her insights are grounded but not the kind that come from running a large team or owning a P&L.
I work in the ever changing field of cybersecurity where technical documentation is very important in this field
As a faculty fellow at the University of Maryland and a writing instructor at UC Berkeley Extension, Sarah empowers students to build a rhetorical toolkit
The episode names specific rhetorical frameworks (stasis theory, ethos/pathos/exigence), specific AI features (Gemini Gems, Projects), and specific tactics (STAR method for resumes, OSINT for interview prep), which is a notch above pure abstraction. However, there are zero named companies, no metrics, no dollar figures, no timelines, and no concrete before/after case studies - the cybersecurity context is described only in generalities.
The EM dash is a classic one. And lately I'm noticing the. It's not this, it's that. Not, you know, the, these types of styles that are very almost cliche.
I use the STAR method, the situation, task, action, response. I like to kind of work with AI tools to say, can we look at my bullet points and help me flesh out the star method
The host asks a few genuinely sharp questions - probing why AI onboarding feels slower than just writing, and whether deep research on interviewers risks being 'creepy' - but largely accepts answers without following up or challenging claims. The conversation stays friendly and validating throughout, with no productive disagreement and several instances of the host summarizing the guest's point back rather than probing further.
Why does this onboarding of AI feel slower than just writing it yourself?
Is there any fear of being too prepared? A little creepy knowing a little bit too much about the person you're talking to.
Computed from the transcript - who did the talking, and the words that came up most.
AI can brainstorm at lightning speed, clean up clunky sentences and help you get unstuck when the blank page stares back. But are you losing your own brand voice and your critical-thinking skills by offloading tasks to AI? Or are you sharpening your writing and accelerating your productivity with AI assistance? In this episode, we explore using AI as your writer and editor companion. How do you decide when AI is used as a creative copilot and when human judgment is needed most? How are communicators in jobs like product development, sales, marketing and HR using AI to work faster, without - and this is key - losing authenticity, accuracy and trust? Let's talk about the art of augmentation, because the future of writing in the workplace is not human or AI. It's human with AI. To discuss this topic, we're delighted to welcome technical communications strategist Dr. Sara Faradji. Read the transcript @ Learn more about UC Berkeley Extension @
Transcribed and scored by The B2B Podcast Index.
Host: Foreign.
Dr. Sara Faragi: We're teaching English classes. We teach developing a good counter argument and a rebuttal.
Dr. Sara Faragi: And I think those are good to keep in mind when working with AI tools.
Dr. Sara Faragi: And you may find that some of
Dr. Sara Faragi: the things that it's pushing back on really as relevant, but it's still good
Dr. Sara Faragi: to at least see some of that information and see it kind of leaning into the more negative or questioning kind of tone rather than just validating everything you say.
Jill: Welcome to the Future of Work podcast with Berkeley Extension and Edge in Tech at the University of California. Focused on expanding diversity and gender equity in tech, Edge and Tech is part of the Innovation Hub at Citrus, the center for IT Research in the Interest of Society and the Banatau Institute. UC Berkeley Extension is the continuing education arm of the University of California at Berkeley. AI can brainstorm at lightning speed, clean up clunky sentences, and help you get unstuck when the blank page stares back. But are you losing your own brand voice and your critical thinking skills by offloading tasks to AI? Or are you sharpening your writing and accelerating your productivity with AI assistance? In this episode we explore using AI as your writer and editor companion. How do you decide when AI is used as a creative copilot and when human judgment is needed most? How are communicators in jobs like product development, sales, marketing, HR using AI to work faster without, and this is key, losing authenticity, accuracy and trust? Let's talk about the art of augmentation. Because the future of writing in the workplace is not human or AI, it's human with AI. To discuss this topic, we're delighted to welcome technical communications strategist Dr. Sara Faragi. Sarah believes that powerful stories drive technical innovation, but critical inquiry is what turns innovation into real world impact. She brings this lens to her technical writing work in cybersecurity by helping research and development leaders communicate technical information in ways that resonate meaningfully with business leaders and customers. As a faculty fellow at the University of Maryland and a writing instructor at UC Berkeley Extension, Sarah empowers students to build a rhetorical toolkit for career success in a shifting job market. Welcome Sarah hi.
Dr. Sara Faragi: Thank you so much for having me. Jill.
Jill: This is going to be fun and I want to start out with this rhetorical toolkit because it sounds very fancy. What led you to develop it and why is it needed today?
Dr. Sara Faragi: Yes, so what I love about being
Dr. Sara Faragi: in the English department at the University
Dr. Sara Faragi: of Maryland and teaching English is we
Dr. Sara Faragi: really ground a lot of our principles on age old rhetorical concepts. These go all the way back to Aristotle and different philosophers.
Dr. Sara Faragi: And I find that these rhetorical skills
Dr. Sara Faragi: are tried and true. No matter what technological innovations come. These rhetorical strategies are really great.
Dr. Sara Faragi: And, and I think in the age
Dr. Sara Faragi: of AI, these kinds of tools are even more valuable.
Dr. Sara Faragi: And I kind of have a three
Dr. Sara Faragi: part toolkit that I really recommend for students or for anyone who is going to use AI. And the first one is understanding the question of stasis theory.
Dr. Sara Faragi: And so what this is, is it's looking at writing in a way that
Dr. Sara Faragi: is question and inquiry oriented. In thinking about this with AI, it's
Dr. Sara Faragi: not just here's something and give me
Dr. Sara Faragi: an output, here's a paper or a
Dr. Sara Faragi: prompt, now give me a full paper
Dr. Sara Faragi: or something like that.
Dr. Sara Faragi: It's more about, here is a prompt. And uh, now I want you to
Speaker E: answer some things for me.
Dr. Sara Faragi: What are the facts here?
Dr. Sara Faragi: That's called conjecture.
Dr. Sara Faragi: And then what is, what kind of thing is this?
Dr. Sara Faragi: How do we define it?
Speaker E: That's called the stasis of definition.
Dr. Sara Faragi: And then look at this.
Dr. Sara Faragi: Is this good, is this bad? That's about the stasis of quality.
