
<Image
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If there's one thing I appreciate about the internet, it's people who find themselves fixated on a topic, and go _really_ deep to research and find the answer to a question. It's a helpful reminder that the internet puts huge power at our fingertips, and the connections available to us are truly incredible. There's something really special about watching people become experts on a topic, and then watching experts do their thing.

Is hyperfixation a good thing? Maybe. Not always. But it's a good thing when it leads to something useful.

There is a similar pattern I see in many of the best engineers I know - a simple need or curiosity will lead to something much larger. Chasing down a solution is often just a series of small questions that need to be asked and answered in order, rolling up to a larger goal.

A few examples from the tech world:

- My friend Charlie found herself wondering about the jets she could see from her apartment window in Seattle. One thing lead to another, and she built a javascript app that gives her [real-time information](https://charliegerard.dev/blog/aircraft-radar-system-rtl-sdr-web-usb/) on the planes whizzing by her window from live, public radio signal broadcasts.
- Curiosity about modifying the generator command in Ruby on Rails led my teammate CJ deep into the weeds of the [RoR source code](https://www.youtube.com/watch?v=8Rnf_-vDuaU&) to figure out how it all works, and how to make it better - his work will likely find its way upstream into core parts of the rails ecosystem before long.

---

## My own hyperfixation

A friend recently recommended a _3-hour long podcast about Costco_ to me from the show Acquired - and while it is an incredible deep dive, it also requires a huge time commitment to get through. I listened to the show, and wanted to chat about it with my teammates, but I knew that it was unlikely they'd have the time to listen the entire 3-hour show.

So, I did what any good engineer would do, and I figured out a way to summarize the show's transcript for each of my teammates in a way that was personalized and relevant to them. I built a little tool that would take the transcript, and then use a series of natural language processing tools to summarize the transcript into a few key points.

In a short amount of time, I found myself learning about:

- **The Podcast RSS feed format**, which contains audio files and metadata about individual episodes. I used this to grab both a show mp3 and transcript to use for summarization.
- **OpenAI's Whisper API**, which can be used to quickly transcribe audio files into text.
- The **GPT-4 API Playground,** where I could play around with different summarization models to see which one worked best for my use case.
- **LLM Prompt writing** for summarization, and ways to ask the model to summarize an episode for a specific listener's perspective, like our head of growth or a software engineer. Clearly, these two personas will have different interests in a show about Costco -- so I wanted to make sure the summary was relevant to them.

I ended up with a tool that I could use to summarize any podcast episode, and I learned a ton along the way.

### Read summaries of the Costco episode generated by AI

Sounds cool, right? I published a few sample summaries of the episode in an [article on my site here](/posts/acquired-costco-podcast-llm-summaries) for you to check out.

Is this something you'd a small amount for? [Drop me a line](mailto:hello@mikebifulco.com) or shout at me on [threads](https://threads.net/@irreverentmike) - I'd love to hear your thoughts.

---

These are a few incredible examples of people who have gone above and beyond to pursue answers to _non-technical_ questions:

### The Mystery of the Bloomfield Bridge

[The Mystery of the Bloomfield Bridge](https://tylervigen.com/the-mystery-of-the-bloomfield-bridge) may be the single most interesting article I've read this year. It shows how a seemingly simple question about the built environment can uncover a long and winding history of civic action, economic change, and a bridge that doesn't seem to go anywhere.

### Finding Michaelsoft Binbows

YouTuber Nick Robinson's 42-minute long vlog titled [I flew to Japan to visit "Michaelsoft Binbows" in person](https://youtube.com/watch?v=QRIklga9IBQ) is actually a follow-up to a previous video where he tried to find the real-life inspiration for the Microsoft Binbows logo. Don't know what the hell that means? Neither did I, but I watched both videos and I'm glad I did. The internet is a weird place.

---

## Build your expertise with some of my favorite resources

### 📰 API Specs, Schemas and Standards

In the latest edition of the APIs You Won't Hate Newsletter, my pal Alex goes deep on [API Specs, Schemas and Standards](https://apisyouwonthate.com/newsletter/api-specs-schemas-and-standards/) - what's the difference between JSON Schema and JSON:API? Find out here.

### 🎙️ The future of HTTP - software engineering daily podcast

I did a super in-depth interview about [The Future of HTTP](https://softwareengineeringdaily.com/2023/10/11/the-future-of-http/) with Nick and Roman, two engineers from Nginx working on a standard that is one of the most basic building blocks of the web. I genuinely had to study up on HTTP basics for this one, and learned a ton. I hope you do too!

### 🧬 Your Resume Sucks

The gang over at Polywork liked my recent newsletter on resume writing so much that they [reposted it on their blog](https://blog.polywork.com/how-to-fix-your-resume/) for the world to see. I'm happy to see that it's resonating with people, and I hope it helps you land your next job!

