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Reshuffle: Who wins when AI restacks the knowledge economy
What happens when the “know-how” that once defined expertise migrates from humans to AI tools? How do organizations reorganize when machines take over not just tasks but entire workflows? And most importantly, how does this reshaping of knowledge work change the products we use and the industries that have evolved around their production?
In today’s economy, value is no longer driven by materials but by knowledge - design, R&D, and innovation power everything from mining to pharmaceuticals to consumer products. Now, with artificial intelligence, we have a range of technologies that don’t just support knowledge work - they perform it.
RESHUFFLE delivers a bold and incisive exploration of how AI is upending the knowledge economy, reshaping not just work but the very foundations of power and control. It unpacks the four key tensions driving this between workers and their software tools, the providers of these tools and the firms that buy them, the businesses consolidating power and the industries they disrupt, and between empowered individuals and entrenched incumbents.
Blending compelling examples, historical parallels, and bold insights, RESHUFFLE equips readers to navigate the many opportunities and challenges that AI introduces while reshaping the knowledge economy. This book is your guide to understanding who wins - and who gets left behind - when AI restacks the deck.
In today’s economy, value is no longer driven by materials but by knowledge - design, R&D, and innovation power everything from mining to pharmaceuticals to consumer products. Now, with artificial intelligence, we have a range of technologies that don’t just support knowledge work - they perform it.
RESHUFFLE delivers a bold and incisive exploration of how AI is upending the knowledge economy, reshaping not just work but the very foundations of power and control. It unpacks the four key tensions driving this between workers and their software tools, the providers of these tools and the firms that buy them, the businesses consolidating power and the industries they disrupt, and between empowered individuals and entrenched incumbents.
Blending compelling examples, historical parallels, and bold insights, RESHUFFLE equips readers to navigate the many opportunities and challenges that AI introduces while reshaping the knowledge economy. This book is your guide to understanding who wins - and who gets left behind - when AI restacks the deck.
460 pages, Paperback
Published July 26, 2025
254 people are currently reading
479 people want to read
About the author
Sangeet Paul Choudary
8 books84 followersSangeet Paul Choudary is a widely published researcher, industry keynote speaker and global CXO advisor on platform business models to high growth startups and Fortune 500 companies.
He is the co-chair of the MIT Platform Strategy Summit and an industry advisor to the Global Platform Data Project at Stanford University. He is an Entrepreneur-in-Residence at INSEAD Business School, an advisor at 500Startups, a Global Fellow at the Centre for Global Enterprise in New York and serves on the advisory board of CoFoundersLab, the world's largest community of startup founders.
Sangeet is also the author of Platform Revolution (W.W. Norton & Company, 2016), as well as a contributing author to Managing Startups (O'Reilly Media, 2013). He has been featured in Fast Company, Forbes, Harvard Business Review, MIT Technology Review, TechCrunch, Wall Street Journal, WIRED Magazine and other leading publications.
For all media-related, research-based advisory and speaker engagement services, contact him on @sanguit or http://platformthinkinglabs.com
He is the co-chair of the MIT Platform Strategy Summit and an industry advisor to the Global Platform Data Project at Stanford University. He is an Entrepreneur-in-Residence at INSEAD Business School, an advisor at 500Startups, a Global Fellow at the Centre for Global Enterprise in New York and serves on the advisory board of CoFoundersLab, the world's largest community of startup founders.
Sangeet is also the author of Platform Revolution (W.W. Norton & Company, 2016), as well as a contributing author to Managing Startups (O'Reilly Media, 2013). He has been featured in Fast Company, Forbes, Harvard Business Review, MIT Technology Review, TechCrunch, Wall Street Journal, WIRED Magazine and other leading publications.
For all media-related, research-based advisory and speaker engagement services, contact him on @sanguit or http://platformthinkinglabs.com
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Displaying 1 - 13 of 13 reviews
October 26, 2025
Reshuffle is a book I had been looking forward to reading ever since I started seeing Sangeet Paul Choudary's excerpts and related posts. And despite reading all those posts, the book had sufficient meat to make it an excellent read. One that offers great perspectives on dealing with the influx of AI in work - at an individual and business level.