Speaker E: And then there's also a stasis of policy, uh, what should be done. So in practice, when you're looking at your prompt, you ask yourself, what do you actually need? If you're not certain about certain key facts, ask, you know, what are the facts of this that are known based on the prompts and what do we need to find out? That way it can help prevent you from getting some answers that are hallucinated or not true. And when you look at a cover letter or something, you say, is this a good example of the COVID letter genre? What are some things I can improve upon? What are the flaws in it? So really looking inward in these questions, and the second thing I recommend in the toolkit is looking at rhetorical appeals. So this is looking at, you know, ethos, is establishing a sense of self. So when you first give a prompt to AI, you can say something like, I am writing for this audience. And here's a little bit about me as well. I am a technical writer. Here's my kind of, you're giving it your Persona, you're establishing your sense of self. And also pathos is looking at kind of emotions or what the audience cares about. So establishing who is your audience, what are their values, what do they care about? And things like this are really going to help it, uh, to be able to understand how to produce a quality output.
Dr. Sara Faragi: And then kind of a third part
Dr. Sara Faragi: of this toolkit is understanding this issue
Dr. Sara Faragi: of exigence or like the so what? The who cares factor. I think this is something that is missing a lot in kind of first turn writing. When you ask the AI to give you an output.
Dr. Sara Faragi: So we. What I like to do is kind of look at, you know, I am
Dr. Sara Faragi: writing this for a specific situation.
Dr. Sara Faragi: Here is what prompted me to write it.
Dr. Sara Faragi: Thinking a little bit about what was the situation, what were you being asked to do, why? And really getting into what is the problem that you are seeking to solve.
Dr. Sara Faragi: Because if you don't give it that information, then it's going to have to assume that.
Dr. Sara Faragi: So being able to give it these kinds of constraints.
Dr. Sara Faragi: So these are the.
Dr. Sara Faragi: This is the toolkit that I recommend for.
Dr. Sara Faragi: And I think if you learn about
Dr. Sara Faragi: and understand situations through this point of
Dr. Sara Faragi: view and use this toolkit, then I
Dr. Sara Faragi: think you can be much better at interacting with AI.
Jill: What I love about this is you're
Host: starting out with the English department. To me this sounds like Journalism 101.
Jill: And when you think about jobs and technology, you often don't think about how
Host: important the humanities are to really communicating the technological innovation. So I love that lens that you're bringing to it.
Dr. Sara Faragi: Yes, absolutely. I think that with journalism, where you are doing creative writing, all of these
Dr. Sara Faragi: different ways that you are engaging with language, I like to compare it a lot to working with code.
Dr. Sara Faragi: And in some ways both we're all like people who are working with language,
Dr. Sara Faragi: human languages and those who are working with code. We're all working with code in some ways.
Dr. Sara Faragi: And I think that's what makes these AI tools so interesting, is that we're
Dr. Sara Faragi: able to get code outputs and generate them much faster. But we still have to analyze the quality, ask IT questions, verify and do
Dr. Sara Faragi: a lot of critical thinking.
Dr. Sara Faragi: Still, all of these skills are still
Dr. Sara Faragi: so valuable and we're redefining what that
Dr. Sara Faragi: looks like and how we continue to shape and sharpen our skills with AI.
Jill: So let's make you go back to the early days. Do you recall the first time you experimented with AI as a writing partner? And how did it go? What mistakes did you make?
Dr. Sara Faragi: Yes, I can recall the very first prompts I remember using when I was
Dr. Sara Faragi: working with AI tools.
Dr. Sara Faragi: Was first I started with what I
Dr. Sara Faragi: knew in the sense that I've used different tools that are for spell check and other than I use search.
Dr. Sara Faragi: In some ways these are helping us to kind of refine what we've written.
Dr. Sara Faragi: But if I'm just taking a paper and then uploading it and saying fix
Dr. Sara Faragi: the typos or edit this and not
Dr. Sara Faragi: giving a lot of structural guidelines or information.
Dr. Sara Faragi: You know, it might be able to identify issues with grammar, but that's not really the hard part.
Dr. Sara Faragi: In some ways there's a lot that's still going to get missed if you do things that way.
Dr. Sara Faragi: But is it aligned to your style guide?
Dr. Sara Faragi: Does it know your specific nuances and things like that? And if it doesn't know that and you're assuming that it knows that, then you might have to get into quite a long conversation, get frustrated with the output.
Dr. Sara Faragi: Another issue I had when I was first prompting was I would just maybe
Dr. Sara Faragi: upload a lot of different docs that were that provided some factual information. Maybe I'll use the source code, maybe
Dr. Sara Faragi: I will provide just a general one
Dr. Sara Faragi: pager of this, all these different types of things and then say here, make a knowledge article out of this material.
Dr. Sara Faragi: Well, all it has is these things. How is it going to be able to validate what is the truth?
Dr. Sara Faragi: What has changed past a specific point?
Dr. Sara Faragi: What is outdated?
Dr. Sara Faragi: What is new?
Dr. Sara Faragi: What are these? How is it going to make sense
Dr. Sara Faragi: of all of this?
Dr. Sara Faragi: And so I realized that I needed
Dr. Sara Faragi: to change my thinking about the prompting and not just give it something. And here, give me an output.
Dr. Sara Faragi: I need to do a little bit
Dr. Sara Faragi: of what I was talking about earlier with the rhetorical toolkit about thinking about prompting as a turn based conversation and a line of questioning. I need to be thinking more about how can I set the stage. I'm writing this for this purpose.
Dr. Sara Faragi: Here is what good looks like. Here are some examples and what I also ask it to verify and validate information.
Dr. Sara Faragi: If you give me the first output, that's not where the conversation ends. I need to follow up and ask it some question.
Dr. Sara Faragi: You know, what are three possible flaws with this?
Dr. Sara Faragi: I think that AI tools are good at editing themselves in some ways, but they have to be prompted. So really thinking of this more as a conversation, that's how it's transformed my thinking a little bit. From here I'm uploading it and I'm not getting it what I want. But it doesn't know what I want. Now I have to train it to know what I want.
Jill: I think this is a critical piece.
Host: There's a mindset shift going on because
Jill: people have grown up with Google Search and this is not Google Search. Can you say a little bit about
Host: more like what has to happen to
Jill: make sure that it's not making things up? What are some of the other things that it's prone to doing that you may not want in your Writing, Yes.
Dr. Sara Faragi: So I think when we think of search and we are just asking a question and we might get a list of links, or we might get some
Dr. Sara Faragi: information that is surfaced that's coming from the surface level or interpreted from the links, then we're only seeing a very cursory story.
