How to Deal with AI FOMO and Not Get Left Behind
How to deal with AI FOMO without chasing every new tool, and how to build learning and usage habits that stand the test of time.
← Paths
Guided learning path
Work smarter
A path that turns occasional AI use into a repeatable personal way of working.
- Core
- 10
- Deep dive
- 8
- Practical exercise
- 2
Who this path is for
For people who already use AI and want less noise, less wasted context and more useful assets and workflows.
What you will know
By the end, you will have a method for choosing a focus, writing requests, managing knowledge and context, and turning repeated work into a process.
Choose what matters
Reduce noise and replace tool chasing with durable abilities.
This chapter starts with Start by reducing noise and choosing a learning and usage routine instead of chasing every new tool.
Why now Once you stop measuring yourself by tools, focus on abilities that last: explaining, understanding systems and thinking in products.
The New AI Skillset Everyone Working with AI Must Develop
You don't need to know how to code to work with AI — but you do need to develop three core skills: explaining clearly what you want, understanding how systems work, and thinking like a product manager.
Communicate with AI
Turn intent into a clear request, examples and an asset you can improve.
This chapter starts with The ability to explain becomes a practical structure of role, context, constraints and outcome.
RICE FRAMEWORK – The Prompt That Will Get You Precise Results 💬
What is the RICE Framework and how to use it to write more precise prompts that return useful, consistent answers.
Why go deeper here After a clear structure, add the right number of examples to show the model the pattern without overwhelming it.
How Does AI Learn? Zero-shot & Few-shot Learning
What are Zero-shot and Few-shot Learning, how AI models perform tasks with minimal examples, and how to use them in prompts.
Why go deeper here Examples guide the result; breaking a task into steps helps when the problem becomes more complex.
Chain of Thought (CoT) – The Method Behind Reasoning Models 🔗
What is Chain of Thought, how does it relate to Reasoning models, and when should you ask a model to explain its steps rather than give a short answer.
Why now A prompt that works should not disappear in a chat. Turn it into an asset you can find, improve and share.
Working Smarter with AI – Prompt Manager Tools
Prompt manager tools help you save, organize, reuse, and improve the prompts that deliver the best AI results. Learn why prompt management matters, which capabilities to look for, and when to build a prompt library.
Build a personal knowledge system
Connect stored knowledge, tools that organize it and context a model can process.
This chapter starts with A prompt library is part of a broader system: an external place that stores knowledge and reduces mental load.
Outsourcing Your Second Brain 🧠
I want to share a method I've been experimenting with lately — one that lets me "outsource" my brain to help me keep up with the pace of change. Some of you have probably heard of it. It's called a "Second Brain."
Why go deeper here After building a second brain, connect the agent so ideas, summaries and tasks move directly to the right place.
Connecting Claude to Notion — MCP & Docker Guide for Smart Automation
Connecting Claude to Notion turns ideas, meeting summaries, and tasks into Notion pages effortlessly, using MCP and Docker. A practical guide that saves you hours of work and organizes your knowledge in one place.
Why now Connecting knowledge raises a new question: how much information should be passed at once? Tokens explain the budget and limits.
What Are Tokens and How Do They Affect Language Models? 🪙
What tokens are in language models, how they affect the context window, and why they matter for working effectively with LLMs.
Manage context and routine
Reduce overload, organize files and learn from work already completed.
This chapter starts with Apply the token principle in a real work environment and identify what consumes the context window before the task begins.
Managing the Context Window in Claude Code
The Claude Code context window is a precious resource. Before you've typed a single word, you've already burned thousands of tokens. This guide explains why that happens and how to deal with it.
Why go deeper here After cleaning digital context, let an agent perform a defined action on files instead of merely suggesting an organization.
How to Connect Claude with MCP and Let It Organize Your Files
How do you connect Claude with MCP to your personal computer? A practical guide to connecting the AI agent to your file system — including steps, use cases, and real-world examples.
Why now Organizing files is only the start. Markdown and YAML turn context into a structure an agent can read consistently.
Markdown Files and Context Engineering When Working with AI Agents
In this post we explain what MD files are, how they are used in AI workflows, and why defining them correctly matters when working with agents.
Why go deeper here After defining a way of working, use session data to see what actually worked and which rules should change.
I Used the Insights Command and Got a Performance Review From Claude Code
I ran /insights in Claude Code and received a personal report on 34 sessions: what worked, where I lost time, and the rules I changed.
Why go deeper here Feedback exposes repeated friction. Instead of handling it manually, build a small personal tool for that exact problem.
Disposable Apps — How to Build a Personal Solution in 10 Minutes ♻️
In an era where anyone can build their own digital solution in minutes, disposable apps are becoming a tool for learning, problem-solving, and smart self-customization with the help of AI.
Turn the method into a repeatable process
Capture operating instructions and choose the right level of autonomy.
This chapter starts with What worked in one session becomes a Skill with inputs, process, boundaries and checks that can run again.
What Are Skills in Working with AI Agents
If an AI agent is a new employee, a skill is their instruction sheet: what the goal is, what information matters, how to work, where to stop, and how to verify the result is good.
Now put it into practice Now turn the principles into practice: build your own Skill and check whether its instructions are complete and useful.
Skill Builder
A guided flow for creating Claude Agent Skills with SKILL.md preview, quality checks and ZIP export.
Exercise outcome
A Skill ready to review, download and share.
Now put it into practice After creating a Skill, compare it with reviewed examples to learn strong structures and avoid reinventing everything.
Skill Store
A curated library of Claude Agent Skills reviewed before publication.
Exercise outcome
A ready-to-use Skill to study or adapt to your workflow.
Why now Finish by deciding when fixed instructions are enough and when an agent must interpret a situation and make decisions.
What Is the Difference Between Automation Workflow and Agentic Workflow
A clear explanation of the difference between standard automation and Agentic Workflow, and when to use each approach in your organization.
You completed the core path. Where next?
Continue with the remaining deep dives or choose another path.
You also completed every deep dive—the entire playlist is done.