I think I have a bias for the book because of a few reasons. One, it follows a clear systems thinking approach, and the logic and reasoning is robust. Two, it is a strategic and framework-driven exploration, which means it offers tools to think about this in one's own contexts. Three, it's not just theory. The book provides sufficient examples that can serve as starting points on how to think through this. That, as you'd notice is an elegant why-what-how approach.
I'll attempt a broad summary without 'spoiling' your reading of the book. Admittedly, this is difficult, because this book probably has the highest density of dog-ears in a while! Reshuffle is about
how generative AI and systems-level automation are not simply replacing tasks but remapping where value, power and expertise live inside organisations and markets/ecosystems. "AI changes the structure of the system in which it is introduced." It moves tacit knowledge out of individual minds/ 'tribal knowledge' into composable/ almost autodidactic (after initial onboarding and tutoring) tools and platforms, which forces businesses and professions to be reorganised from first principles rather than merely sped up through automation and efficiency. An excellent framework here is how AI achieves coordination without consensus - the architecture of coordination: representation, decision, execution, composition, governance (superb example of how the British controlled the provinces through this coordination).
The overall narrative is like a consultant making a layered case study (which I think his profession is). The first section - "AI & the system" - is about reframing the mental models we use to understand AI. AI isn’t simply substituting/automating tasks but re-modularising knowledge. Its superpower is coordination across fragmented systems involving actors with divergent incentives. This section explains how the 'knowledge economy' is built on a stack of activities (data, expertise, judgment, coordination) rather than simple task work, and shows how AI is modularising what used to be tacit, breaking up old unit-models of expertise, and thereby changing the anatomy of work and value creation. When the word processor arrived, 'typists didn't disappear, but the job of the typist did'. In essence, value is shifting from ownership of assets/knowledge to orchestration of flows and coordination, and thus restructuring power. Great examples here of Amazon (warehouse), legal firms, Shein, Walmart, through a task - organisation system - competitive ecosystems framework that showed the redistribution of value through (eco)system thinking.
The second section is "Work & Organizations", and it focuses on the strategic implications on individual roles, and the workflows and business architecture of organisations. For individuals, the future is less about racing to acquire skills - because an entire system is changing , and more about rebundling different modules and contexts to create leverage, value and relevance of a different kind (sommeliers). It makes a good point that though human-generated outputs might have higher intrinsic value (subjective, rooted in meaning), its economic value (what gets traded) and contextual value (value within the system of work) might be less because markets might reward 'sufficiency at scale'. Taxi drivers (knowledge based on experience) becoming commodity in the era of GPS. are an example. So the idea is to find new constraints. These could be based on scarcity (radio operators in ships vs modern communication infrastructure) , risk (anaesthesiologist making decisions based on patient response and taking on the risk) or coordination (movie producer). 'Don't follow the skill, follow the constraint'. This goes for organisations too, with the additional layers of how roles and teams need to be redesigned, and how governance must evolve. A good example is Ramp using AI to convert customer support team conversations into podcasts that people across departments could hear and thus reduced the coordination tax (meetings, reports) that it pays. Another example is the work Palantir's Foundry does. Whether individuals or organisations, it is about new business economics when AI can embed expertise into software. Systems over tools.
The final section is "Competitive Advantage", and it focuses on ecosystems and economies. The first two chapters are spent differentiating the scope and future of tools vs solutions. I understood/thought it was a little B2B digression, but they do have some excellent examples and frameworks. For instance, how TikTok used a constraint (lack of social graph) to create an advantage, inferring a behaviour graph from scratch. Now new creators didn't need to create an audience (a barrier to them joining), a 'good' video would become viral irrespective. Also, an interesting part on why the robotics industry hasn't really scaled (access, usable, reliable framework). And a framing of differentiating Work/Result/Outcome as a a Service. The next three chapters focus on how AI can be used by organisations to reorganise entire ecosystems, what this would mean for labour markets and society, and how winners are doing/will do differently. I found the idea of 'control without consensus' (dynamic linkages across components, humans and machines, illustrated with an example of Tractable vs CC in the insurance claims space) very intriguing and at a very broad level dovetailing into the blockchain philosophy. A good analogy I found here was 'what Ford's moving assembly line did for car production, AI powered systems are doing for knowledge workflows, coordinating activity around the user rather than forcing the user to coordinate activity'.