Dr. Sara Faragi: But it's not always from the lens of an actual person using this, or it's maybe not looking at it in
Dr. Sara Faragi: the same way that a scholar or a developer or someone might be. And it's again, just skimming the surface
Dr. Sara Faragi: back when if you're writing a dissertation
Dr. Sara Faragi: or doing deep research, you might spend a lot of time in the library going well beyond the scope of search
Dr. Sara Faragi: to really dig into that research. And I think that with using AI
Dr. Sara Faragi: tools, it can help bring some things to the surface. But you have to be questioning and going deeper and deeper. You need to be asking what were the sources?
Dr. Sara Faragi: And then actually opening and looking into
Dr. Sara Faragi: those sources if you can, and reading and understanding the context. Because sometimes with that cursory level, maybe it's just reading the abstract of something, but it's not getting much deeper into
Dr. Sara Faragi: the real situational information.
Dr. Sara Faragi: Whereas of course, if we're doing research, we need a lot of different facts and statistics put together and analyze in all these various situations to be able to draw an effective conclusion. Not just a single source proves that.
Dr. Sara Faragi: And so I think these are things that we still need to keep in
Dr. Sara Faragi: mind when we're researching. We have to be asking those types of questions.
Dr. Sara Faragi: We can surface and find things at
Dr. Sara Faragi: the initial level, but we still have to do that work of reading through understanding that context, probing a bit more to be able to make sure that we appropriately fact check and put information out there that can be trusted by other people.
Host: So, you know, we're architecting the intent, we're providing more context, we're talking about the audience, but also what we want to attain as an output.
Jill: These guardrails.
Host: It sounds like it's taking an incredible amount of time.
Jill: So why does this onboarding of AI feel slower than just writing it yourself?
Dr. Sara Faragi: I think that's a really good question. Because we keep hearing about how AI is going to make our job so much faster. We're going to be able to generate articles and knowledge so quickly.
Dr. Sara Faragi: We're going to be able to produce twice, three times the output that we did before. But I think there is a, uh, truth to that.
Dr. Sara Faragi: But at the same time, there is this long terray or this longer relationship that we have to have with the
Dr. Sara Faragi: AI when we first start Using it, like I was mentioning, it's like training a baby in some ways. It only knows what you give it.
Dr. Sara Faragi: And what I found really valuable is we have to kind of let the
Dr. Sara Faragi: AI deal with our frustrations a little
Dr. Sara Faragi: bit, be able to voice information and
Dr. Sara Faragi: the more information it has, the better it's going to get.
Dr. Sara Faragi: So that future state of you're being
Dr. Sara Faragi: able to really turbocharge your workflows and
Dr. Sara Faragi: everything, I wouldn't expect the very first
Dr. Sara Faragi: thing you produce, the first question, the first output.
Dr. Sara Faragi: To be able to make it like
Dr. Sara Faragi: that, you really have to train it
Dr. Sara Faragi: and be able to give it your constraints.
Dr. Sara Faragi: It does take some time, but I
Dr. Sara Faragi: also think that you can really, as
Dr. Sara Faragi: you get to understand it more and as you use certain tools, there are
Dr. Sara Faragi: some options where you can create documents
Dr. Sara Faragi: or a folder and have all of
Dr. Sara Faragi: the source information there, or you can
Dr. Sara Faragi: add it to a project and then you don't have to keep repeating all of this information every single time you start the conversation. Gradually it is going to learn, but it has to baseline and understand you a bit more. So, so it really does take that time.
Host: So upfront costs for longer term efficiency,
Jill: but also probably more complete completeness.
Host: Right, because it's accessing a lot more information than we as an individual might have.
Dr. Sara Faragi: Right, exactly.
Dr. Sara Faragi: It can pull from a lot of different sources. I think back to when I was
Dr. Sara Faragi: doing research on my dissertation. I would have all of these documents
Dr. Sara Faragi: I would go and read and many, many books and have all of these
Dr. Sara Faragi: lists of quotes, all these highlighting across all of the different sources. Still, there's still so much value in that and being able to do that deep research. But we can have kind of a co worker to help us to find
Dr. Sara Faragi: and organize some of that information and
Dr. Sara Faragi: to make sure that we can find what we need. We're still doing the work, but it might be surfaced or organized a bit
Dr. Sara Faragi: better so that we can maintain focus
Dr. Sara Faragi: on being able to draw important and sophisticated conclusions.
Jill: So you work in a very sensitive field, cybersecurity, where data and accuracy is essential. Tell us about that work and how
Host: that context made you use AI, perhaps
Jill: a little more cautiously.
Dr. Sara Faragi: Yes, I work in the ever changing field of cybersecurity where technical documentation is very important in this field because it's. If you misconfigure something, if you don't follow a correct step, then that could lead to big issues in your environment or. And so it's very important that users trust this documentation. I didn't want to just offload all
Dr. Sara Faragi: of that thinking and the complexity of technical writing to AI or to ask it to do the technical piece. Something I found really interesting when getting
Dr. Sara Faragi: into these types of roles is I think there's an assumption that if you are an engineer, then you have very strong technical skills, but maybe you don't necessarily have the best communications or writing
Dr. Sara Faragi: skills in some ways, and you can use AI to kind of offset that type of work.
Dr. Sara Faragi: And then there's the assumption that if
Dr. Sara Faragi: you are a writer or a communicator,
Dr. Sara Faragi: then maybe your strength is in being
Dr. Sara Faragi: able to translate complex information into easily digestible information. But you might not necessarily have the deep technical background, but you could offset that to AI.
Dr. Sara Faragi: And in some ways, I think that there's some flaw in that kind of thinking because we can use AI to
Dr. Sara Faragi: help make up for those gaps, but at the same time, it can't replace in the sense that, oh, the I'm just going to trust what the AI gives me as the technical output, and I don't need to verify that information. I'm still working. I use the AI tools to help me give first drafts based on my style guide, my templates. But then I ask it, what are questions that I need to ask the product managers, or what are questions I need to ask our ciso? What are the privacy considerations? If I'm a user going through this
Dr. Sara Faragi: for the first time, then what problems might I encounter?
Dr. Sara Faragi: What are some troubleshooting?
Dr. Sara Faragi: And then it can really start to
Dr. Sara Faragi: get into some interesting information beyond just here. Here's the factual information I'm giving you. Make a guide.
Dr. Sara Faragi: It's more, how can we fill in
Dr. Sara Faragi: these gaps and be able to answer key questions?
Dr. Sara Faragi: And when I'm reviewing the output, if there's something that I know that I
Dr. Sara Faragi: have not verified or wasn't from the text, I'm going to flag that and ask more questions about it.
