I’m one of those people who thinks that “artificial intelligence” is a misnomer. So is “machine learning” and, I hasten to admit, I sometimes extend this line of criticism all the way to such familiar things as “computer memory” and “programming language”. That is, I’m a bit of a kook. It is my deep conviction that computers can’t think, speak, or remember, and I don’t just mean that they can’t do it like we do it; I mean they can’t do it at all. There is no literal sense in which a machine can learn and, if we are to take it figuratively, the metaphor is stone dead. Much of the discourse about the impending rise of artificial general intelligence these days sounds to me like people earnestly claiming that, since they have “legs”, surely tables are soon going to walk. We have not, if you’ll pardon it, taken the first step towards machines that can think.

To fully appreciate my seriousness on this point, let me try to persuade you that pocket calculators can’t do math either. They have a long and very interesting history and, until I looked into it, I didn’t realize that it was actually Blaise Pascal who invented the mechanical adding machine – the Pascaline — in 1642. But, before this, there was always the abacus, and before this there was the root of the word “calculus”, namely, “chalk,” or the small limestone pebbles that were used as counters and eventually become the beads on the wires of counting frames. Interestingly, the word “abacus” originally denoted a writing surface of sand that was also used to do calculations. In any case, I hope you will immediately agree that a pile of pebbles or a string of beads can’t “do math”. A paper bag that you put two apples into and then another two is not capable of addition just because there are, in fact, four apples in the bag when you look.

Is it such a leap from this to the electronic calculator? Do we have to imbue it with “intelligence” of any kind to make sense of it? Some will point out that calculators use numbers and operators in their symbolic form as input and output. You type “2 +2 =” and you get “4” back. But suppose you have an ordinary kitchen scale and a bunch of labelled standard weights. Surely you can get it to “add up” the weights for you? Or you can imagine a plumbing system that moves quantities of water in and out of tanks, marked off with rulers so that the quantities are made explicit. Whether these systems are manual, hydraulic, mechanical, or electronic doesn’t change the fact that these are just physical processes that, properly labelled, give us an output that we humans can make sense of.

That’s all very well, you might say, but have I tried ChatGPT? How do I explain the perfectly intelligible output it produces daily? Here’s my take: it articulates words, like a calculator calculates numbers. To calculate is basically just to “keep count”. To articulate is just to “join up”. A machine that is capable of keeping count is no more intelligent than a paper bag, nor is a machine that is capable of joining words together. Imagine you have three bags, numbered 1, 2, 3. In bag number 1 there are slips of paper with names on them: “Thomas”, “Zahra”, “Sami”, “Linda”. In bag number 2 there are phrases like “is a”, “wants to be a”, “was once a”, and so forth. In bag number 3, there are the names of professions: “doctor”, “carpenter”, “lawyer”, “teacher”, etc. You can probably see where this is going. To operate this “machine”, you pull a slip of paper out of each bag and arrange them 1-2-3 in order. You’ll always get a string of words that “make sense”. Can this arrangement of three bags write? Of course not!

In a famous essay, Borges credits Ramon Llull with the invention of a “thinking machine” that works much like this. Or, rather, doesn’t work: it is not “capable of thinking a single thought, however rudimentary or fallacious.” Llull’s device (or at least the device that Borges imagined based on Llull’s writings) consisted of a series of discs that allowed the operator to combine (or “correlate”) agents, patients, acts. (I wonder if this is where the “robot rights” people got the idea of distinguishing between the moral “agency” and “patiency” of subjects.) “Measured against its objective, judged by its inventor’s illustrious goal,” Borges tells us, “the thinking machine does not work,” but, like all metaphysical systems, he also points out, its “public and well-known futility does not diminish [its] interest.”

The machinery has become a lot more complicated since Pascal and Llull. But I want to insist that it has not become more mysterious and, by the same token, not more intelligent. That is, we don’t need a “ghost in the machine” to explain how the prompt we give to a language model spurs it to produce an output that, on the face of it, “makes sense”. Just as the calculator has no “understanding” of numbers or quantities or the mathematical operations it carries out, so, too, does ChatGPT have no conception of what the prose it generates means. All it does is to convert a text into a string of numbers, those numbers into vectors in a hundred-dimensional space, in which it then locates the nearest points and, from these, chooses one of them at somewhat random (depending on the “temperature”). It converts the result (which is just a number) back into a word or part of a word (by looking it up in a table) and adds this to the string it is building. It repeats the process to find the next word. If “artificial intelligence” is a misnomer, what would I call these machines? They are electronic articulators.