Overall the book is about how AI is reshaping systems, and how the restacking of knowledge work will redistribute power (winners vs. losers), alter career paths, require new skills (judgement, curiosity, integration) and create new structural bottlenecks (coordination, data access, platform control). In summation, value, power and work are being redesigned; and human skills need to shift toward orchestration and judgement.
The language is very accessible, and the key takeaways at the end of chapters is a nice touch. I had only a couple of thoughts on what could have been made better. One, an editor could have made it crisper (without repetitions) and provided a more elegant narrative flow (seamlessness and cohesion of concepts, as opposed to stacking what might seem like blog posts rather than chapters). And two, for a book like this, not having an index is criminal!
But those are minor things compared to the value of the book. Absolutely worth a read.
Notes & Quotes
1. AI is better understood as a practical utility that integrates into workflows and changes how decisions are made. By 'sensing' the environment, creating a working model, reasoning and acting based on this, and learning using patterns. (e.g. Google Maps, ChatGPT)
2. The example of how containers changed shipping. Predictability and reliability through coordination. Airbnb being similar, through reviews and a reputation system. Trust is practically a 'system'. Stripe, Tesla are other examples
3. Three factors in making algorithmic coordination important. Ability to collect and use data to manage economic activity (software sensors over physical presence). Growing adoption of smartphones. (production and consumption timescale difference between Nike and Shein), rise of cloud based services to access specialised operational capabilities instead of building it themselves (Uber).
4. AI works at three different levels - first order effects of automation, cascading effect of coordination, accelerated effects of learning, where AI shapes the system's behaviour and this further trains the AI
5. Mr.Beast assembled a business from pre-made building blocks. He had an online audience and started a burger chain with no expertise using 'blocks' of getting orders (demand generation), cooking the food (Ops), and delivering it (logistics). The constraint because of which it failed - quality control and lack of someone who took ownership of the entire process.
6. Historically expertise and specialised knowledge were tightly bundled with human labour. Organisations paid a premium for this. Now AI had unbundled it. It becomes rentable, recombinable and scalable.
7. "Tools amplify performance but solutions absorb risk." A good version of the latter has the ability to "deliver predictable performance in unpredictable environments."
8. "Control is earned by solving coordination problems, not merely by owning interfaces."
9. Dominance does not guarantee control, but dependence does.
10 AI eliminates the need for shared standards by enabling the interpretation of diverse inputs into a unified understanding.
I think I have a bias for the book because of a few reasons. One, it follows a clear systems thinking approach, and the logic and reasoning is robust. Two, it is a strategic and framework-driven exploration, which means it offers tools to think about this in one's own contexts. Three, it's not just theory. The book provides sufficient examples that can serve as starting points on how to think through this. That, as you'd notice is an elegant why-what-how approach.
I'll attempt a broad summary without 'spoiling' your reading of the book. Admittedly, this is difficult, because this book probably has the highest density of dog-ears in a while! Reshuffle is about
how generative AI and systems-level automation are not simply replacing tasks but remapping where value, power and expertise live inside organisations and markets/ecosystems. "AI changes the structure of the system in which it is introduced." It moves tacit knowledge out of individual minds/ 'tribal knowledge' into composable/ almost autodidactic (after initial onboarding and tutoring) tools and platforms, which forces businesses and professions to be reorganised from first principles rather than merely sped up through automation and efficiency. An excellent framework here is how AI achieves coordination without consensus - the architecture of coordination: representation, decision, execution, composition, governance (superb example of how the British controlled the provinces through this coordination).
The overall narrative is like a consultant making a layered case study (which I think his profession is). The first section - "AI & the system" - is about reframing the mental models we use to understand AI. AI isn’t simply substituting/automating tasks but re-modularising knowledge. Its superpower is coordination across fragmented systems involving actors with divergent incentives. This section explains how the 'knowledge economy' is built on a stack of activities (data, expertise, judgment, coordination) rather than simple task work, and shows how AI is modularising what used to be tacit, breaking up old unit-models of expertise, and thereby changing the anatomy of work and value creation. When the word processor arrived, 'typists didn't disappear, but the job of the typist did'. In essence, value is shifting from ownership of assets/knowledge to orchestration of flows and coordination, and thus restructuring power. Great examples here of Amazon (warehouse), legal firms, Shein, Walmart, through a task - organisation system - competitive ecosystems framework that showed the redistribution of value through (eco)system thinking.
