Get Your weekly dose of insights

Join my newsletter, “3 Things I Learned Last Week”
for your weekly dose of insights.

Stay up-to-date with the latest trends, discoveries, and ideas that can help you grow both personally and professionally, as I share the top three things I learned from my explorations across a variety of media.

Subscribe now and join the journey of continuous learning and discovery.

How to Use AI to Quickly Digest Long-Form Content Like a Pro

We live in an age of information overload.

There are seemingly endless supply of content coming at us from all directions.

Trying to take in all the content out there can be really tough. It’s like trying to drink from a fire hydrant – way too much, way too fast! And let’s be real, it’s about as doable as trying to read every book in a huge library all at once.

Even though we’re often eager to soak up as much information as we can, it’s just not possible to read everything! With our busy schedules, finding time to get through lengthy articles, books, or podcasts can be a real tough cookie.

That’s where a summary of all that content come in handy.

Here’s why:

  • They help you get the main idea fast.
  • They make learning quick and save your time.
  • They’re useful when you’re short on time or need to decide whether the content is worth consuming.

In essence, summaries streamline our consumption of information, making it more efficient and effective.

.

.

.

How AI Can Help Us in Summarizing Long Form Content

In recent years, AI has made some seriously impressive strides.

And guess what? It turns out AI can be a total game-changer when it comes to summarizing long-form content!

But it hasn’t always been smooth sailing.

When I first started using AI to summarize long-form content, I began with models like GPT-3.5 and the early release of GPT-4. Back then, the experience was quite challenging.

These older models had limited context windows, meaning they could only handle small chunks of content at a time. This often resulted in skipped or ignored sections, leaving me with a fragmented understanding of the material, much like trying to piece together a puzzle with half the pieces missing.

The summaries were often superficial, missing the depth needed for complex topics.

Over time, I noticed another significant issue: maintaining coherence.

These early models struggled with short-term memory, making it difficult for them to retain information over long passages. This led to summaries that were incoherent or disjointed, with no smooth flow. Additionally, when faced with lengthy content, these models couldn’t prioritize essential information effectively, resulting in summaries that missed the mark.

Thankfully, things have come a long way with the latest AI models….

Advancements with New LLM Models

Using newer versions like Claude 3 Opus, Gemini 1.5 Pro, and GPT-4o has been a night and day difference.

  1. Larger Context Windows:
    .
    • Enhanced Processing Capabilities: These newer models have much larger context windows. They can process and understand entire documents without losing context, which is a huge relief.
      .
    • Comprehensive Summarization: Because they can look at the whole content at once, the summaries they produce are more comprehensive and accurate. No more missing pieces!
      .
  2. Improved Recall Capabilities:
    .
    • Memory Integration: Modern models have much better memory integration. They can recall previously processed information more effectively, keeping track of key points throughout the summarization process.
      .
    • Context Retention: This improved memory means that important themes and details are retained, leading to coherent and thorough summaries.
      .
  3. Depth and Detail in Summarization:
    .
    • In-Depth Analysis: These advanced models can perform deeper analysis, capturing intricate details and nuances. They dive deep into the content instead of just skimming the surface.
      .
    • Contextual Understanding: Larger context windows help these models grasp the broader context of the content, ensuring that summaries are not just a collection of isolated points but a coherent narrative that makes sense.

These new LLM models make it easier than ever to stay informed, save time, and make smarter decisions about what to read or watch.

Now that you’ve got a good idea of how AI has evolved and improved in summarizing long-form content, let’s get down to the nitty-gritty. After all, it’s not just about having a fancy AI models, but knowing how to use it effectively.

And the key to that? Crafting a good summarizing prompt.

Think of it as instructing a new intern.

You wouldn’t just throw them into the deep end without clear instructions, right? Same goes for AI. It’s all about giving it the right guidance to get the job done. Ready to learn how to craft the perfect summarizing prompt?

Let’s get started!

.

.

.

What Makes a Good Summarizing Prompt?

Picture this: you’ve found a lengthy article that you want to summarize using AI.

You excitedly copy the text, paste it into your AI tool, and type out a quick prompt: “Please summarize the content above.” You hit enter, eager to see the magic happen.

But the result? It’s underwhelming, to say the least.