<small>

_note: Cover photo for this newsletter by [C D-X](https://unsplash.com/@cdx2?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash) on [Unsplash](https://unsplash.com/photos/PDX_a_82obo?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash)_

</small>


Chase your interests to build something useful


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  alt="The secret to using chatGPT to LEARN"
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AI is _everywhere._

Chat GPT and interfaces like it have found themselves centerstage in tech culture. AI features have been added to search engines, word proccesing tools, image editors, audio editing software, and for crying out loud, even [Snapchat](https://www.theverge.com/2023/2/27/23614959/snapchat-my-ai-chatbot-chatgpt-openai-plus-subscription)! It's an exciting time, and there's lots to learn from the new frontier of AI-powered tools -- especially, I think, for people who don't work in heavily technical roles.

I've been writing about generative AI for a while (["Hey Influencers, be careful with ChatGPT](https://mikebifulco.com/posts/product-marketing-defy-expectations)") - and I'm really happy to see that it's finally starting to find its way into the mainstream. It's super interesting to see all of the creative ways that people are using it. Seeing people find ways to use ChatGPT through the lens of their own experiences, skills, and desires is truly fascinating.

Today, I want to talk about **using tools like ChatGPT to learn**.

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One of the most common use cases I've seen for people using ChatGPT for the first time is - "tell me about `%some-interesting-thing%`". ChatGPT can distill complex topics into easily understandable summaries in a flash. It's thrilling -- seriously. But there's a tradeoff: ChatGPT's speed to respond can make it feel like we never need to think again. Got a question? Ask the robots. Curious about something? Ask the robots. Can't remember that one thing from high school physics? Ask the robots.

Offloading work from your brain is a good thing -- but making knowledge fully disposable isn't. Retaining _some_ of the things we learn is what helps us draw connections, foster creativity, and grow as people.

The [_Generation Effect_](https://en.wikipedia.org/wiki/Generation_effect) is the idea that you'll remember and understand stuff better when you put in the effort to do it yourself, rather than passively taking it in.

The thing is, when we take the time to experience and write about something, we're not just passively absorbing information. We're actively making connections, thinking critically, and making the material our own. It's the difference between watching a tutorial on YouTube about fixing your dryer, and then actually _fixing_ the damn thing yourself. Applied experience will do a lot more to cement learnings in your brainmeat™️.

When we engage with the material, we're more likely to remember it.

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  alt="The secret to using chatGPT to LEARN"
  caption="I often use ChatGPT to spur ideas for writing"
/>

This is where tools like ChatGPT come in. These AI-powered dudes can be super helpful in getting our creative juices flowing. They can toss ideas back and forth with us, ask questions, and give us inspiration. By ChatGPT to kickstart our thinking, we're more likely to dive deep into a subject and learn more than if we were just scrolling through generated content on our own. That's a win.

So, the bottom line is that by getting hands-on and generating our own ideas, we stand to learn and retain so much more than if we're just skimming through content. And when we use ChatGPT to help us, we're taking advantage of the best of both worlds: the AI's ability to spark ideas and our own creative thinking to really make that knowledge stick.

For me, that means using AI tools to generate high-level bullets, and doing the work of expanding on those points and summarizing myself. When I'm doing research, the initial high-level points for my notes may start from ChatGPT,but in the process of summarizing, they often get revised to a completely different set based on my perspective. It's often enough to cause me to ask the bots for more _specific_ summaries, or a pivot from one topic to another.

For example -- this very newsletter started out as 5 bullets from chatGPT about something called the [Doorway Effect](https://en.wikipedia.org/wiki/Doorway_effect).

The simple act of going a level deeper to engage with the things generates can be _surprisingly_ productive. Give it a shot the next time you fire up ChatGPT - you might be surprised by the things you learn.

---

## Tucked away in my notes about taking notes

- 🗂️ The [Tickler File System](https://officedynamics.com/43-folders-method-paper-system/) is a physical system for organizing tasks that need to be completed on specific dates. It pre-dates digital note-taking, but is certainly a forebearer of more modern systems like [Getting Things Done](https://gettingthingsdone.com/). It's a surprisingly elegant system - 43 folders are used to represent tasks for each day of the year. I know -- I was surprised, too.
- 🎥 My brilliant better-half Natalie recently released a video about [ChatGPT in K-12 schools](https://www.youtube.com/watch?v=M9oOtOkPTzc&t=175s) on her YouTube channel, Primary Focus. The big idea: it's time to _lean in_ to AI for education, and not build walls around it. The revolution is here, my dudes.
- 🧘‍♂️ Axios published a great article on [Using ChatGPT for therapy](https://www.axios.com/2023/03/08/therapy-chatbots-chatgpt-ai). Therapy is a good thing, and _many_ people can't afford it. Chatbots are not a perfect solution by any means, but if they can help expand access to healthcare, that's got to be a good thing.