The second section is "Work & Organizations", and it focuses on the strategic implications on individual roles, and the workflows and business architecture of organisations. For individuals, the future is less about racing to acquire skills - because an entire system is changing , and more about rebundling different modules and contexts to create leverage, value and relevance of a different kind (sommeliers). It makes a good point that though human-generated outputs might have higher intrinsic value (subjective, rooted in meaning), its economic value (what gets traded) and contextual value (value within the system of work) might be less because markets might reward 'sufficiency at scale'. Taxi drivers (knowledge based on experience) becoming commodity in the era of GPS. are an example. So the idea is to find new constraints. These could be based on scarcity (radio operators in ships vs modern communication infrastructure) , risk (anaesthesiologist making decisions based on patient response and taking on the risk) or coordination (movie producer). 'Don't follow the skill, follow the constraint'. This goes for organisations too, with the additional layers of how roles and teams need to be redesigned, and how governance must evolve. A good example is Ramp using AI to convert customer support team conversations into podcasts that people across departments could hear and thus reduced the coordination tax (meetings, reports) that it pays. Another example is the work Palantir's Foundry does. Whether individuals or organisations, it is about new business economics when AI can embed expertise into software. Systems over tools.
The final section is "Competitive Advantage", and it focuses on ecosystems and economies. The first two chapters are spent differentiating the scope and future of tools vs solutions. I understood/thought it was a little B2B digression, but they do have some excellent examples and frameworks. For instance, how TikTok used a constraint (lack of social graph) to create an advantage, inferring a behaviour graph from scratch. Now new creators didn't need to create an audience (a barrier to them joining), a 'good' video would become viral irrespective. Also, an interesting part on why the robotics industry hasn't really scaled (access, usable, reliable framework). And a framing of differentiating Work/Result/Outcome as a a Service. The next three chapters focus on how AI can be used by organisations to reorganise entire ecosystems, what this would mean for labour markets and society, and how winners are doing/will do differently. I found the idea of 'control without consensus' (dynamic linkages across components, humans and machines, illustrated with an example of Tractable vs CC in the insurance claims space) very intriguing and at a very broad level dovetailing into the blockchain philosophy. A good analogy I found here was 'what Ford's moving assembly line did for car production, AI powered systems are doing for knowledge workflows, coordinating activity around the user rather than forcing the user to coordinate activity'.
Overall the book is about how AI is reshaping systems, and how the restacking of knowledge work will redistribute power (winners vs. losers), alter career paths, require new skills (judgement, curiosity, integration) and create new structural bottlenecks (coordination, data access, platform control). In summation, value, power and work are being redesigned; and human skills need to shift toward orchestration and judgement.
The language is very accessible, and the key takeaways at the end of chapters is a nice touch. I had only a couple of thoughts on what could have been made better. One, an editor could have made it crisper (without repetitions) and provided a more elegant narrative flow (seamlessness and cohesion of concepts, as opposed to stacking what might seem like blog posts rather than chapters). And two, for a book like this, not having an index is criminal!
But those are minor things compared to the value of the book. Absolutely worth a read.
Notes & Quotes
1. AI is better understood as a practical utility that integrates into workflows and changes how decisions are made. By 'sensing' the environment, creating a working model, reasoning and acting based on this, and learning using patterns. (e.g. Google Maps, ChatGPT)
2. The example of how containers changed shipping. Predictability and reliability through coordination. Airbnb being similar, through reviews and a reputation system. Trust is practically a 'system'. Stripe, Tesla are other examples
3. Three factors in making algorithmic coordination important. Ability to collect and use data to manage economic activity (software sensors over physical presence). Growing adoption of smartphones. (production and consumption timescale difference between Nike and Shein), rise of cloud based services to access specialised operational capabilities instead of building it themselves (Uber).
4. AI works at three different levels - first order effects of automation, cascading effect of coordination, accelerated effects of learning, where AI shapes the system's behaviour and this further trains the AI
5. Mr.Beast assembled a business from pre-made building blocks. He had an online audience and started a burger chain with no expertise using 'blocks' of getting orders (demand generation), cooking the food (Ops), and delivering it (logistics). The constraint because of which it failed - quality control and lack of someone who took ownership of the entire process.
6. Historically expertise and specialised knowledge were tightly bundled with human labour. Organisations paid a premium for this. Now AI had unbundled it. It becomes rentable, recombinable and scalable.
