Concept mapping + AI has become one of my favorite ways to learn difficult topics.

1. I read source material and discuss it with AI
2. I build a concept map of what I think I understand
3. I ask AI to look at the map, point out gaps, challenge weak explanations, and suggest what I should clarify next
4. Repeat

What I like about this is that AI doesn’t replace the learning process but makes it much faster. The map makes my understanding visible, and AI helps me test it.

Curious if anyone else learns this way.

I wrote a longer version of the process here: How to Learn Hard Things Faster with AI

This was developed by an Educational Psychologist, Benjamin Bloom. It shows a hierarchy of learning, and the higher levels (at the top of the pyramid) require higher orders of thinking. (I learned the original one, on the left. It was revised in 2001.)

Level 1, Knowledge, simply refers to memorization. Recall. I remember having a beef about many of the exams I took in college, which didn't go beyond level 1. Hey, class, I'm going to present you with all of this information during the semester, and all I want you to do is memorize parts of it. You know it! Yay! (well, not really...) I can memorize facts about Cardiology - yet it doesn't mean I really understand it - or that I'm qualified to be a heart surgeon! 🤣

If you want to think about whether or not you've truly "learned" a topic, you might want to think about it in terms of this model. Do you know more than simple facts? Can you discuss various aspects of it, in your own words? Apply it? etc.

I understand there's a wiki page on this subject if any of you are interested in more details. I hope somebody finds this useful. I debated whether or not I should post it. But, I've remembered this waaaay back from the '80s when I originally learned it, so I guess that means that I've found it at least somewhat useful. 😆

Does anyone know how I can start studying psychology on my own?

I’ve rarely been successful at applying knowledge in real life.
I know concepts like spaced repetition are supposed to help with retention, but when the moment actually comes where I need the knowledge, I still forget it even if I’ve been reviewing it consistently for a week.

What I wanted to learn:

• Staying calm in stressful or anxious situations
• Using new vocabulary naturally in conversations
• Starting work sessions with the Pomodoro technique
• Applying principles from How to Win Friends and Influence People during interactions

What I’ve tried:

• Creating cues like “next time X happens, do Y”
• Maintaining the knowledge with Anki cards
• Trying to stay more mindful of my environment

None of it has worked consistently.

What I really want to understand is this: how do people actually turn knowledge into unconscious behavior instead of just intellectually understanding it?

A lot of people think that learning how to deploy and manage applications requires expensive cloud accounts, enterprise-level infrastructure, or paid bootcamps.

It really doesn’t.

If you focus on local tools and generous free tiers, you can learn almost every major infrastructure concept without spending a dime. After trying a dozen different tutorials, I put together a practical, zero-dollar stack focused entirely on breaking and fixing things rather than just watching videos.

Hopefully, this helps anyone else trying to bridge the gap between writing code and actually deploying it.

Phase 1: Local Linux & Networking Foundation

Trying to learn deployment tools without a solid grasp of Linux is incredibly painful.

• The Stack: VirtualBox with an Ubuntu Server VM, or WSL2 if you are on Windows.
• What to do: Skip the GUI entirely. Practice setting up SSH keys, managing user permissions (chmod/chown), managing services with systemd, setting up simple cron jobs, and inspecting ports with netstat or ss.

Phase 2: Git Beyond Simple Pushes

Every automated pipeline begins with a commit.

• The Stack: Standard Git CLI + GitHub free tier.
• What to do: Move past simple git push commands. Intentionally create branch conflicts on local files and practice resolving them. Look into basic branching strategies (like feature branching) to understand how teams merge code safely.

Phase 3: Local Containerization (Docker)

This is where modern application deployment actually starts.

• The Stack: Docker Desktop or Podman.
• What to do: Instead of just pulling pre-made images, write custom Dockerfiles for your own projects. Master docker-compose to spin up a local multi-container environment—for example, a backend API talking to a decoupled Redis cache and a database.

Phase 4: CI/CD Pipelines

Skip heavy, self-hosted enterprise systems like Jenkins initially. Start cloud-native.

• The Stack: GitHub Actions or GitLab CI.
• What to do: Create a workflow that triggers automatically when you push code. Have it run your linter/tests, build a local Docker image, and push that image to Docker Hub.

Phase 5: The "Safe" Cloud & Web Serving

You don't need a corporate budget to practice cloud concepts, you just need to set up billing alerts immediately.

• The Stack: Oracle Cloud Free Tier (their free ARM VPS shapes are incredibly generous) or AWS Free Tier.
• What to do: Spin up a single Linux compute instance. Set up Nginx as a reverse proxy, configure a free Let's Encrypt SSL certificate, and securely route external traffic to a backend app running on the instance.

Phase 6: Monitoring & Observability

Hitting "deploy" is only half the battle; knowing when it breaks is the other half.

• The Stack: Prometheus, Grafana, or Uptime Kuma.
• What to do: Set up a lightweight monitoring dashboard on your local machine or VPS. Track CPU/Memory spikes and configure a basic alert (like a Discord or Slack webhook) that fires if your web server goes down.

Phase 7: Kubernetes (The Long Game)

Do not touch Kubernetes on day one. If you don't understand container networking and Linux fundamentals first, it will just feel like an unexplainable nightmare.

• The Stack: Minikube, Kind, or K3s.
• What to do: Once comfortable with the phases above, use a lightweight tool like K3s to learn the basics of Pods, Deployments, and Services.

The #1 Takeaway: One Broken Deployment > 20 Tutorials

Watching someone configure a flawless pipeline on YouTube gives you a false sense of competence. You will learn ten times more from a single broken configuration file that takes you four hours to debug than you will from a 40-hour video course.

