Thriving in the Weird Times: Preparing for the 100X Economy
Epistemic status: Confident in the general concept, but not in the specific details.
The world is changing fast. As soon as 2026, we may experience an exponential increase in personal productivity, intelligence, and overall capacity to influence the world, powered by new AI tools. To remain relevant in this new era, individuals must embrace these tools.
In this emerging economy, certain factors will determine one’s ability to excel:
Easily transmitted and quickly acquired factors, such as access to public AI tools like ChatGPT, AutoGPT, and new AI assistants, as well as novel productivity workflows and strategies. Since the disparity in access to these resources among individuals will be minimal, this post will not focus on them.
Resources that are difficult to transmit and slow to acquire, which will be the key differentiators among people in this rapidly evolving technological landscape. Examples include personal datasets, trained mental habits, and the ability to swiftly adapt to new AI tools and workflows. Gaining these resources might take months or even years and cannot be easily condensed into a brief period. For instance, fully realizing the productivity benefits of new AI tools like GitHub Copilot requires individuals to deeply adapt their coding practices.
To succeed in this environment, it is vital to identify and begin acquiring these slow-to-acquire resources now to gain a competitive advantage. It is preferable to possess unused resources than to encounter insurmountable bottlenecks in the future. Here are some essential resources for this new era:
Mental habits: Learn to effectively use new AI tools, verbalize thoughts and ideas, and manage tight feedback loops with AI. Cultivating a habit of continuous learning and adaptation to new technologies is crucial. Becoming a skilled cyborg will be necessary to harness future AI creativity.
Personal datasets: Assembling and curating personal datasets for use with personal assistants or AI model training could become individuals’ most valuable digital assets in the new economy. Start building these datasets now to ensure you have the necessary information for future AI tools. One example is a friend who has recorded everything on his screen for the past two years, which could be leveraged by future AI assistants.
Classic capital: Money will still matter. Access to financial resources allows for flexibility and investment opportunities in new tools, training, and staying ahead of competitors. If the economy begins growing rapidly, having significant initial capital is the best way to benefit from this growth. As AI tools advance and become more expensive, subscribing to them will be essential for boosting productivity. The cost of these tools could surpass $1000 per month (recall that GPT4-32k is $1 per call).
To obtain these resources, prioritize and focus on the ones most valuable right now to create compounding returns, and those that will take the longest to acquire. Examples of wise investments at the moment include:
Regularly selecting and integrating new tools into your workflow
Training in prompt engineering techniques to enhance your intuitions on language models
In conclusion, to thrive in the 100X economy and remain relevant amidst rapidly advancing technology, it is crucial to adopt new AI tools and begin acquiring slow-to-acquire resources now. Identifying and prioritizing these resources, such as mental habits and personal datasets, can give individuals a competitive edge and position them for success in the weird times ahead.
Do you think there are important points missing in preparing for this wild future?
2026 mainly reflects the fact that we have short timelines. This market could be relevant to our prediction of short term economic change :
A further question to explore is how to filter the ever expanding list of new tools and workflows. I hope LessWrong can stay a place where high quality productivity information is filtered and curated.
Another possiblitity is that assistants will be good at modelling their user from little interaction, so the large initial dataset will be less useful.
Types of data which could be valuable could be notes database, unstructured voice and screen recordings, measurements à la Quantified self.
If Roodman’s model of economic growth holds, prepare for serious gains.