I doubt this will catch on. In 1971, the year I was born, Sharp marketed its EL-8 calculator as “a really fast thinker” and I remember, ten years later, my elementary school principal announced that a computer (an Apple II+) would “moving in”. It was all very exciting.

“Your daddy’s rich
And your ma’ is good looking…”

I encourage scholars and students to work on their writing in a deliberate and disciplined fashion 32 weeks out of the year — 16 in the fall and 16 in the spring, each divided by a one-week break into two stretches of 8. This leaves 5 weeks in the winter 13 weeks in the summer for more impulsive and improvised pursuits. The winter includes some time off for Christmas and, if you’re like me, indulging your melancholy disposition. In Denmark, it’s customary to take a three-week summer vacation, so that leaves 10 weeks to work in a less rigorous key. I won’t pretend to know how students should spend their summers, but, for scholars, some of that time is usually devoted to exams and conferences anyway. So it all usually works out pretty well. By mid-August, they return, hopefully refreshed, to the discipline of composing paragraphs, one at a time, about things they know for peers they respect.

We’re two weeks into summer here. The other day on Twitter, I stumbled on an apposite exchange between two poets. “Many things are very hard but nothing is hard the way writing is hard,” said Lindsay Turner. “Kenneth Koch was very fond of Valéry Larbaud’s line about facilité,” replied Jordan Davis. This piqued my interest (and Henry Gould’s) and we set about trying to locate the source. I soon found Koch’s remark: the transcript of a 1993 talk her held at the Center for Imaginative Writing of the Teachers & Writers Collaborative.

It really is true about Whitman what the French writer Valery Larbaud said, that the main thing that Whitman showed to twentieth-century American poets was that greatness in poetry can come not from difficulties overcome but from — and this is better in French, facilités trouvée — easinesses found.

 Kenneth Koch, Teachers & Writers Magazine (1994, Vol. 25, No. 4)

Well, that was certainly interesting for me to hear, having just written written two posts about the “measured little difficulties” we call paragraphs! “I’m not here to make writing easy,” I had tweeted almost exactly a year ago, “but I may be able to help you locate the difficulty.” And the difficulty is always the difficulty your reader faces in trying to believe, understand, or agree with you. Lindsay Turner is right that there’s no difficulty quite like supporting, elaborating, or defending a claim in writing. But was Kenneth Koch (and is Jordan Davis?) right to counter that we sometimes do better to find writing easy than to face it as something hard? The idea is certainly worth exploring.

Ezra Pound used to say that a poem is the “record of a struggle”, and his own Cantos can rightly be called an epic struggle with his material. (Some would argue it was also a failure of epic proportions, a tragedy of literature.) Whitman’s Leaves of Grass, on the view we’re exploring, would be more like the record of loafing in an orchard, picking low-hanging fruit from the trees. In one sense there is no contradiction here. A teacher, and certainly a coach, is always helping you find the difficulty so that you can master it in a general way, making it at least look easy when you do it from then on. Could I not argue that my approach is, basically, to pick the ripe, low-hanging fruit every day? Choose paragraphs to write that are well within your ability. Choose your subject and your reader wisely so that the problem is not one of knowing what you’re talking about, nor who you are talking to, but simply that of saying it as clearly as possible. You don’t want your difficulty to be that of knowing the material, just the difficulty of presenting it.

Let’s resolve this summer to take it easy! That is, instead of writing the paper you think you have have to write, instead of “getting things done”, go after those facilités trouvées that Larbaud was talking about. Just pick something you know very well and a reader whose company you enjoy, and write freely and easily exactly what you think, in your own voice. In the morning, rise up singing, spread your wings, and take to the sky. In the moment of writing, there’s nothing that can harm you.

An 8000-word paper in the social sciences consists of about forty paragraphs. With a few exceptions, each paragraph supports, elaborates, or defends a claim that the writer presumably thinks is true. The claim poses a particular difficulty for the reader — it may be hard to believe, hard to understand, or hard to agree with — and the paragraph helps the reader overcome this difficulty. The reader may be provided with evidence to foster belief, illustration to clarify meaning, or arguments to address objections. Since a paragraph consists of no more than two-hundred words, it must accomplish its task in less than a minute of the reader’s attention. A paper occasions forty such difficulties and equips the reader to face them. It takes less than hour to read.

