In 2007, Scott Adams — creator of Dilbert — published a short blog post on writing. Naval Ravikant thought it was worth adding to his recommended reading list in the Almanack of Naval Ravikant.
There's one problem. Typepad, the blogging platform that hosted it, shut down permanently on September 30, 2025. The post disappeared with it.
I tracked it down through the Internet Archive. You can read the original here.
This post is my attempt to make it accessible — and to add something new.
An ongoing weekend project documenting the journey of uncovering hidden connections in corporate financial filings—the stumbles, the learnings, the 'aha!' moments, and everything in between. Started January 2025.
What is RiskChain?
The core idea is simple but ambitious: find hidden connections and risk trails that aren't immediately obvious when you're just reading through a 10-K filing.
It's hard to ignore the news about AI taking over. Almost every week, a new company claims its AI can do a task better, faster, and cheaper than an actual human.
Think about it: creating a logo, editing a picture, writing content, researching a topic, or even writing code. All of these used to take hours or even days, and now they can be done in minutes. Going from an idea to a finished product has never been faster. In some cases, AI tools are even outperforming humans. It's easy to see why so many jobs that exist today might not exist in just a few years.
Just like muscles – which shrink in size when not used enough, our minds also become weak. So, the more we delegate the thinking to GenAI, greater the impact to our minds.
In this article, I share an interesting proposal to address this challenge.
How about we use the poison itself to create the cure.
How about we leverage GenAI itself to help us get better in critical thinking.
Note: The article addresses to Software Engineers, but the ideas apply to knowledge workers in every domain.
I've spent considerable amount of time using GenAI past year at work. Also, having spent time with many power users, I begin to see an interesting trend.
Engineers are increasingly using GenAI to accomplish wide range of tasks, from advanced software engineering problems, to drafting a simple slack message.