Dr. Sara Faragi: So I certainly in cybersecurity and other
Dr. Sara Faragi: fields, you have to be careful about what you put out there. And not just using the AI tool as the SME, but there are certain
Dr. Sara Faragi: ways that it can help with changing your workflow a bit. I am now in a place where
Dr. Sara Faragi: I don't just write the information all
Dr. Sara Faragi: on my own and then have a
Dr. Sara Faragi: long list of questions for a SME, I have very focused questions that I might ask certain stakeholders who know more. And we can also use different kinds of technologies so that once we have the verified information, we let the AI tool know that that's the correct answer and it'll learn from it later on. Same thing with style Guides.
Dr. Sara Faragi: If there's something that I'm realizing is
Dr. Sara Faragi: a bit off, then I'm going to train the AI like now, from now on, use this type of response or know this fact and make sure that's correct in our master materials.
Host: So it can help you identify a little bit what you've missed. It sort of has the complementary skill sets. How do you use it to find blind spots in your own arguments if you think you've done everything correct, how might you use it to explore if you actually do have it correct?
Dr. Sara Faragi: Yes, that's a good question about how can it find some things that I might have missed? So I might actually ask it some questions. I'll give the information and then I will say uh, I uh, will kind
Dr. Sara Faragi: of give it some role playing advice.
Dr. Sara Faragi: Like first imagine that you are a
Dr. Sara Faragi: CISO and you're looking at this and
Dr. Sara Faragi: you need to understand how do I find the high level metrics or what
Dr. Sara Faragi: are the privacy considerations?
Dr. Sara Faragi: What in the event of a certain issue, then what is my concern going to be?
Dr. Sara Faragi: And then I might have it review from the perspective of a security analyst
Dr. Sara Faragi: and say what are some different types of issues that you might find?
Dr. Sara Faragi: If you were this Persona, what questions would you ask back at me?
Dr. Sara Faragi: And then I might even ask some
Dr. Sara Faragi: questions like are there any errors in this or is there any information in
Dr. Sara Faragi: this document that isn't answered by the
Dr. Sara Faragi: initial resources that I gave you? Is there any logic that seems unsound? I just go and ask it these questions and ask it to verify and give me really clear answers. And in some ways that's a great
Dr. Sara Faragi: process because I think both the AI
Dr. Sara Faragi: tool and myself, we're both learning at the same time. I'm building kind of my technical knowledge in some areas and it's learning how to write better, how to better explain how to surface gaps. So in that ways it's a mutual learning when we think about it as your co pilot but also you're going to learning partner.
Host: I like the focus on the process and being able to use it to really analyze and to give you feedback, ask questions. So that two way street that you were talking about, I uh, see this having real applications for people who are maybe doing a startup and they have a pitch deck, they could say, hey, shred my pitch deck, tell me what questions I'm going to be asked.
Jill: And it allows you to not only
Host: anticipate the questions that you might be
Jill: asked, but prepare answers for those questions.
Dr. Sara Faragi: Yes, absolutely. I love seeing how you almost ask it to question everything that you have
Dr. Sara Faragi: written and say what, what's the flaw here?
Dr. Sara Faragi: I actually think AI tools work a
Dr. Sara Faragi: lot better that way.
Dr. Sara Faragi: Rather than saying is this good or did I do everything right? I think that the AI tools are a lot better at finding what's wrong
Dr. Sara Faragi: and they, they're good at self correcting too.
Speaker E: It's interesting.
Dr. Sara Faragi: I've been experimenting with using AI tools and looking at GitHub repos, um, and being able to on an automated schedule
Dr. Sara Faragi: like self audit a certain thing.
Dr. Sara Faragi: And it'll be interesting to see how maybe through the first self audit it
Dr. Sara Faragi: didn't find some errors. Then it goes back and says, I,
Dr. Sara Faragi: uh, actually found this other source that
Dr. Sara Faragi: contradicts what I was saying.
Dr. Sara Faragi: And so it's really interesting to be
Dr. Sara Faragi: able to continually question, even have it question itself, to be able to find what the flaws are.
Dr. Sara Faragi: And I would highly recommend that type
Dr. Sara Faragi: of mindset of like going into the negative or having it find what's wrong
Dr. Sara Faragi: rather than just create something or is
Dr. Sara Faragi: this good type of things. I really kind of start with those negative leaning types of questions and it can be, um, you'll be, I think, more impressed with the output.
Host: One of the things I think about is it is hard when you face a blank page. It's much easier to edit someone's work than it is to start with that blank page.
Jill: But there's also sort of a flip side to this as well, where you
Host: have just a jumble of documents and ideas and you need to get it organized. How would you use AI in that situation?
Dr. Sara Faragi: Yes, this happens to me a lot. You will get all kinds of things,
Dr. Sara Faragi: meeting notes or tickets and various sources that might not be organized very properly. And you need to make sense of the mess. And I think that's okay to start with that.
Dr. Sara Faragi: It's better to start with that using an AI tool than without one in some sense because otherwise there's a lot of manual reading.
Dr. Sara Faragi: And like I said with that rhetorical toolkit, I think that the stasis theory
Dr. Sara Faragi: kind of comes into play really well here because you have this note pile,
Dr. Sara Faragi: you have a transcript, just a brain dump, and you bring all these materials and then say, can you look at
Dr. Sara Faragi: these documents through the lens of stasis theory? Or start asking some of those questions I was mentioning, what are the factual claims that we can pull from all these documents that we know need to be surfaced in the article?
Dr. Sara Faragi: And then what are the quality judgments
Dr. Sara Faragi: that we should ask?
Dr. Sara Faragi: You could even ask it just very
Dr. Sara Faragi: briefly, sort these into facts, definitions, kind
Dr. Sara Faragi: of judgment calls, or optional Types of
Dr. Sara Faragi: configurations and things like that. And so that way we're starting from a place of brainstorming and not just create a document out of this. We're saying, can you pull out the facts first? And it's a gradual type of conversation.
Dr. Sara Faragi: And then you can kind of shape
Dr. Sara Faragi: it and evolve it. And maybe it's not until the fourth or fifth prompt where you really start to get into, okay, let's start to build a draft from this.
Dr. Sara Faragi: So I really like starting with that to try to say, before I start
Dr. Sara Faragi: manually reading through all of these things, can you help me pick out what the most salient points are? And then we start from there.
Host: You know, one of the other challenges is AI has been trained as a. You know, it's a service. They want people to keep using it.
Jill: So AI tends to be very flattering
Host: of your work and telling you you've done very good things.
