The Chamber 🏰 of Tech Secrets is open. Due to reader feedback, we’ll be abandoning the “Chamber of Tech Secrets #X” title and go to a real title for easier search in the Substack app and elsewhere. Title inversion begins now!
Superpowers are rare or unique characteristics—often attributed to heroes—that set them apart from the common man: incredible speed, the ability to fly, unworldly strength, teleportation, or a cool bat suit with utility belt. 😜
Superpowers also exist in the real world. With the advent of the AI age, some powers are bubbling to the top of the list in important. By cultivating them intentionally, we can set ourselves up for outsized success and drive incredible outcomes (maybe even save the world!).
Have you ever felt “behind” in your area of expertise? Have you looked around at some of the elite thinkers in your domain and told yourself “there is no way I can ever do what they do… they know so much. They seem to have a superpower that I don’t”? Being around such people is a great learning opportunity, but it can also be intimidating and even demoralizing. I remember many times where I was talking with someone who bounded deep into the technical weeds and I wondered to myself “how do they know all this stuff?”.
The answer to this question has always been, in some form or fashion, “experience”. Not in the “x years of doing y” that pads resumes… the real kind of experience. Real experience is where the [for our purposes] technology has been rigorously tried and applied over many hours of time, often in substitute for sleep. Adamant determination to “figure it out”, rigorous trial and error, and thoughtful application of learnings builds something over time—expertise—that is hard to duplicate otherwise. I call the person that has all of this experience the “Tech Genius”.
Let me be clear — I am not the “Tech Genius”.
Have you ever had thoughts like…
“I could never start an open source project… people would just laugh at my code”.
“TPM, endorsement key, attestation key, measured boot, platform configuration registers… what exactly is happening here?”
“Models invoke tools via the Model Context Protocol (MCP) — think of it as USB-C for models”. [sounds simple, but the model doesn’t actually invoke the tool, so there ya go]"
“I could never make my own linux distribution”
I have good news. Regardless of the doubts you may have, the legacy barriers to learning are rapidly being removed.
[[ Enter AI ]]
Alongside experience, the next best way to learn is through great teachers and mentors. But the great ones are not equally distributed.
AI assistants — specifically via the chat (or voice) interface — unlock the potential for incredibly high-speed, high-quality learning via a digital mentor or teacher. If invited to do so, they can play a technical mentor role on topics of interest and take you down the proverbial rabbit hole as deeply as you desire to go. I believe this technique works extremely well for understanding how technical things work since that is, by nature, something that is already present in the corpus of human knowledge and is often well-documented.
There have always been a great resources available in the form of technical books or awesome resources like Kubernetes the Hard Way. What is absent in those is the ability to ask questions as you go, and the ability to shape the material in the way your brain works. This is where an AI mentor has huge potential to help. While AI experiences have a tendency to spew a lot of text, you can ask things like “lets walk through this step by step to make sure I really understand”, and then you can move at the speed of your own questions and processing.
Here are a few of my recent experiences:
AI as Teacher/Mentor: I wanted to understand every detail of how a device with a TPM chip can be securely on-boarded and trusted in a datacenter or edge environment. I wanted to understand every key exchange and certificate signing request. I wanted to understand how to validate that the machine was running the software and configuration expected (measured boot). I wanted to understand how the inbound device trusts the server that configures it. So I spent about 90 minutes one evening asking question after question until there were no remaining mysteries. My next step is to apply this to my Edge Lab project (starting soon!).
AI as Co-Architect: Last week, I was working on a personal project to build out a series of AI agents to help me with some financial investment research. I used a few AI assistants to help me think through my architectural design, challenge some of my ideas, and ultimately arrive at a better overall architecture. I am also working on a potential open source project that I built to help me with agent discovery. AI was a big help crafting and refining the design there, too. It offered me several feature ideas I didn’t think about on my own.
AI as Engineer: Sometimes there are small hurdles in your project that get you stuck from moving forward. While working on a project a few weeks ago, I needed OAuth, specifically Auth Code Flow. Rather than spending several hours scouring for open source projects and getting them running, I “vibe coded” a mock OAuth server that just did Auth Code flow in about 2 minutes and used that for testing (all local so no worries). There is much more to say about vibe coding in a future post.
With AI being here, what do we need to bring to the table? I submit that there are three key characteristics that stand out as superpowers in this new era.
Curiosity: Those who are actively curious—those who ask questions until achieving understanding and who put the learnings into practice—will learn much faster than those who don’t. Technical knowledge has a compounding effect—the more you have learned, the easier it is to learn more. Said another way, your learning potential (considering the corpus of what is already known) will be capped only by your curiosity and resources you have available to you (most of us won’t be setting up clusters of Nvidia H100s). Rapid learning is one of the most important characteristics of a human in a rapidly changing world.
Creativity: AI models are not intrinsically creative. From Balaji: “… AI is really amplified intelligence rather than truly agentic intelligence, since it requires the creative prompt to get started”. My thesis is that AI will be most valuable to those who have an abundance of creative ideas for using it. I mean creative ideas very broadly: “How can I contribute to shaping reality?”. This appears in the form of questions, business ideas, open source projects, ways to automate workflows, and much more (yes, I did leave out images, music, video—also relevant).
Courage: We must do something with what we learn. We must create or we have simply entertained ourselves and occupied our time. It takes courage to reinvent oneself and to create.
Paired with a rapidly-improving AI complement, these three superpowers will propel us into shaping the future we want to see.
Okay, so what can you do with this information? A few suggestions:
Start a list of topics you are interested in but don’t fully understand. Add to it often. Pick one topic from the list each week and work through it to the level of your satisfaction under the tutelage of your favorite AI assistant. I suggest just picking one at a time as it is easy to get distracted by too many new ideas (guilty!).
Put ego aside. You may feel like you should already know something and feel a little funny about admitting to yourself that you knowledge is more shallow than you think it should be. Don’t get caught in the trap of thinking you are better than you are.
Go beyond conceptual understanding to doing. Doing is where the experience will come from. Don’t be afraid of doing something wrong or having to start over many times. Doing will show you where the gaps in your understanding are. Don’t concern yourself with if the thing is already a “solved problem”… build it again yourself for understanding alone. Don’t forget take time to celebrate what you do and what you learn.
Share what you build and what you learn publicly. Put the code on your GitHub. Write a blog post. Share the parts of your thinking that are still cloudy. Explain why you decided to take path X over path Y. The human feedback you get, even if it comes across as judgmental or “jerky” at times (and sometimes it will though most will be friendly and positive), will be useful to validate your learnings and refine your thinking.
Develop the characteristics of curiosity (see above), creativity (change inputs and practice divergent thinking / steel manning), and courage (best learned by taking action).
Let’s wrap by recalling that the purpose of these superpowers are to accelerate learning—which is to say intelligence, since intelligence is simply the speed of applied learning (via Alex Hormozi)—for the purpose of doing something good in the world.
Pick a subject you’d like to understand, give this a try, and let me know how it goes in the comments or on LinkedIn. Happy learning friends!
Yes, real experience still matters. But you can close the knowledge and understanding gaps must faster than ever before by trying, failing, and fixing in a lower-stakes environment. No, you can’t blindly trust everything AI says, but it can be a very useful teacher and assistant. No, you shouldn’t vibe code up a critical business application and sling it into production if you have no idea what you are doing. The horror stories are already out there. Yes, it will still matter what we know as AI continues to “do all the things”. The nature of those things may change, but they will still matter. None of this matters if you don’t act on it.
No posts
Comments
Nothing yet. Say the first thing.
Sign in to join the conversation.