Since it takes 27 minutes to write a paragraph, a paper can be written — once — in 20 hours. Working 2 hours a day, taking three-minute breaks between paragraphs, a paper can be written in two weeks. You can even take the weekends off. At the end of each day, decide what four paragraphs you will write tomorrow, assigning a key sentence and a half hour to each; at the beginning of the next, pose each difficulty and compose each paragraph in 27 minutes. Then get on with your day. You probably have other things to think about too, but you can take an hour or two in the afternoon to reflect on the larger structure of your paper and your line of argument. The important thing is to make a decision, when your working day is coming to a close, about what paragraphs you will write tomorrow. Whatever you’ve been struggling with, you need to pick four things you know are true to write about in the morning.

Remember that 27 minutes is 27 times longer than the reader has to read your paragraph. Use the time to make the text as easy to read as you can. A paper consists of forty little difficulties, not one huge impossibility, and it is your job as a writer to cut the reader’s work out for them. Take your time, choose the right words and put them in the right order. Be conscious of the effect you are trying to have on the reader. What experience are you trying to get the reader to have? What claim should the reader feel is being supported, elaborated, or defended?

You can get an overview of these experiences by making an outline that simply lists the key-sentences. A good paper will make sense at that level; that is, if you read your key sentences one after the other, without the rest of their paragraphs, you argument should make sense but, of course, lack a certain persuasiveness. Just looking at the key sentences, however, you should feel that you know they are true, and you should even be able to call to mind your reasons for thinking so. Also, with your reader in mind, each of the key sentences should represent a difficulty to overcome: will the reader need help believing, understanding, or agreeing with it? This difficulty is the occasion you will rise to on each half page of your paper.

A paragraph is a deliberate act. It presents one thing you know in at least six sentences and at most two-hundred words and, if you let it, takes exactly twenty-seven minutes to write. It occupies one minute of the reader’s attention, during which it supports, elaborates, or defends a proposition that you have good reason to believe is true. After reading, the reader may still have doubts, questions, or objections, but your position will be clear and you will have given the reader an occasion to tell you that you are wrong. You respect the reader as a knowledgeable peer and you want to know what they think. You have deliberately opened yourself to criticism.

It is my aim to help you become more capable of this act. You can find out how good you are at it by doing a simple exercise. At the end of today, at the moment when you put away your research and begin to relax, write a simple declarative sentence about something you are knowledgeable about. Choose something you find it easy to think and talk about, something that you’ve got your mind all the way around. Write one true sentence about it and plan to write a paragraph about it tomorrow morning during the first half hour of intellectually demanding work you will do. Then put it out of your mind. Tomorrow morning, compose a paragraph of at least six sentences and at most two-hundred words. Set a timer for 27 minutes and stop when it tells you to. That’s it. (Well, almost.)

Maybe you can already see the difficulty. If not, you will experience it concretely when you try it. In order to get a sense of what I am trying to teach you, imagine a sixteen week period (roughly, a semester) in which you do this exercise every day, five days a week. Imagine writing 80 deliberate paragraphs. Even if you didn’t listen to another word I say, I’m sure you will agree that this would make you a better writer of paragraphs. At the very least, it would make you accutely aware of the difficulty of writing paragraphs; and this awareness, I would argue, can’t but make you a better writer of prose. It would also, and not incidentally, make you a better knower of things. It would make you a more knowledgeable person.

In order to get something out of my approach, you don’t have follow such a rigorous discipline. But I do encourage you to practice as you go. I am a coach, not an entertainer. You will not really understand what I am trying to tell you if you don’t actually sit down to write some paragraphs of your own. And I really do mean “paragraphs of your own”. You want to become better at writing down anything you know in a way that opens it to the criticism of a knowledgeable peer. I don’t know you and I am not your peer, so you can’t expect me to tell you whether or not you are improving, nor give you simple recipes or templates to follow. You will be struggling to write down your own ideas for scholars or students in your own discipline.