Jill: Have you had any issues with AI not telling you when you've got something wrong?
Dr. Sara Faragi: Yes, this happens a lot.
Dr. Sara Faragi: It is very much wanting to please you and say, yes, this is great. It's very, um, quick to call out
Dr. Sara Faragi: what you're doing well, or this is
Dr. Sara Faragi: gold, all of these things.
Dr. Sara Faragi: It's very aspirational in that way.
Dr. Sara Faragi: And so that's why I think kind of leaning into the negative is important. I think that when you give it
Dr. Sara Faragi: a draft, its inclination is to give you a slightly more polished output, uh,
Dr. Sara Faragi: but it's not necessarily going to give
Dr. Sara Faragi: you a genuine assessment of what's wrong every time.
Dr. Sara Faragi: And so I sometimes will ask it
Dr. Sara Faragi: questions like, what is the weakest part of this argument? Or what would a skeptical reader push back on? Try to look at this from the
Dr. Sara Faragi: perspective of someone who's convinced I'm wrong.
Dr. Sara Faragi: And these go back to rhetorical strategies. When we're teaching English classes, we teach the conversation about developing a good counter argument and a rebuttal. And I think those are good to
Dr. Sara Faragi: keep in mind when working with AI
Dr. Sara Faragi: tools is don't just come to it looking for the praise and saying, here, here's some information.
Dr. Sara Faragi: Really, really ask those deep questions.
Dr. Sara Faragi: And you may find that some of the things that it's pushing back on,
Dr. Sara Faragi: you know, they're maybe they're not really
Dr. Sara Faragi: as relevant, but it's still good to at least see some of that information and see it kind of leaning into the more negative or questioning kind of tone rather than just validating everything you say.
Dr. Sara Faragi: So I think you have to give
Dr. Sara Faragi: it some of these types of prompts
Dr. Sara Faragi: to look at it as a place
Dr. Sara Faragi: of that critical inquiry, the questioning side of things, and you're going to get some better results.
Host: This is where your own domain expertise really can help you. There have been some articles talking about how people who are older are better at using AI because they can interrogate it more effectively and young people maybe don't have as much of a lived experience to see.
Jill: So why is our own domain expertise important?
Dr. Sara Faragi: I think the domain expertise of humans is more relevant than ever. Because if I'm just working with an AI tool and I get an output and I believe it must be valid
Dr. Sara Faragi: because I am not able to question it otherwise, then that's where the danger can lie.
Dr. Sara Faragi: And in some ways I think if
Dr. Sara Faragi: you're just delegating or offloading a certain type of expertise to AI, then you're really doing yourself a, uh, disservice.
Dr. Sara Faragi: And, and again, we have grown up in a culture where we have very
Dr. Sara Faragi: specialized types of knowledge.
Dr. Sara Faragi: Someone is trained to be a writer,
Dr. Sara Faragi: someone is trained to be an engineer.
Dr. Sara Faragi: But I think AI is kind of
Dr. Sara Faragi: breaking down these silos in some ways
Dr. Sara Faragi: and kind of, I think I've heard
Dr. Sara Faragi: the phrase collapsing the talent stack.
Dr. Sara Faragi: Or someone can be a jack of
Dr. Sara Faragi: M all trades and do many of these things with AI, kind of helping to fill in the gaps. And I think that is exciting in
Dr. Sara Faragi: some ways because you can make, uh,
Dr. Sara Faragi: tool and you can vibe code or
Dr. Sara Faragi: something and help to fill in the
Dr. Sara Faragi: gaps that you might not have. But if you don't have that domain expertise to know this is going to work or this is going to scale well, or there's a problem here, then it's not going to be as successful. So I think the domain expertise is important, but I do think that we
Dr. Sara Faragi: can use AI tools to help us
Dr. Sara Faragi: get that expertise and not just take the output at face value.
Dr. Sara Faragi: Something that I've been doing is when I'm looking at steps that are very
Dr. Sara Faragi: technical in nature, I look at the
Dr. Sara Faragi: output that it gives me and then I say, what about, is this supposed to be all one command?
Dr. Sara Faragi: What would happen if they didn't do it this way? If the user did it this way,
Dr. Sara Faragi: what would happen if, if the user approached this in, uh, a different type of angle, what would happen if the
Dr. Sara Faragi: user clicked this instead of that?
Dr. Sara Faragi: And so I keep kind of going
Dr. Sara Faragi: through these different scenarios at every step
Dr. Sara Faragi: and then let the AI kind of
Dr. Sara Faragi: teach me and fill in the gaps. And so I'm building my knowledge and expertise at the same time as I'm also using kind, uh, of my expertise in the writing to be able to frame what it should look like.
Host: The democratization of the technology and the growth mindset really does allow people with problem space expertise to now actually go forward and solve some of these problems. I like this positive spin because I think a lot about atrophy, that we're going to lose some of the skills because we're offloading it to AI, or
Jill: for young people, foreclosure, where they're never
Host: going to learn some of these skills because their AI is going to do
Jill: the work for them. I say that.
Host: But when you are describing these rhetorical
Jill: toolkit, that's really teaching critical thinking skills,
Host: so maybe we don't have to be as concerned.
Dr. Sara Faragi: Exactly.
Dr. Sara Faragi: I think that someone who starts working with AI tools, it's going to be great to see how they approach it
Dr. Sara Faragi: with a skeptical mindset, not just an evangelist mindset. I think there's a lot to be
Dr. Sara Faragi: excited about with AI, but if we
Dr. Sara Faragi: go into things with the perspective of a skeptic, uh, and being able to ask more questions, that we're only going to be able to use the tools better and we're only going to learn more from it.
Dr. Sara Faragi: And so I do think that these
Dr. Sara Faragi: skills that you're learning in English classes and whatnot, they still come into play and they're even more valuable in some ways because we're not just taking the output at face value and saying this must be the fact.
Dr. Sara Faragi: We always go into it with that
Dr. Sara Faragi: skeptical mindset and being able to kind of help us discern what's fact from
Dr. Sara Faragi: fiction, what's credible, what are the edge cases? I think that really the edge cases
Dr. Sara Faragi: are most important when it comes to documentation or any type of writing. We can have it give you an output or say what it is, but the what it's not, or what's on the edges or what are the outliers,
Dr. Sara Faragi: that's what's going to make these documents
Dr. Sara Faragi: and this writing much more valuable. So I'm excited to see how we kind of continue to push on the tools to be able to think more critically alongside us.