Here’s why:

  1. Surface-Level Summaries:
    .
    • Such prompts tend to produce summaries that only scratch the surface, missing deeper insights.
    • Key examples, strategies, and important details are often omitted.
      .
  2. Lack of Depth:
    .
    • Without specific instructions, the AI might not delve into the sub-points and nuances, leading to a shallow summary.
    • The summary might fail to capture the full context and intricacies of the content.

This is the problem with generic summarizing prompts.

They don’t provide the AI with any guidance on what aspects to focus on, how much detail to include, or how to structure the summary.

As a result, the AI does its best, but the output often misses the mark.

To get the best out of AI for summarizing stuff, we can’t just throw any old instructions at it.

We’ve gotta give it clear, detailed directions, kinda like how you’d explain a game to a friend. This helps the AI zero in on the important stuff, include all the juicy details, and arrange everything in a way that makes sense.

Doing this, we can use AI to create great summaries easily.

Consider the following prompt:

### Instructions for Crafting a Detailed Summary:

1. **Objective**:
   Understand that the purpose of this summary is to extract the essential insights, strategies, examples, tactics, and tips from the content. The reader should gain key knowledge from your summary without having to read the entire content line by line.

2. **Length**:
   While brevity is valued, it should not come at the expense of key information. It's better to have a longer, comprehensive summary than a brief one that misses out on crucial insights.

3. **Detailing Topics**:
   - When summarizing a section, delve beyond just the headline. Dive into the sub-points and nuances.
   - If specific examples are provided to illustrate a point, include those examples.
   - If a particular strategy or tactic is mentioned, describe it briefly in your summary.

4. **Incorporate Direct Quotes**:
   If there's a particularly impactful or insightful quote from the content, include it verbatim, ensuring you attribute it to the speaker or author.

5. **Use Bullet Points for Clarity**:
   - Bullet points make content easier to scan and digest.
   - For instance, if multiple strategies are discussed under a section, list each strategy as a separate bullet point with a brief description or example.

6. **Avoid Generalizations**:
   Avoid phrases like "Various strategies are discussed." Instead, specify what those strategies are: "The content discusses strategies such as A, B, and C, explaining that..."

7. **Conclude with Takeaways**:
   At the end of your summary, include a "Key Takeaways" section. This should be a bullet-pointed list that captures the core lessons, strategies, and insights from the content.

This prompt is my secret sauce.

It guides the AI to:

  • Set Goals: Tell the AI exactly what we want – to pull out the most important bits and strategies.
  • Dig Deep: Ask the AI to go beyond the main points and look at the little details and finer points.
  • Use Direct Quotes: Spice things up by adding in powerful quotes straight from the source.
  • Keep it Organized: Use bullet points to make everything clear and easy to read.
  • Stay Specific: Make sure the AI doesn’t just make broad statements, but gives us the specific details.
  • Recap Quickly: Wrap things up at the end with the key lessons for a quick and easy reference.

With a prompt like this, the AI has a clear roadmap to follow.

The resulting summary is detailed, insightful, and captures the core of the original content. It’s a summary that actually saves you time and provides value.

.

.

.

Comparing GPT-4o, Gemini 1.5 Pro, and Claude 3 on Summarizing Long-Form Content

Imagine this: you’ve found a gem of a podcast episode, but it’s way too long.

Tim Ferriss’s podcast episodes are like buried treasures full of insights. The problem? They’re longer than your usual commute. That’s where AI summarizers can help.

In a test, we had three leading AI models summarize an episode.

Seth Godin’s episode on the Tim Ferriss Show was our guinea pig.

It’s a great episode on How to Say “No,” Market Like a Professional, and Win at Life. We tested GPT-4o, Gemini 1.5 Pro, and Claude 3, using the same detailed prompt.

And guess what? The results were fascinating.

GPT-4o: Detailed and Organized

First, we tell GPT-4o that its role by providing a detailed prompt for summarizing Seth Godin’s podcast episode, including objectives and key instructions.
Here we feed GPT-4o with the podcast transcript
Here’s GPT-4o’s summary of Seth Godin’s podcast on the Tim Ferriss Show, highlighting key insights on habits, routines, and effective marketing strategies.

GPT-4o delivered a killer summary of Seth Godin’s podcast episode.

It started off strong with a clear introduction, then dove into the meaty topics. It tackled things like overcoming overwhelm, project management, and the difference between long work and hard work.