If I were telling you how to draw hands I would tell you to look at your hand and draw it. Yes, I could assume that it has a front and back, fingers, wrist, palm, etc. (But not with 100% confidence, of course.) I could tell you to notice these things — their outlines and surfaces. But I wouldn’t know exactly what you see or how it would best be rendered on the page. It is the same when it comes to writing. I tell you to think of things you know, consider them carefully, think of your reader, and then write one or two hundred words to help them overcome the small difficulty your knowledge implies. That’s what a paragraph is: a measured little difficulty for your reader to overcome. It takes about a minute of their time and, like I say, when you’re working well, about half an hour of yours.

There’s a good interview with Rodney Brooks about artificial intelligence at IEEE Spectrum. I was struck especially by an idea that he has been promoting for some time, namely, that the way we generalize from performance to competence in humans cannot be applied to machines. If a human being is able to perform some cognitively sophisticated task we are warranted to assume that they can perform many other sophisticated tasks, whereas when a machine does something similar, we can’t use that as an indication of some underlying general competence. The reasons for this are nicely explained, as Brooks points out, by a recent blogpost by Stephen Wolfram, which everyone who wants to have an opinion about ChatGPT should probably read. The point is that once you know how ChatGPT does what it does, you can’t attribute sentience to it just because it uses language in an almost human way. By contrast, when a human body uses language, it is a clear indication of a deep and broad array of cognitive functions. As far as we know, human beings can’t use language without being sentient (and conscious and intelligent). And once we know this about them, we know a great deal about what they’re capable of, just from watching and listening to them speak.

This is why the sudden emergence of language models has been such a shock to many of us in academia. We have been accustomed to taking the performance of students in their writing assignments as a good indication of their knowledge competence. Consider the following paragraph, which I easily coaxed out of ChatGPT (3.5) in a few minutes:

According to Weick (1995), sensemaking is a reflective and retrospective process. Weick (1996, p. 54) defines sensemaking as an "ongoing retrospective process of forming images that justify what people are doing." It is a cognitive mechanism that individuals and organizations employ to comprehend complex and ambiguous situations. Sensemaking involves looking back at events and experiences, constructing meanings, and forging understandings. By interpreting and attaching significance to events based on existing mental frameworks, sensemaking allows for the creation of order and coherence amidst uncertainty. Weick emphasizes that sensemaking is an ongoing and iterative process, continuously evolving as new information and perspectives emerge. It encompasses the act of storytelling and constructing narratives to give meaning to our experiences. Sensemaking extends beyond the individual, serving as a social process that takes shape through interactions and conversations. It serves as a means to reduce ambiguity, facilitating decision-making in intricate and turbulent environments. Weick highlights the importance of sensemaking in generating and maintaining a coherent understanding of the world around us. Additionally, sensemaking plays a pivotal role in sensegiving, the process of effectively communicating and influencing others' understanding of a given situation. By elucidating Weick's perspective and incorporating his quote, it becomes evident that sensemaking is a fundamental tool for navigating complexity and making informed choices.

I gave it the key sentence “Sensemaking is a retrospective process”, the source (Weick 1995), and the quoted definition (from memory, wrong year, wrong page). I had it think about how to pitch the key sentence, brainstorm some sentences for the body of the paragraph, and then compose one coherent paragraph that helped the reader understand Weick. After a little more back and forth, the result was the above paragraph. At no point did I edit the paragraph. That is, none of the sentences are mine.

I then asked it to “construct a one-paragraph description (a story) of sensemaking in action to illustrate these ideas”. It gave me this:

Sarah, a project manager, found herself facing a daunting challenge. The unexpected departure of a key team member had left the project in disarray, with looming deadlines and a complex web of interdependent tasks. Engaging in sensemaking, Sarah began her reflective journey. She revisited past team meetings, scrutinized project documentation, and engaged in conversations with remaining team members. As she immersed herself in this retrospective process, images started forming in her mind, providing justifications for the team's current situation and possible paths forward. Sarah realized that the departure of the team member had disrupted the workflow, leading to miscommunication and overlapping responsibilities. Drawing upon her mental frameworks, she began constructing a narrative, identifying the root causes and envisioning potential solutions. She engaged the remaining team members in discussions, seeking their perspectives and insights. Together, they collaboratively made sense of the situation, aligning their understandings and identifying actionable steps. Through this ongoing and iterative sensemaking process, Sarah and her team regained clarity, rebuilt cohesion, and developed a shared understanding of the project's direction. Sensemaking not only empowered Sarah to navigate complexity but also fostered a collective sense of purpose, enabling the team to move forward with confidence and resolve.