7. "Tools amplify performance but solutions absorb risk." A good version of the latter has the ability to "deliver predictable performance in unpredictable environments."
8. "Control is earned by solving coordination problems, not merely by owning interfaces."
9. Dominance does not guarantee control, but dependence does.
10 AI eliminates the need for shared standards by enabling the interpretation of diverse inputs into a unified understanding.
September 15, 2025
OK contents but not well written, typical of this kind of books.
Can essentially be boiled down to
1. Rebundling
2. Try to identify constraints, not tasks
3. AI is most impactful on not automation, but coordination
Can essentially be boiled down to
1. Rebundling
2. Try to identify constraints, not tasks
3. AI is most impactful on not automation, but coordination
August 20, 2025
The best AI Playbook I have read so far
If you need to understand AI and its organizational transformation, look no farther. This book surfaces the non-obvious & challenges you to look deeper than the conventional surface level AI Analyses you might have come across.
If you need to understand AI and its organizational transformation, look no farther. This book surfaces the non-obvious & challenges you to look deeper than the conventional surface level AI Analyses you might have come across.
August 20, 2025
insightful and helpful
As we all struggle to make sense of the changes AI is likely to bring to our companies and our jobs, this book is illuminating. I found it really clear and helpful in setting out a framework for considering the opportunities and threats from AI
As we all struggle to make sense of the changes AI is likely to bring to our companies and our jobs, this book is illuminating. I found it really clear and helpful in setting out a framework for considering the opportunities and threats from AI
August 7, 2025
I have always been impressed with Sangeet Paul Choudary's observations and posts on LinkedIn. So much, so I pre-ordered this book and read it end to end. It's an unputdownable book! Everybody talks about AI, ML, Generative AI and how it's going to change everybody's lives but no one zooms out and looks at the bigger picture and tells us what to expect! If you are individual worried about your job or a company worrying about your strategy, this is a must read book! Model makers are racing towards Artificial General Intelligence (AGI). They may or may not succeed in that "Life is what happens when you're making other plans". Models are so powerful today without fully replicating human thought processes and intelligence that things are changing beneath your feet TODAY! Organizations are not waiting for AGI to use today's technology. Understanding how someone's work is being unbundled and then again rebundled with changes in technology is key to predicting what skills are passe and what might be needed in the future. The same applies to organizations also - AI levels the playing field for competitors, taking away the secret sauces that organizations may have. Sangeet makes the argument that coordination across functions in the same company or across organizations is where the competitive advantage may lie. The only development that Sangeet predicts but may happen more slowly than he thinks, may be the speed at which AI models learn an organization's institutional memory, experiences, data and competitive advantages and make it available to others. Organizations are very wary of making their data available to model makers, even as they use them. They are making sure that those trained models are not available to anyone but themselves. Smaller, distilled models are the future - so much so, even OpenAI released some of their distilled models as open source just a few days ago! Great read and I highly recommend it!
August 21, 2025
Reshuffle is a sharp, thought-provoking examination of how artificial intelligence is not simply adding efficiencies to the current system but completely restacking the foundations of the knowledge economy. Sangeet Paul Choudary has a gift for connecting history, strategy, and technology, showing why businesses that prepare for AI with old assumptions are building Maginot Lines, defenses that look strong but are destined to fail. His framework for the “new stack” offers both clarity and urgency, making this a book that leaders, policymakers, and entrepreneurs cannot afford to ignore.
What makes the book stand out is its balance between deep analysis and accessible storytelling. Choudary goes beyond the usual hype to reveal who the winners and losers will be in this economic transformation, and what strategic blind spots organizations must overcome if they want to stay relevant. It’s not just another book about AI, it’s a roadmap for navigating a fundamental power shift. Highly recommended for anyone who wants to understand not only what AI is doing, but how it is restructuring the very rules of value creation.
What makes the book stand out is its balance between deep analysis and accessible storytelling. Choudary goes beyond the usual hype to reveal who the winners and losers will be in this economic transformation, and what strategic blind spots organizations must overcome if they want to stay relevant. It’s not just another book about AI, it’s a roadmap for navigating a fundamental power shift. Highly recommended for anyone who wants to understand not only what AI is doing, but how it is restructuring the very rules of value creation.