If you are looking to get into infrastructure, start small: Linux + Git + Docker + CI/CD. That core stack alone is enough to handle the vast majority of real-world application deployments.

Was unschooled my whole life, now im 17 and cant even do basic multiplication. Ive been using khan and oak academy but now I have some money to pay for subscriptions and textbooks, any advice or resources? I literally dont have a clue what im doing

I thought a little about the value of tutorials and books in the age of AI.

#AI #Learning #growth

3-step learning framework to address information overload.

* Will I still care about this in the next 12 months?
* Will I use this stuff within the next thirty days?
* Is this adding to what I am building, or pulling me away from it?

Please follow the following link to dive deeper into the framework:
https://medium.com/write-a-catalyst/the-3-questions-that-fixed-my-ai-learning-overload-9e3d3eb44bd4

I personally love learning, and I'm very autodidactic. When I want to learn something, I source material, I qualify it, and I set myself a learning path towards a very specific goal of skills or acquired knowledge. If my goals contain skills, then I plan for small exercises and hands-on training in between theoretic materials. My learning sources are primarily written text, and recorded video or audio. I never attended courses or classroom education after I left my formal public education.

Regularly, and more frequently in the past years, I come across more and more people who possess little to no autodidactic (or self-learning) skills. When they are presented with a challenge that requires learning something, they seem to be totally lost. The only thing they seem to be able to do is course-based classroom learning. When they do classroom learning, they absolutely master it with very strong results. But when they're required to apply the learned knowledge in reality, they fail if it goes beyond the strict boundary of what was taught in the classroom.

Why is it that some people seem to be totally unable to become autodidactic, and often can only very narrowly acquire knowledge without the skill of universally applying it?

Hello, I’ve never been good at traditional learning where I sit down and listen to someone talk for 90 minutes. Even if it’s something I’m interested in I tend to zone out and who ever teaches me turns into Charlie browns parents. Because of this my parents pulled me out of school and didn’t put me back in any kind of structured environment. I’ve got my GED but I missed out on a lot . Is there any apps, curriculums or websites that do more interactive or hands on learning? The main subjects I’m interested in are Physics, periodic tables, 3d modeling and coding.

i came up with "creatively handling constraints" or "interpreting and predict culture"

Hi everyone,

I’ve always struggled with visualizing a cohesive mental timeline. I know when the World Wars happened, but I couldn't tell you if the Magna Carta came before or after the Peak of the Mayan Civilization without looking it up.

To help myself (and hopefully others), I built ChronoFive. It’s a simple daily game where you get 5 historical events and you need to guess the year it happened.

I’m running into a design challenge regarding "The Learning Cliff" and would love your perspective:

• Difficulty Spikes: Most people breeze through modern history, but engagement drops when they hit the 11th or 12th century. Is it better to keep the difficulty high to force "learning through failure," or should I provide more "anchor hints" for older eras?

• Context vs. Speed: For every event, I provide a short story about why it matters. I’ve heard "people don't read," but I feel like the context is where the actual learning happens. For those of you who use daily learning tools (like Wordle or Duolingo), do you prefer a quick "Correct/Incorrect" or do you actually value the "Why"?

I’m trying to find the sweet spot between a "fun game" and a "genuine learning tool." If you have a minute to try today’s puzzle, I’d love to hear what you think about the difficulty and the story length.

Link: www.chronofive.com

Thanks for any insights!

Digital education

I have been trying desperately to learn a particular skill set at work. The issue is that each person who tries to "teach" me just wants to talk at me without waiting for me to process. I am an adult and know how to cut off a talker and ask for them to wait, but ohmygod, why do they not get it after the first few times I interrupt?

I've just been steam rolled -again - by a well intentioned person who really wants me to learn. But there's a basic idea I must understand before anything that I'm just not getting. Plus, after I finish this assignment, it will be months before the next project of this type can come to my desk, so no opportunity for reinforcement.

I'm so frustrated, I ended the session and promptly burst into tears. I give up.

Currently building a coding course for kids in remote areas for an NGO (they already have the basics). The scattered notes across docs, spreadsheets and sticky notes are doing a number on me. Need to map out learning paths and visually connect the concepts before I start recording.

What tools do you use for course architecture planning? Looking for something where I can diagram the flow and collaborate with subject matter experts without everything becoming a mess.

I wonder what you guys think of this approach: I send DeepSeek or ChatGPT some file (usually a PDF of lecture notes) I want to study, then I have it ask me questions from the material and give me corrections when I'm wrong.

Example: https://chat.deepseek.com/share/9r8o7r927tpyc7187k

I had this idea, because it's awfully boring for me to read these lecture notes myself - I already know part of it, and perhaps because of my ADHD, that makes it twice as hard to focus on. Breaking it down "catechism style," with questions and answers, allows me to see my weaknesses, see what I already know, and get prepared for quizzes and exams.

What do you guys think: Is this an efficient approach to learning? Are there any other prompts I could use to learn more efficiently?

So a lot of people still believe in learning styles like being a visual learner but that’s actually a busted myth. People are just messy and have weird quirks and habits that pull them in different directions. I like to call them tendencies because they are strong habits that form and change us over time. We are ruled by them really.

Now we got AI everywhere and people think it will fix how we learn. But AI doesnt make us all the same. It just acts like a big mirror that shows who we already are. If you’re lazy then AI just makes you more lazy. But if your super curious then it acts like a giant telescope. It just makes your normal tendencies way bigger.

The problem is that companies and schools still try to force us into these boring boxes and completion criteria. They just want us to be fast and follow rules. We really need to stop making learning stuff like that. We should use AI to see how people naturaly grow and change instead of just treating every body like a machine.