Now, there is perhaps nothing Earth-shatteringly brilliant about these two paragraphs. But, in the old days, working on the assumption that the student had actually written them, I would have inferred a relatively deep underlying competence in them. The student is able to present an understanding of what they have read; indeed, they could presumably not have written that paragraph without reading Weick. Also, they are able to imagine or observe a reality that corresponds to the concepts they have introduced. It could be argued that the “imaginative” or “empirical” material is a bit abstract. But it didn’t take me much more coaxing to get ChatGPT to give something more concrete:

But the piles of data on Sarah's desk weren't sufficient. She craved the human insights that could illuminate the path forward. With determination, she picked up the phone and called the remaining team members, inviting them for a face-to-face discussion.

In a small meeting room, Sarah sat across from John, a seasoned team member who had been with the project since its inception. She leaned forward, her voice earnest, "John, I need your help. I want to understand what went wrong and how we can fix it. Tell me about your experiences and frustrations."

John's brow furrowed as he recalled the recent challenges. "Well, Sarah, since Mark left, communication has become a nightmare. We used to have regular team huddles where we shared updates, but without him, things have fallen apart. Everyone seems unsure of their responsibilities, and tasks are slipping through the cracks."

Sarah nodded, her notepad ready to capture every valuable insight. "I see. Can you provide specific instances where miscommunication occurred? Any ideas on how we can improve the clarity of roles?"

John scratched his head thoughtfully. "One example is the client meeting last week. We were all working on different aspects of the project, but nobody knew what the others were doing. During the meeting, the client asked questions that none of us could answer. It was embarrassing and made us look unprepared."

Sarah scribbled notes, her mind racing to identify patterns. "So, improved communication and clearer role delineation are crucial. What suggestions do you have for addressing these issues, John?"

John leaned back, his expression thoughtful. "We need a central hub for information, where everyone can access updates, share progress, and see the big picture. Regular team meetings should be reinstated, so we can align our efforts and address any roadblocks together. And we need to clarify each team member's responsibilities and establish clear lines of communication."

Sarah's eyes lit up with excitement. "Those are excellent suggestions, John. I truly appreciate your insights. Let's discuss these ideas with the rest of the team and see how we can implement them effectively."

As Sarah continued her conversations with other team members, she encountered similar stories of miscommunication, frustration, and potential solutions. Jennifer, a detail-oriented analyst, shared her experiences with overlapping responsibilities that resulted in redundant work. David, a junior developer, expressed his struggles to navigate the project without clear guidance.

Armed with these specific insights, Sarah synthesized the collective wisdom and proposed tangible actions during their next team gathering. The air buzzed with anticipation as Sarah laid out the proposed central hub for information sharing, the reinstatement of regular team meetings, and the need for role clarity. Dialogue ensued, with team members offering further suggestions and refining the proposed solutions.

Through these concrete conversations and shared experiences, Sarah and her team co-created a roadmap for moving forward. They set deadlines for implementing the new communication practices, assigned responsibilities for maintaining the central hub, and established a process for clarifying roles and expectations.

The team members left the meeting feeling heard, energized, and part of a collective effort. Concrete steps had been taken, thanks to the specific insights shared during their conversations. The path forward was clearer, and a sense of unity and purpose permeated the team.

Again, this isn’t profound stuff. But a human student who could do this, either through imagination or observation, would be showing they can do many other things. I keep saying “imagination or observation” because, in the case of a human student, such an account may be presented as made up or as based on data. We expect the student to be honest about such things, and if the account really were empirical we would expect them to be able to write a plausible statement of method. From this performance (of writing a methods statement) we would again infer all manner of underlying competence.

But ChatGPT can give us such a statement too. In a perhaps unnecessary attempt to avoid certain “safety” measures, I prompted it to “imagine that the account is the result of participant observation by an ethnographer. Write a paragraph for the methods section in which you imagine how the data the account of Sarah’s sensemaking is based on.” After giving me an explicitly imaginary account of “an ethnographer”, I asked it simply to rewrite it in the first person as a straight statement of method.