## Cache me outside

- 🎙️ My [interview with Guillermo Rauch from Vercel](https://softwareengineeringdaily.com/2023/03/15/building-user-experiences/) for Software Engineering Daily went live last week. Guillermo is clearly an extremely thoughtful and clever leader -- and I was lucky to get some time with him to talk shop.
- 🎤 I also interviewed [YC Founder Danny Sheridan](https://softwareengineeringdaily.com/2023/03/15/building-user-experiences/) about his new startup, [Fern](https://www.buildwithfern.com/). If you're building SDKs or client libraries for your company's API, you'll appreciate this one.
- 📖 As I've been prepping outlines for a quick course on note-taking, I was reminded that I've shared some of my notery on my site before. My article [Book Notes: Working in Public](https://mikebifulco.com/posts/working-in-public) is essentially a direct copy/paste of my notes on a great book from _Nadia Eghbal_ called [Working in Public: The Making and Maintenance of Open Source Software](https://amzn.to/3LAc0a6).


An idiot's guide to using ChatGPT to make yourself smarter


It's no secret that I like playing with new tech, and lately there has been no shortage of AI tools making the news. By now, I've spent quite a bit of time testing out AI tools of various descriptions. It is encouraging to see consumer-facing AI products quickly becoming more useful.

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Even on my own website ([mikebifulco.com](https://mikebifulco.com)), I've used AI for a pretty broad variety of tasks. This includes writing and publishing articles, and maintaining the code that keeps the site running. Some recent articles have cover art generated by Open AI's DALL-E. I bet you can probably even pick them out if you look closely! Until this moment not a single soul has asked me about where they came from. That's one point to the machines for their good work. 🤖

I also use GitHub's Copilot as a pair programmer when I'm working on personal projects. It's definitely not perfect, and I have my concerns about the way that GitHub/Microsoft are sourcing the code that Copilot uses to generate suggestions, but it's still a really useful tool. I find that it helps me avoid brain fatigue when I'm coding, even if it suggests solutions that are sometimes incomplete or incorrect - it's still a great way to get unstuck.

Of course, alongside good experiences, I've had my fair share of eye-opening and distinctly bad experiences with AI tools. In my favorite article ever, I wrote about a positively jaw-dropping moment I had when attempting to use one product to write blog posts. Sound interesting? I hope so - give it a read here: [Why no one talks about the best marketing campaign in history](https://mikebifulco.com/posts/product-marketing-defy-expectations).

It's important to point out that AI makes many people (myself included) nervous. We're anxious about what implications AI tools have on the future of our work, culture, and politics. Those concerns are valid - right now, I think one of the most important things you can do is get some experience using AI. This will help you understand its strengths and weaknesses in a practical way. It will also help you stay in touch with what's going on in the industry.

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## AI tools you should try

These tools all use machine learning and AI to help you get things done. While most of them are not free, they all have some version of a trial or free tier that you can use to get a feel for them. If you haven't tried any of these, I recommend giving at least one a look - AI has come a **very** long way since the days of Goldeneye 64.

### No Code AI tools

📝 [Jasper AI](https://jasper.ai/) is a fantastic aid for people who write - it will help you write better emails, blog posts, and more. It's a great tool for people who want to write better, but get stuck on the details, or suffer from writer's block.

🎙 [Snipd](https://www.snipd.com/) is an incredible tool for people who listen to lots of podcasts. They use AI to automatically create an analyze transcripts of the shows you listen to. You can then use those transcripts to **snip** moments from a podcast, just like you'd bookmark a link to a webpage, or earmark a page in a book. I use it to take notes on podcasts that I listen to, and it's a great way to keep track of the things I want to remember.

🛋 [Interior AI](https://interiorai.com/) is a tool that lets you upload a photo of a room and it will suggest furniture that would fit in the room. It's pretty cool, and has been growing by leaps and bounds. Full disclosure: I happened across the product on twitter recently, and [have been helping its creator](https://twitter.com/irreverentmike/status/1579959127932968960) hone in on their pricing strategy using Stripe's tools. Apart from that, I'm not affiliated with, or paid by them in any way.

### For developers

✍🏼 [Open AI](https://openai.com/) are the creators of GPT-3, a language model that can generate text. It's pretty amazing, and you can try it out for yourself [here](https://beta.openai.com/).

🖼 [Stable Diffusion](https://github.com/CompVis/stable-diffusion) is an AI tool that you can run on your own computer to generate images from text. This one is for my more code savvy friends - it's written in python and not too challenging to use, but it does require some comfort with using a terminal.


What I learned from using AI in my work

#ai: 4 posts tagged

Chase your interests to build something useful

An idiot's guide to using ChatGPT to make yourself smarter

What I learned from using AI in my work

Hey, influencers: be careful with ChatGPT