Jill: Let's talk more about these tools because there are things you can do with
Host: AI that will lead to those efficiencies. You mentioned earlier, another definition for skills is what are you teaching the AI specific skills, or sometimes they're called gems in Gemini.
Jill: And can you talk a little bit about what you can do to train the AI?
Dr. Sara Faragi: Yes. So I highly recommend using gems and also projects to be able to build
Dr. Sara Faragi: very focused initiatives where the AI is going to Learn over time. You're not just retraining it.
Dr. Sara Faragi: I think with a lot of tools.
Dr. Sara Faragi: We have a chat feature where that's just back and forth conversation. Those are good for just initial kinds
Dr. Sara Faragi: of research or you know, you just want to have a, almost a search
Dr. Sara Faragi: function to be able to ask a question and just get a general answer.
Dr. Sara Faragi: But if there's a project you're working on, you're working on revising your resume
Dr. Sara Faragi: or your cover letter, or you're working on a very specific type of article
Dr. Sara Faragi: project, then I would make some kind of project or a gem where you're going to have a, uh, style guide. You're going to have work samples, you're going to have objectives and almost instructions that you want this tool to know
Dr. Sara Faragi: and repeat and understand. So every conversation you have with it, it's not going to be starting from scratch. It's going to have all of these resources and the answer it's going to
Dr. Sara Faragi: give is going to be closer to
Dr. Sara Faragi: the output that you want. And over time you can even talk with it and say, for example, I
Dr. Sara Faragi: have my style guide, but I'm realizing that my style guide, I want it
Dr. Sara Faragi: to evolve over time. I don't want it to be static. There are these just different edge cases that I want to keep in mind. Tell it that in the project and
Dr. Sara Faragi: I'll say, okay, I'll update the master
Dr. Sara Faragi: file, it'll do that for you.
Dr. Sara Faragi: And then it'll help to format the
Dr. Sara Faragi: output from now on using what you've given it.
Host: You've mentioned style guide a couple of times.
Jill: How do we teach AI to speak in either our own voice or our corporate brand voice?
Dr. Sara Faragi: That's a good question.
Dr. Sara Faragi: I think that what I would suggest
Dr. Sara Faragi: is first starting with the personal voice
Dr. Sara Faragi: and what you like and you can even use an AI tool to give
Dr. Sara Faragi: it an initial document.
Dr. Sara Faragi: Maybe there is a style guide that
Dr. Sara Faragi: you have, or even if you don't
Dr. Sara Faragi: have one, just say I want to make a style guide.
Dr. Sara Faragi: And it might give you kind of a quiz question and it might give
Dr. Sara Faragi: you two side by side documents and
Dr. Sara Faragi: say which one looks more like you.
Dr. Sara Faragi: And you go through this process, you
Dr. Sara Faragi: can ask it to and then eventually
Dr. Sara Faragi: it's going to be able to make
Dr. Sara Faragi: your own style guide based on your own voice. And it'll say does this sound like you? And give you options like this sounds like me and be very straightforward. You'll, it'll get to learn more about what are your convictions, what would you never say? What would you say?
Dr. Sara Faragi: What sounds more like you and then from there you can really be able
Dr. Sara Faragi: to have the AI start to sound more like you. And then when you have the corporate style guide that might emphasize more mission, vision, values and things like that, and seeing, uh, if you can kind of merge them, say, here's my company's mission, vision, values, here's some examples of documents
Dr. Sara Faragi: that they have and their writing style.
Dr. Sara Faragi: Are there ways that we can merge them? I almost make kind of hybrid style guide. And maybe you're also building your style guide off of MLA AP style, like a master style guide that a lot of organizations use. You can almost use AI tools to kind of find that middle ground among these style guides and adapt it over time.
Host: This might be technical, but if you've
Jill: given it a bunch of examples of
Host: your voice, the way you write, and
Jill: you've asked it to create this, how do you save that style guide and
Host: then how do you use it when you want to draft an article or write an email?
Dr. Sara Faragi: Yes, I think the style guide really has to have multiple parts. One, it's what are the rules and
Dr. Sara Faragi: what are the formatting choices that you want it to follow?
Dr. Sara Faragi: And then also I would have as
Dr. Sara Faragi: part of it, uh, what would I never say? For example, I think there are a
Dr. Sara Faragi: lot of even writing choices that AI
Dr. Sara Faragi: tends to gravitate toward. The EM dash is a classic one.
Dr. Sara Faragi: And lately I'm noticing the. It's not this, it's that. Not, you know, the, these types of
Dr. Sara Faragi: styles that are very almost cliche.
Dr. Sara Faragi: There are things that probably come up
Dr. Sara Faragi: in a lot of writing.
Dr. Sara Faragi: If we're looking at all the writing in the world that AI is picking
Dr. Sara Faragi: up on, it probably sees these repeated modeling after human language.
Dr. Sara Faragi: But now I think we're getting at a point where that's becoming too repetitive
Dr. Sara Faragi: and doesn't make us unique. So in your style guide you have maybe you want to set some constraints. I don't want to be using too many or of these. I don't want the whole document to be kind of full of this repetitive type of word choice or sentence structure.
Dr. Sara Faragi: And then also I think having the examples let the AI know what good
Dr. Sara Faragi: looks like to you and show it. These are examples of things that I
Dr. Sara Faragi: have written without AI tools.
Dr. Sara Faragi: And this looks good to me. This is natural. This is something that is ideal. It needs to be able to understand that as opposed to all of the writing in the world.
Dr. Sara Faragi: So again, having with your style guide, the examples are good and, and you
Dr. Sara Faragi: can with certain tools like the projects,
Dr. Sara Faragi: maybe you just have this file.
Dr. Sara Faragi: It's like a markdown file or something that is in a folder that your AI tool can read from or you can upload it to the specific project. So it's always going to reference that.
Host: So you can tell it to avoid these sort of robotic tells that it's been written by AI. You can tell it to, hey, I don't want to be trite, I don't want to use, you know, common phrases and then you give it the positive guide.
Jill: But at the end of the day,
Host: how do you maintain authenticity? You know, if you're an HR person
Jill: and you're trying to rewrite a job description and you, you want people to want to work at your company, how do you avoid not sounding generic or rote?