As an ethnographer, I immersed myself in the project management context to conduct participant observation and gain insights into Sarah's sensemaking process. Over an extended period, I actively observed team meetings, carefully documenting the dynamics, non-verbal cues, and communication patterns. I took detailed field notes, capturing the atmosphere, interactions, and notable events. Additionally, I engaged in informal conversations with Sarah and other team members, both individually and in group settings, to delve into their experiences, frustrations, and suggestions. These conversations were audio-recorded to ensure accurate representation. To supplement my observations and interviews, I thoroughly reviewed project documentation, including meeting minutes, task assignments, and relevant correspondence. The data collected through participant observation, field notes, interviews, and document analysis were meticulously analyzed and synthesized to construct a comprehensive account of Sarah's sensemaking journey. Through my firsthand involvement and interpretation, I aimed to provide an authentic and nuanced portrayal of the project's context, Sarah's challenges, and the collaborative sensemaking process that unfolded.

I really wish we could still use the writing students do at home to gauge whether they have learned what we were trying to teach them. But examples like this are enough to completely undermine my faith in such performances as indications of actual competence. Going forward, I only want to look at writing from students that was produced off-line. I want to know what they are capable of without the assistance of AI.

* * *

PS. All the outputs in the above post were generated using ChatGPT model 3.5. I gave the long ethnographic passage to 4.0 and asked it to help me write a methods statement. Here’s its first attempt:

Based on the ethnographic description provided, here is a potential methods statement:

This ethnographic study adopts an interpretative, qualitative approach to understanding project management under crisis conditions. The research method includes direct observation and engagement with the research subject, Sarah, a project manager. The research subject was observed in her natural environment at her workplace to understand her behaviors, actions, and interactions in a real-life context.

Sarah's activities were meticulously documented as she navigated through a crisis caused by the sudden departure of a key team member. The observation involved recording her approach to problem-solving, including her reflective analysis of previous records, her communication with team members, her mental processes during decision-making, and her efforts towards group sensemaking and decision-making.

Primary data collection involved the naturalistic observation of Sarah's behaviors, conversations, and interactions, supported by the collection of project-related documents like meeting notes and records. Additionally, informal interviews were conducted with Sarah and her team members to gain further insight into their experiences, frustrations, perspectives, and potential solutions.

The analysis process was inductive and iterative, informed by grounded theory. This process helped to identify patterns, themes, and emergent properties related to team communication, role clarity, and collective sensemaking. These findings were then used to construct a narrative that detailed Sarah's sensemaking process during crisis management.

Sarah's experiences were triangulated with the insights shared by the other team members. This approach allowed for a richer, more nuanced understanding of the crisis situation and how the team navigated through it. The interpretive approach allowed for the examination of the shared sensemaking process, enabling the research to delve deeper into the team's collective resilience and problem-solving approach.

The outcome of this research is intended to provide insights into effective crisis management strategies, with a particular focus on the importance of collaborative sensemaking. It is hoped that these findings will contribute to the broader literature on project management and organizational behavior, as well as provide practical insights for those managing teams under crisis conditions.

I then asked it for a background description of Sarah’s organization.

Sarah's organization, InnoTech, is a leading mid-sized tech company located in San Francisco, California. With a workforce of approximately 500 employees, the company specializes in developing cutting-edge software solutions that address the critical needs of businesses across various sectors, including healthcare, finance, and e-commerce.

InnoTech has a reputation for fostering innovation and technological advancement. It's been in operation for more than a decade and has become well-regarded for its pioneering contributions to the tech industry, primarily through its suite of productivity-enhancing applications and data analytics platforms.

The organization prides itself on its agile work environment and flat hierarchical structure. Teams within InnoTech function as autonomous units, each overseeing different projects with specific goals aligned with the company's broader mission. This structure promotes a high degree of collaboration, enabling cross-functional teams to work seamlessly together.

Sarah's team, known as the Phoenix Project Team, consists of developers, UI/UX designers, quality assurance engineers, and product managers. Their role is to conceptualize, design, develop, and launch new software products aimed at enhancing business productivity.

The company's culture emphasizes continuous learning and improvement, fostering a climate of creativity and risk-taking. It invests significantly in its employees, offering them opportunities for professional growth and development. There's also a strong focus on maintaining a positive work-life balance, reflected in flexible working arrangements and comprehensive employee wellness programs.

However, despite its positive attributes, the organization isn't immune to challenges. As depicted in the ethnographic description, sudden staff departures and project disruptions can put immense pressure on teams, necessitating robust crisis management strategies. It's within this context that Sarah, as a project manager, navigates her role, working to ensure her team effectively overcomes obstacles and delivers on their project objectives.