Introduction
in a world where knowing a programming language was considered “hot”. If you knew how to program, you had an advantage: you could create software and automate tasks, while others depend on you. Now, the world has changed, and everyone can build AI without a single line of code.
AI is much more advanced than chatbots. In the past few years, learn how to use it ChatGPT effectively it was enough to stand out. In 2025, building local agents still meant writing Python code, with developers turning to tools like LangChain to run open source models directly on their computers. However, since the beginning of 2026, the state of AI has grown significantly. We have now entered the era of non-code AI, where anyone (without a technical background) can quickly build, deploy, and manage multiple custom agents.
But don't be afraid. In this article, I will explain what skills you need to succeed in this new era (to feel “special” again).
It is appreciated
Every interaction with an AI model starts with a command. The difference between intermediate users and advanced users is not the model itself. As much as it pains me to say it, writing good warnings is the new coding. If you want to use AI products, you need to know the industry standard of information.
Over the years, we have seen many ways to inform, such as Zero-Shot, ReAct, Chain-of-Thoughts… (you can check this article). Today, there are two main frameworks for informing:
- TCRF (most commonly used):
- Work (T) – Clear instructions that can be done (eg “write email to requester”).
- Context (C) – Basic information and constraints (i.e. “after 2 weeks of CV screening, you got a young talent. Don't be too formal but keep it professional“).
- Role (R) – Person to be replaced by AI (ie “you are an experienced HR manager“).
- Format (F) – Required output structure (ie “an email should have three sections, use the following example…“).
2. TCREI (introduced by Google as an iterative and improved TCRF extension):
- Work (T) again Context (C) they are the same as before.
- References (R) – Role + Format (ie “you are an experienced HR manager. An email should have three sections, use the following example…“).
- Measure (E) – This is an add-on: ask the AI to deeply evaluate your output based on certain criteria (eg “after writing the email, rate it on a scale of 1-10 regarding: Clarity, Engagement, Persuasiveness, and Alignment. Show some weakness”).
- Iterate (I) – Instruct the AI to improve the output based on the evaluation (eg “and rewrite the improved version“).
Products
There are so many AI products. There is no official registration, but industry analysts estimate that thousands of new AI tools, wrappers, and applications are created each week. The total number of active AI platforms in the ecosystem is estimated at 90,000.
To this day, the market is still dominated by the “Big 4” General purpose cloud agents: OpenAI's. ChatGPTGoogle GeminiAnthropic's Claudeof X Grok. Then there are special products for certain domains, such as Confusion study and research, and Cursor or GitHub–The pilot for coding (in fact, a growing trend is “Agentic Engineering” which is new AI coding software).
Another great cloud-based way to play, host, and share AI projects for free HuggingFace-Spaces.
However, that seems to be the case the market is recently shifting to local models ensuring data privacy, eliminating recurring API costs, reducing cloud latency, and maintaining control over proprietary workflows. We are talking about independent closed source products (eg Claude-Cowork again Claude-Code), and open source solutions (eg OpenClaw again Hermes) which should be paired with an LLM management application (e.g Ollama).
Please note that to run utilities locally, you need a machine with at least 16 GB of RAM and 8 GB GPU (or total 24 GB of integrated memory pool).
Currently, Claude the most intelligent AI out there, so it is important to understand the differences between the products of the Anthropic family:
- Claude (web app) is a standard cloud-based chatbot, no different than ChatGPT, Gemini, or Grok. This is for the general user.
- Claude-Cowork (desktop application) for smart but non-technical users. It works in a sandboxed environment on your PC with selective access to your folders. It's ready automatic operation.
- Claude-Code (terminal application) is for developers. It has full access to your terminal, so it can run the code. Useful for building applications.
Workflow and applications
We have moved from active AI to active AI. Previously, it was you who sent your chatbot asking questions. Now, the agent congratulates you and tells you that the job you referred to him has been completed. With the right setup, you won't have to do anything (except to update and verify the output). AI automatically researches, organizes, implements, and delivers results.
Local AI Agents open up a completely different way of working, as well as a new way of life. To put it another way, in this new era, everything that does not require physical action can be automated with AI. So that's what you have to do… learn to automate your life:
- all your daily activities follow a workflow that can be done automatically by giving instructions (ie “research this article, enter it into Excel, and email it“)
- All your ideas can be created in the form of operating system with to give a goal (ie “I am looking for a mobile dashboard that I have installed“)
During your work, you certainly need to connect your Agents to real-world tools, systems, and data. The best way to do that is to pass MCP servers. MCP (Model Context Protocol) is an open source standard framework introduced by Anthropic that allows AI systems to communicate with external applications and data sources. An MCP server is simply a set of tools written by those rules (or your Agent's “skill” in gaming terminology).
There are over 30,000 MCP servers available (full list here), so anyone can build and publish one. The main platforms for creating and running MCP servers are: n8n (runs in place) and Zapier (cloud based).
The conclusion
As AI continues to evolve, the skills needed to stay ahead of the game change. You need to know which products to use and how to maximize profit from them. Of course, the underlying capabilities (thinking, automation, integration, and software creation) will always be useful regardless of which AI products dominate the market.
I recommend using Claude-Cowork automating all of your life's repetitive tasks. Then, the more you work on that, the more ideas you might have. If so, switch to Claude-Code and start building things. If you have good hardware and don't want to pay Claude, run OpenClaw or Hermes in place to do the same things. Finally, if something you've built is successful, upload it to the MCP Server and publish it so other people can use it.
All of those are the “hot” skills of this new era of No-code AI.
I hope you enjoyed it! Feel free to contact me for questions and feedback or just to share your interesting projects.
👉 Let's connect 👈
(All images are by the author unless otherwise noted