Dr. Sara Faragi: I think that sometimes with these documents it can be very easy to let
Dr. Sara Faragi: the AI slip and use language like
Dr. Sara Faragi: our ideal candidate wants to be X, Y and Z. Or it might say like the cliche
Dr. Sara Faragi: kind of language, like I need the
Dr. Sara Faragi: candidate to wear many hats or to be able to work in a fast
Dr. Sara Faragi: paced environment and things like that. And those all might be true, but
Dr. Sara Faragi: if they're all put together in the
Dr. Sara Faragi: job description, then it feels vague or
Dr. Sara Faragi: it feels, it might even have a
Dr. Sara Faragi: negative connotation that uh, oh, this job might not be too specified. And so something I recommend if you
Dr. Sara Faragi: are writing a job description or working
Dr. Sara Faragi: with any kind of corporate language is to ask the AI tool to push
Dr. Sara Faragi: back and say questions. Just start asking the AI questions and
Dr. Sara Faragi: think about is, uh, is this job
Dr. Sara Faragi: description written for somebody who really loves
Dr. Sara Faragi: this type of environment? What would a candidate find confusing about this?
Dr. Sara Faragi: What would a candidate find vague and be able to ask it those and how can I write this job description
Dr. Sara Faragi: in a way that sounds engaging? And you still might have to go
Dr. Sara Faragi: back and question on that because then it might give you a lot of
Dr. Sara Faragi: kinds of language like with exclamation marks or with just general vague, like happy language too. When you describe the tone, just be specific and clear about what you want things to look like.
Jill: In some ways, the sea of sameness
Host: happens on the flip side as well. When people are applying for jobs, they're using AI to help write their cover letter. They want it to be specific to the job and they want to make sure they're mentioning the keywords so they can get through the filters.
Jill: What is your advice to people using
Host: AI to write those kind of career applications?
Dr. Sara Faragi: Yes, I think that the best way to start with writing a cover letter or resume is to first look inward and not outward. And so by That I mean, you might give the AI tool your current
Dr. Sara Faragi: resume or your cover letter, or even
Dr. Sara Faragi: if you don't have these documents yet,
Dr. Sara Faragi: just start explaining a little bit about your background and some work experience you've had and ask the tool, what types of jobs would I qualify for in this job market?
Dr. Sara Faragi: Or what would you say are my
Dr. Sara Faragi: strongest skills that would look attractive to employers? And sometimes the AI tools can flag
Dr. Sara Faragi: things that maybe you didn't even realize
Dr. Sara Faragi: were the most valuable skills and things like that. And so first, just start even before you look at a specific job ad, and just start by looking within and
Dr. Sara Faragi: think about how you can really build
Dr. Sara Faragi: like a good kind of master resume or cover letter template, almost like that
Dr. Sara Faragi: style guide, like, see, how can I
Dr. Sara Faragi: answer certain questions, Maybe set up kind of a, an interview with your AI tool to be able to do some of that introspective work and learn more about yourself. And then when it comes to starting to apply, maybe you ask the AI
Dr. Sara Faragi: tool to different job ads and think, what I would maybe ask the AI tool to consider, what types of job
Dr. Sara Faragi: roles would I most qualify for and
Dr. Sara Faragi: what skills and experience are required or recommended for these jobs and have those
Dr. Sara Faragi: conversations to better understand how would I tailor my resume for these fields. And then after you have that back and forth, then you start to look
Dr. Sara Faragi: at actual job ads and then bring those in. And even before you start matching the
Dr. Sara Faragi: resume and the COVID letter with the job ad, say, here's the job ad. What are the top skills that this employer is looking at out of all of these different requirements? What is the employer really asking for? These are kinds of good questions to maybe get some good results to surface. Then after you just start learning a little bit more about the job ad and trying to surface, you know, from this long list, what's hidden or what's interesting, Then start to put your existing resume or cover letter against the tool and think about what, what should I change? What should I surface? Maybe you need to tell more of the story. I use the STAR method, the situation, task, action, response.
Dr. Sara Faragi: I like to kind of work with AI tools to say, can we look at my bullet points and help me
Dr. Sara Faragi: flesh out the star method for these? And then maybe I work backwards in that way to think, okay, now that we have more of that context and that rich information now can we go back and kind of reformat that bullet point with the context in mind to
Dr. Sara Faragi: really show what the values and what
Dr. Sara Faragi: the kind of key metrics, what the
Dr. Sara Faragi: roi, all of these different things were
Dr. Sara Faragi: that maybe weren't very evident in the first draft.
Dr. Sara Faragi: And of course give it some constraints.
Dr. Sara Faragi: Don't make up experiences or information to fit what they're asking for and whatnot.
Host: I like the focus on specificity. If you can write something in your cover letter that anyone can write in their cover letter, that's not doing you any favors because AI will generate that sentence for everybody. So to that tying back to that star method and what have I done specifically that demonstrates this skill rather than saying I'm good at, you know, managing details.
Dr. Sara Faragi: Yes, exactly. I think the specificity is important. Example I use sometimes where AI tools can help is maybe you need to
Dr. Sara Faragi: start thinking about your resume and your
Dr. Sara Faragi: cover letter less in a task oriented format and more in what was the
Dr. Sara Faragi: value that I brought? Like a value add resume.
Dr. Sara Faragi: But again, if you, if you don't
Dr. Sara Faragi: have enough information to share, it's going to sound like every other resume and then it's not going to help you succeed with the, you know, the ATS
Dr. Sara Faragi: and all these different factors. Because if it's seeing the same thing
Dr. Sara Faragi: across a hundred resumes, you're not really going to stand out. Can use the AI tool to help you understand what the value really was. That's beyond the task. But you have to do that work of being able to balance what is clear and correct with what is unique. What stands out, what would be impressive to this audience? I think also asking the tool those questions of would this appeal to this hiring manager? And things like that would be important.
Host: AI can really help you prepare for interviews. It can help you to network. Is there any fear of being too prepared? A little creepy knowing a little bit
Jill: too much about the person you're talking to.
Dr. Sara Faragi: It's funny because you can certainly use AI tools to do the open source intelligence or the Ocean OSINT work on
Dr. Sara Faragi: your hiring manager or the recruiter, the
Dr. Sara Faragi: company, things like that. And what I would recommend is you
Dr. Sara Faragi: can do that research, that's great.
Dr. Sara Faragi: But try not to come into the interview or have your cover letter say
Dr. Sara Faragi: I really align to your mission and
Dr. Sara Faragi: then just repeat the mission statement or something like that. Think about what are the specific areas
Dr. Sara Faragi: of that mission or the values that align with your own personal mission statement or your own values and think about where they align.
Dr. Sara Faragi: And I think the same thing can
Dr. Sara Faragi: apply when it comes to the AI tools.