The real highlight was GPT-4o’s knack for detail. It gave a great explanation of Seth’s thoughts on pricing and scarcity, using relatable examples like Supreme and Franklin Barbecue. It didn’t stop at the surface, it went deep into the content, giving us a clear understanding of the topics.

At the end, GPT-4o wrapped it all up with a tidy list of key takeaways. This made it super easy to get the core lessons without having to listen to the whole podcast.

In short, GPT-4o nailed the summary game.

Gemini 1.5 Pro: Insightful and Engaging

Here, we provide a detailed prompt to Gemini 1.5 Pro via the Gemini API playground for summarizing Seth Godin’s podcast episode
Gemini 1.5 Pro’s engaging summary of Seth Godin’s podcast on the Tim Ferriss Show, highlighting key insights on managing overwhelm and choosing work.

Gemini 1.5 Pro turns summarizing into storytelling.

This model kicks things up a notch by delivering a comprehensive summary that reads like a captivating narrative. It sets the tone right from the start, presenting the discussion as a masterclass in modern work and marketing, drawing the reader in. The summary is neatly divided into distinct sections, each honing in on a crucial theme – from overcoming overwhelm to the art of saying “no” and identifying your niche audience. What really sets it apart are the catchy subheadings like “The Lizard Brain’s Influence” and “The Three-Sentence Marketing Promise,” that make the summary not just informative but also enjoyable to read.

To top it off, Gemini 1.5 Pro serves up practical templates like Seth’s three-sentence marketing promise, offering readers not just insights but actionable takeaways.

In short, Gemini 1.5 Pro doesn’t just summarize, it tells a story.

Claude 3: Concise yet Comprehensive

An example of a detailed prompt given to Claude 3 for summarizing Seth Godin’s podcast episode on the Tim Ferriss Show.
Claude 3’s summary of Seth Godin’s podcast episode on the Tim Ferriss Show, showcasing its ability to produce concise yet comprehensive summaries

Claude 3 pumps out the most concise summaries, but don’t let that fool you.

Each section is clearly divided, with bold headings that perfectly capture the essence of the main ideas. Its brevity doesn’t mean it’s skimping on the good stuff – far from it. Key examples and direct quotes are all part of the package, shedding light on things like Seth’s approach to overwhelm and his views on authenticity versus professionalism. At the tail end of it all, a “Key Takeaways” section steps in, boiling down the big lessons into clear, actionable nuggets of wisdom.

So, while it may be the most concise, Claude 3 gets you straight to the good stuff without missing a beat.

The Verdict

All three models produced excellent summaries that capture the podcast’s core insights.

GPT-4o’s summary is the most detailed, making it perfect for those who want an in-depth understanding. Gemini 1.5 Pro shines with its engaging, narrative style, making the content enjoyable to read. Claude 3 excels in conciseness, providing key points without unnecessary fluff.

Ultimately, your choice depends on whether you prioritize detail, engagement, or brevity.

.

.

.

Deep Dive Summarization by Focusing on a Specific Topic

Summarizing extensive content like three-hour podcasts can be challenging, even for advanced AI.

The sheer volume of information can lead to summaries that only skim the surface, leaving crucial insights untouched. But hey, we’re not settling for that. We’re aiming for detailed, insightful summaries that dig deep into specific topics, ensuring we don’t miss a thing.

So, let’s dive in and learn how guiding AI to focus on specific topics can transform our summaries and bring us the rich insights we’re after.

How to Extract and Summarize Specific Topics

Step 1: Extract Relevant Content

First off, figure out the part of the content you’re really into.

For instance, if you’re curious about Seth Godin’s discussion on “Long Work vs. Hard Work” from his Tim Ferriss interview. Just grab that bit from the transcript.

Here’s how: Ask the AI to extract the segment where Seth talks about this topic. A simple query like, “Can you extract the part of the transcript where Seth Godin talks about the long work vs hard work?” should do the trick.

The AI might come back with something like this:

Step 2: Crafting a Detailed Summarizing Prompt

After you’ve pulled out the content you’re really into, it’s time to get the AI to work its magic.

You’ll want it to use the same super detailed summarization instructions we used earlier. But here’s the twist: you’re gonna ask it to only focus on the part of the transcript that’s all about the topic you’re dying to dive into.

