How to keep up with AI (when you’re already overwhelmed)

Let’s quickly summarize what’s happening right now:

• Generative AI is improving in accuracy and ability. Many of those building LLMs expect this to continue.
• VC money is pouring into AI, and costs to build on AI systems are decreasing. This is resulting in the rapid scaling of existing AI companies and the sprouting of new startups.
• Individuals and companies haven't even fully realized AI's existing capabilities yet.
• People and organizations are experimenting with and studying this technology, and sharing what they’re learning.  

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When we consider all these factors, it’s no wonder that we’re seeing an avalanche of AI advances — from new tools and enhanced capabilities to better documentation and novel applications.

Here's the irony: AI exists to help us work smarter and faster, yet staying informed about AI has become its own time-consuming job.

And with a wealth of information and intelligence available on-demand and for free, the real challenge isn't access to information — it's managing it effectively.‍‍

‍So what do we do? ‍

Well, a few things:

• In many ways, we have to return to the fundamentals: attention, time management, good judgment, and systems thinking. It is true in life and in business that most things don't matter. While the competition zigs and zags to every shiny new thing, disciplined focus is your competitive advantage.
• We must view work through a new lens: That change is something to be expected, not resisted. That change is not something we *do* at regular intervals — monthly, quarterly, yearly — but something we *are doing*, continuously and constantly.

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Once we embrace this mindset, we must adopt behaviors, habits, systems, and processes that support it and operationalize it.

Here's one framework to help you do so:  

1. Define
2. Focus
3. Isolate
4. Automate
5. Iterate

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Let’s tackle the problem of keeping up with AI, and apply this framework to AI news monitoring.

1. Define: Clarify your purpose.  

Why are you learning about AI? Be specific.

You’re likely in business to make more money — ideally, without overworking yourself. So consider that, and get specific. Really specific. ‍

I’m learning about AI:

• To understand AI applications that will make me a more successful [role] or help me achieve [goal].
• To stay ahead in [industry] to serve clients better and more profitably.
• To identify critical developments (new regulations, breakthroughs, leading tools) that could significantly impact my business or market.

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Great, you've defined your "AI Whys." Now, set your standards: What is ‘good’? More importantly, what will be ‘good enough’?

You could spend all day seeking out more experts and getting new perspectives on AI. Instead, what criteria will you use to reduce the noise?

My AI sources must meet all of the following criteria:

• Credibility: Demonstrate real-world experience and results applying AI, or affiliation with a reputable news or research institution.
• Relevance: Consider big-picture ideas and connect them to my work in a way that feels practical and achievable.
• Insight: Offer a balanced, nuanced (hype-free) perspective on AI, and add value beyond reporting.
• Originality: Provide a unique perspective or point of view on AI that I’m not getting from my other sources.  

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Keep your standards high and your list small: Make your sources work for you. Your goal isn’t to follow everything, but to curate the best and most helpful sources that can filter out distractions and do some of the thinking for you.

2. Focus: Build your system.  

With your goals and standards defined, it's time to create a practical system that puts them into action. This is where we transform your criteria into concrete filters and boundaries.‍

Create your information filters based on your standards:

• Choose 3-5 trusted sources (e.g., blogs, newsletters, industry leaders) that meet your criteria.
• Focus on specific domains (e.g., generative AI, AI ethics, business use cases) that align with your goals.
• Prioritize actionable news (e.g., tools you can immediately apply or advancements that impact strategy).

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Set clear boundaries to manage information flow:

• Information boundaries. Subscribe to curated AI newsletters or summary services (e.g., This Week in AI, The AI Show). Avoid diving into rabbit holes — stop consuming once a specific purpose is fulfilled.
• Time boundaries. Allocate dedicated time and commit to how you'll use that time. For example, "I will set aside 1-2 hours on Thursdays to consume AI content. During this time, I will listen to a podcast, skim headlines and new posts from my trusted sources, and read articles that are aligned with my AI Whys. If any news is actionable, I'll add the link and any next actions to my project management system."

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The amount of time you dedicate should be proportional to the size of your goals and the value of applying AI to them. (See the AI Alignment Matrix for more help.)

3. Isolate: Break down your process.

Now that you have your system in place, break it down into distinct, manageable components. This modular approach makes it easier to optimize each part of your workflow.

When applied to AI news monitoring, this includes:

• Curating: Gathering relevant news.
• Consuming: Reading or watching the content.
• Processing: Determining relevance to your work.
• Analyzing: Identifying actionable insights.
• Applying: Taking action or archiving for future use.

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Document the workflows for each to streamline and make them repeatable.

4. Automate: Tools for each step.

With your workflow broken down into clear components, you can now identify the right tools and systems to optimize each step. Here are some ideas to get you started:

5. Iterate: Commit, evaluate, improve.

The hardest part of any system isn't building it — it's sticking with it long enough to evaluate and improve it. Without disciplined iteration, even the best-designed system will fail.

Two common pitfalls when managing systems:

1. Abandoning systems too quickly when you discover new tools or methods.
2. Never revisiting your system because you get caught up in the day-to-day.

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To avoid these traps, commit to:

• Using your system consistently for a set period (e.g., 30 days) before making major changes.
• Scheduling non-negotiable review sessions to evaluate and adjust.

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Here's a simple but effective iteration framework:

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Remember: The goal isn't perfection, but steady improvement. Each iteration should make your system slightly better at its ultimate goal: filtering signal from noise and connecting insights to action.‍

Measure your success not by how many articles you read or tools you try, but by how often your AI monitoring leads to meaningful improvements in your work and results.

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