Dr. Sara Faragi: I think some people go into these
Dr. Sara Faragi: interviews and they'll ask, what is your AI policy? I want candidates to think more about what is their personal AI policy? What are they going to use the AI tools for? What are they never going to use AI tools to do? What is your kind of philosophy on this?
Dr. Sara Faragi: And then, you know, when you're asking
Dr. Sara Faragi: that question of uh, what is the company's AI policy, think about how does it align with your own.
Dr. Sara Faragi: Because I think you'll most likely find
Dr. Sara Faragi: that companies may not have a fully fleshed out AI policy. They may want you to use it, but they don't quite have those guardrails in place. It's just we have to adopt this
Host: really levels up the con, levels up the conversation, because it allows you to
Jill: say, I've thought about these issues, I've thought about what responsible and ethical AI is.
Host: This is what it means to me. This is my practice and my process.
Jill: Here's how I ensure that I'm getting accuracy.
Host: And I think that's really interesting because there's sort of this double whammy today where they expect you to use AI, but if you use AI, they don't
Jill: believe you can do it without AI.
Host: But if you can explain your AI policy as you call it, that's going to show the critical thinking skills. To your point, they're looking for the skills, not the tasks.
Dr. Sara Faragi: Exactly.
Dr. Sara Faragi: And um, at uh, the company I work for, there's a big emphasis on AI native mindset. They want everyone at the company to be AI native.
Dr. Sara Faragi: And I've been thinking quite a bit about what that means because AI native
Dr. Sara Faragi: doesn't mean I am going to use AI tools for everything I do to
Dr. Sara Faragi: the point where I'm just automating myself out of this role and the AI is taking control. It's really being thoughtful about what types of tasks AI is going to be able to help you with and can continually questioning your current workflows and think where would it make sense to use
Dr. Sara Faragi: an AI tool or kind of automate this?
Dr. Sara Faragi: For example, I've been using tools for scheduled tasks to be able to look through all of these different sources that I'm working with, uh, whether it's email and tasks, all of these different tools
Dr. Sara Faragi: that I use on a regular basis. Can it surface a really cohesive to
Dr. Sara Faragi: do list of what I need to
Dr. Sara Faragi: do when I finished a two week sprint or something. Can it automatically look at all of those tickets and generate a summary that
Dr. Sara Faragi: is tailored for a certain team's audience to be able to communicate to that, that information to them? I mean there are some things where
Dr. Sara Faragi: the repetitive tasks or the things that
Dr. Sara Faragi: are maybe on your task but maybe they're not your favorite things to do. Like there might be some Good ways to find automation.
Dr. Sara Faragi: And then there's ways where you know,
Dr. Sara Faragi: you thinking of your own personal, your deep thinking and your skills where your expertise is going to be best served.
Dr. Sara Faragi: How can AI be that kind of
Dr. Sara Faragi: co worker or co pilot for you,
Dr. Sara Faragi: but not just fully handing over the reins? I think that's really what AI Native
Dr. Sara Faragi: is, is how do you kind of restructure your thinking?
Dr. Sara Faragi: In a lot of ways it' embracing
Dr. Sara Faragi: and understanding yourself a bit more. It's a good opportunity to really be thinking more about what makes you unique and stand out.
Dr. Sara Faragi: And how are you going to be
Dr. Sara Faragi: in the driver's seat when it comes to AI, not just kind of this passive role and letting it take control. So being very clear and having a strong statement on how you're going to use these tools, what you're planning to
Dr. Sara Faragi: learn from them, how is AI going
Dr. Sara Faragi: to fit into your overall career strategy? And these are all great things to be thinking about.
Host: These are super helpful tips. And I love the fact that we're looking at applying this information and putting it into the workplace and using it to prioritize, using it to kind of augment and support the work that we're doing so we can do it better with less of the annoying parts of our job. But AI is changing so quickly, so fast.
Jill: What are the things they can do that will make staying current possible?
Dr. Sara Faragi: That's a great question, because I think it is overwhelming in some sense, the notion of everything is changing every day. We can't keep pace of all of these different tools, but I would just
Dr. Sara Faragi: keep an ear open. It's kind of that social listening of looking what's happening on LinkedIn or social media or what your colleagues are doing.
Dr. Sara Faragi: I do think that one big risk that I'm noticing is that everyone is working on these AI tools in their
Dr. Sara Faragi: own individual silos in some ways and they might be learning new things.
Dr. Sara Faragi: But if you're learning it and you're
Dr. Sara Faragi: helping with your own personal workflows, how can you help the broader team?
Dr. Sara Faragi: Or maybe there's someone at a different
Dr. Sara Faragi: company out there who's using the tool in a way that you hadn't thought about. So just be vocal, keep your ears
Dr. Sara Faragi: open, your eyes open everything, and look
Dr. Sara Faragi: for ways to collaborate. I think another thing that would be
Dr. Sara Faragi: good to do is to kind of
Dr. Sara Faragi: make a plan, a schedule, and you
Dr. Sara Faragi: could use an AI tool to even
Dr. Sara Faragi: help you with this. Like, uh, what is make sure that you're learning something specific every day or reaching a goal.
Dr. Sara Faragi: And maybe one of those is, I want to spend 10 minutes a day training my resume builder AI tool or I want to spend 10 minutes a
Dr. Sara Faragi: day building my domain expertise in this
Dr. Sara Faragi: specific area and I want to use this AI tool to help me learn
Dr. Sara Faragi: something new every day about this. So I think just being consistent, you might not have all the answers today, but trying to develop that plan of
Dr. Sara Faragi: action and learn a little bit every single day.
Host: Well, thank you for sharing your knowledge.
Dr. Sara Faragi: Thank you so much.
Dr. Sara Faragi: It was a great conversation. I appreciate your time. Jill.
Host: Thank you so much.
Jill: And with that, I hope you enjoyed
Host: this latest in a long series of
Jill: podcasts that we'll be sending your way every month.
Host: Please share with friends and colleagues who
Jill: may be interested in taking this Future
Host: of Work journey with us.
Jill: And make sure to check out extension berkeley.edu to find a variety of courses and certificates to help you thrive in
Host: this new working landscape. And to see what's coming up at
Jill: Edge and Tech, go ahead and visit Edge Berkeley Edu. Thanks so much for listening and I'll be back next time month to continue our Future of Work journey. The Future of Work podcast is hosted
Host: by Jill Finlayson, produced by Sarah Benzulli, and edited by Matt DiPiet.
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