Antonym: The End of Docs Edition
Code, complexity and consciousness
Dear Reader
Got some big thoughts cut with practical tools and tips that will blow your mind this week (at least they had that effect on me when I found them).
We are at a turning point in how we communicate complex ideas and data with one another. AI is enabling new forms of what we once called documents. Increasingly, structured, adaptable information - more akin to code than traditional docs, spreadsheets and slides - is becoming a practical necessity and far more accessible.
Make Code, Not Docs
I’m wondering: will "send code, not docs" catch on? Maybe, or perhaps we will just see new shapes emerge for sharing things.
At Brilliant Noise, we've started transforming some traditional slide decks into interactive applications. I suspect that this will go from sometimes to always, with traditional documents, spreadsheets and slides becoming optional extras.
Here’s an example of very quickly taking new knowledge and turning it into different types of visuals and apps with AI writing the code to make it exactly how you want it.
Yesterday, I was reading The Dealmaker, a business memoir by private equity legend, Guy Hands. About 100 pages in I’m thinking the book’s not for me. I’d been expecting to learn a lot about the PE industry and how it works, but so far I’ve learned a lot about how fabulously brilliant he was at investment banking and pulling off deals, but not insight of value to me.
On about page 114, however, he talks about the maths of private equity and it all becomes clear. Scales fall from my eyes. I see the PE model in all its innovative, rapacious glory.
Imagine I want to brief some other non-financial types on this insight, or include it in some training. The old way of doing this would be to write up some notes, maybe create a PowerPoint slide or three. You can do this faster by having ChatGPT or your model of choice write it up in simple steps. For example this is the summary for the private equity model:
1.a. Buying the Company. Find a promising company priced at a fair value. Example: Purchase price = £10 million, making £1 million a year profit (10% yield).
1.b. Using Borrowed Money. Pay mostly with borrowed money (loans), similar to taking a mortgage when buying a house. Advantage: Debt costs less than using your own cash, increasing your returns.
2. Improving Operations. Increase company profits by running it better. Example: Aim for annual 4% improvement in efficiency and profitability. Benefit: Company becomes more valuable each year.
3. Growing the Company through Mergers & Acquisitions Combine the company with another to increase its size and strength. Larger companies are usually seen as safer and valued higher. Benefit: Company value significantly increases.
4. Clarifying the Company’s Value. Make financial reports clear and simple. Clearer reports make buyers more confident and willing to pay more.
5. Using Technology and Data Analytics. Apply data-driven methods to find hidden value. Example: Identify ways to borrow cheaper or manage finances better. Benefit: More informed decisions, higher profitability.
6. Selling the Company. Sell the improved, larger, and clearly valuable company. Investors pay more for a stronger, more transparent, bigger business. Result: Your original investment (£10 million) grows substantially.
We want to create slides or a more visual way of seeing the process. The best options are to use something like the amazing Napkin for creating a diagram:
Or Brilliant Noise favourite Gamma.app which will make a nicely designed presentation (or web page or document) in seconds. Voila!:
You can even use your everyday ChatGPT, Claude etc to make you a diagram, which it will by writing code. They tend to be rougher for now, but will export in files that you can edit to make prettier. Here’s Claude’s attempt:
ChatGPT took a different approach. Again, not perfect – those icons are hideous – but it put the whole thing in my company’s brand style:
But then, why send it as a picture or text explanation? How about an interactive demo of how the different techniques Guy Hands talks about affect the final value of the investment? Well, just tell your AI to create that. Here’s the one we ended up with:
Much better. Now you can see how the process works and play with the numbers yourself, seeing the difference that different debt levels and time spent improving a company’s performance improves the result. Click on this image or this link to have a go yourself.
Work-arounds Make Systems Fragile
Our organisations are far more provisional and brittle than we like to think. They are – despite the precise organograms, data architectures, and grand systems diagrams of the business plan –held together at a practical level by all kinds of jerry-rigged bodge jobs and workarounds.
One of the reasons for this is the incredible lack of consistent training and use of common work tools, the most common being Microsoft Office. People learn by trial-and-error, by osmosis, by what gets the job-in-hand done. The reality is shocking.
Despite its ubiquity, only 48% of workers received formal Excel training as of 2022 (2022 Survey on Excel Training).
A 2024 survey of 14,000 job postings found that Microsoft Office is now the most in-demand tech skill (2024 Survey), yet few organisations invest in structured training.
The result: lots of files and data and processes that are make-do-and-mend patchworks rather than the seamless workflows the organisation imagines they have.
In Right Kind of Wrong, Amy Edmondson describes this habit of unsystematic getting by with tools as work-arounds.
When we analyzed the hospital nursing care as a system, we realized that work-arounds, despite being effective in the short term, actually made the system worse over time. You read that correctly. Reliance on work-arounds does not just fail to improve the system, it makes it worse.
The quick-fixes, and bodge-jobs of reporting and planning and communicating in an organisation make it brittle. Donella Meadows described how this erodes resilience and the ability to function of an organisation in Thinking in Systems.
I think of resilience as a plateau upon which the system can play, performing its normal functions in safety. A resilient system has a big plateau, a lot of space over which it can wander, with gentle, elastic walls that will bounce it back, if it comes near a dangerous edge. As a system loses its resilience, its plateau shrinks, and its protective walls become lower and more rigid, until the system is operating on a knife-edge, likely to fall off in one direction or another whenever it makes a move. Loss of resilience can come as a surprise, because the system usually is paying much more attention to its play than to its playing space. One day it does something it has done a hundred times before and crashes.
Using AI at an individual and team level reveals to everyone the systems they work in and their flaws.
That’s all for this week, folks…
Thank you so much for reading Antonym. Let me know what you thought or leave a like to say “yes, that was adequate or better”.
Antony