September 14, 2025
Fantastic Read
Unlike other books on AI which get lost in tools, jargons, Sangeet takes an approach of workflow and explains how AI disrupts the workflows by unbundling, rebundling of services, how coordination happens without consensus. There are handful of ideas explained, reinforced, given examples and repeated again and again in a new context - I found this approach refreshing instead of hurrying through ideas with no stickiness.
Trying to learn AI to be relevant( as the only strategy) - very soon AI will learn your current AI skills and make you redudant . Crucial thing is to find that new value, that risk you can absorb, the trust you can introduce, the gap you can surface - and it need not be a tech skill ( by itself) . The curve would definetly swift slowly once the AI bubble gets its cracks,
This book definetly needs a) A two time read b) Internalisation by doing some exercises after reading each chapter, specific to your context * c) Reflect again and again
Unlike other books on AI which get lost in tools, jargons, Sangeet takes an approach of workflow and explains how AI disrupts the workflows by unbundling, rebundling of services, how coordination happens without consensus. There are handful of ideas explained, reinforced, given examples and repeated again and again in a new context - I found this approach refreshing instead of hurrying through ideas with no stickiness.
Trying to learn AI to be relevant( as the only strategy) - very soon AI will learn your current AI skills and make you redudant . Crucial thing is to find that new value, that risk you can absorb, the trust you can introduce, the gap you can surface - and it need not be a tech skill ( by itself) . The curve would definetly swift slowly once the AI bubble gets its cracks,
This book definetly needs a) A two time read b) Internalisation by doing some exercises after reading each chapter, specific to your context * c) Reflect again and again
November 13, 2025
Sangeet offers a humbling view on how deeply AI will impact the way we work, and how businesses/organizations are structured. However, it's not a dark and deflating read. It offers multiple ways and frameworks to make sense of the disruption and the opportunities it creates for the knowledge worker.
The book starts with a story from Singapore in COVID days and weaves through multiple industries and examples where the work was automated, optimized, and re-organized. Looking back, you can see patterns and anti-patterns and Sangeet - because he actively consults on the topic - offers a deep view into how businesses need to prepare themselves.
The book does feel repetitive in portions, but that it helps close the loop or help reinforce key concepts that are important to remember.
It is NOT a technical read, and pretty much anyone can pick it up and benefit from a new way to learn how to re-imagine their place the AI-infused world.
The book starts with a story from Singapore in COVID days and weaves through multiple industries and examples where the work was automated, optimized, and re-organized. Looking back, you can see patterns and anti-patterns and Sangeet - because he actively consults on the topic - offers a deep view into how businesses need to prepare themselves.
The book does feel repetitive in portions, but that it helps close the loop or help reinforce key concepts that are important to remember.
It is NOT a technical read, and pretty much anyone can pick it up and benefit from a new way to learn how to re-imagine their place the AI-infused world.
December 11, 2025
Perhaps the best take on AI I’ve read so far. It can be a bit long-winded, but the insights are solid. These two quotes perfectly sum up the core argument:
“The real impact of AI comes not from how it performs a task, but from how it restructures the entire system around that task.”
“When AI enters a system, it alters the economic logic of that system. It changes how value is created and who gets to capture it.”
“The real impact of AI comes not from how it performs a task, but from how it restructures the entire system around that task.”
“When AI enters a system, it alters the economic logic of that system. It changes how value is created and who gets to capture it.”
November 8, 2025
Reshuffle
This book was quite interesting.. it provides a lot of insight into how AI should be used in most situations. I suspect that it won’t be though, people won’t take the time to rethink the system that it will be deployed in. That will make it less effective.
This book was quite interesting.. it provides a lot of insight into how AI should be used in most situations. I suspect that it won’t be though, people won’t take the time to rethink the system that it will be deployed in. That will make it less effective.
December 5, 2025
Articulates powerfully why the differentiating role humans will play when using AI will be in coordination and in spécialisation. IT allows decoupling data from its activities into separate data assets. AI enables instantaneous use and coordination of that data.
November 17, 2025
Best book on AI's impact to economy and strategy I have read so far.
December 21, 2025
Thought-provoking content.
Would benefit from editing: somewhat repetitive and needs better, simpler structure.
Would benefit from editing: somewhat repetitive and needs better, simpler structure.
Displaying 1 - 13 of 13 reviews