Tell the AI:

Detailed Summary Example

Here’s an example of how the AI might respond with a detailed summary of the “Long Work vs. Hard Work” section:

### Detailed Summary of the Long Work vs. Hard Work Section

**Objective**:
This section focuses on the differences between long work and hard work, with Seth Godin explaining the concepts and providing examples from his experience.

**Main Points**:

1. **Definitions**:
   - **Long Work**: Involves tasks that are time-consuming and repetitive, such as billing hours for a lawyer or performing piecemeal work. These tasks are exhausting and provide diminishing returns as more time is spent.
   - **Hard Work**: Consists of emotional labor, confronting risk, and finding generosity. This type of work requires dealing with discomfort and seeing nuance. Hard work is about creating value through challenging tasks that don't always provide immediate applause or satisfaction.

2. **Examples and Insights**:
   - **Platform Work**: Platforms like Fiverr and Medium often reward long work, where additional hours don’t yield significantly better results.
   - **Emotional Labor**: Hard work involves emotional labor that might feel risky but is ultimately generous and useful over time.
   - **Seth's Experience**:
     - Early in his speaking career, Seth paid to give the first hundred speeches and was initially ranked very low among speakers. He faced getting booed off stage multiple times.
     - Starting the altMBA and other online initiatives involved significant hard work. Initially, these projects were not well-received, requiring persistence and the willingness to "make a mess" before finding success.
     - He described a critical moment of reflection in the desert where he decided whether to continue pursuing the altMBA concept or walk away. He emphasized the importance of making decisions, even risky ones, to eventually produce something valuable.

3. **Strategies and Tactics**:
   - **Focusing on Impact**: Seth stresses the importance of choosing projects that align with one's long-term goals and values, rather than being driven by immediate opportunities or fears of insufficiency.
   - **Iterative Process**: The altMBA was developed through iterative playtesting, with Seth pretending to be the system. This allowed for refinement based on real feedback before fully committing to the project.
   - **Building Trust**: Initially, the altMBA participants were those who gave Seth the benefit of the doubt, highlighting the importance of trust and reputation in launching new initiatives.

4. **Direct Quotes**:
   - "Hard work is the emotional labor of confronting risk; the emotional labor of finding generosity when you don’t feel like it; the emotional risk of seeing nuance where there isn’t a lot of nuance." - Seth Godin
   - "You have to get booed off stage a whole bunch of times." - Seth Godin, on the journey to becoming a successful speaker.

**Key Takeaways**:
- **Long Work vs. Hard Work**: Understand the distinction and focus on hard work that involves emotional labor and risk-taking to create lasting value.
- **Persistence**: Success often requires enduring initial failures and continuously refining your approach.
- **Strategic Choices**: Make decisions that align with your long-term goals and values, and avoid being driven by fear of insufficiency.
- **Building Trust**: Cultivate trust and reputation to help launch and sustain new projects.
- **Iterative Development**: Use feedback and iterative testing to refine projects before full-scale implementation.

And there you have it!

Zero in on the bits you care about the most and really dive into the nitty-gritty. This way, you save time and make sure you fully understand the stuff that matters to you.

.

.

.

Wrapping It All Up

Managing the vast amount of information we encounter daily can feel overwhelming.

Fortunately, AI is here to help. With significant advancements in AI technology, models like GPT-4o, Gemini 1.5 Pro, and Claude 3 have transformed the way we summarize long-form content. These models offer larger context windows, better recall capabilities, and more detailed summarizations, making it easier to grasp main ideas quickly and efficiently.

Crafting the right prompt is key.

Just like giving clear instructions to a new intern, a specific and detailed prompt can guide the AI to produce comprehensive and insightful summaries.

Whether you need an in-depth understanding, an engaging narrative, or a concise overview, these AI models cater to various needs effectively. Don’t let lengthy content overwhelm you. Next time you face a long article, book, or podcast, remember that AI can help you digest and understand the content like a pro.

Happy summarizing!

.

.

.

The author partially generated this content with GPT-4 & ChatGPT, Claude 3, Gemini Advanced, and other large-scale language-generation models. Upon developing the draft, the author reviewed, edited, and revised the content to their liking and took ultimate responsibility for the content of this publication.


Posted

in

, , , ,

by

Tags:

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *