If I were starting AI from scratch in 2027, I’d learn these, not tools

A new model every week, a new tool every month. In a world changing this fast, what should you learn, and which tool should you hold on to? My answer: instead of memorising tools, learn the three things that stay with you when the tools change.

This post is a map if you’re new to AI or lost in the crowd of tools. First, which tools I hold on to today and why; then the three things that don’t change; and at the end, five habits I use every day as someone who uses Claude Code at least five hours a day. If you already use Claude Code daily, skip straight to “Tools change, the chain stays”. (The video is in Turkish.)

1. THE TOOLS CHANGE EVERY MONTH

This year Gemini CLI closed to individual users. Roo Code shut down. Sora went away first as an app, then from the API too. OpenAI’s Agent Builder is shutting down as well. How many of the tools you learned last year are still standing?

Meanwhile everyone launches and markets a new app every week. It has turned into an AI junkyard. But that noise doesn’t mean automation is pointless. In small businesses, in companies, in our own teams, agents do more work every day. Companies that keep the door shut to agents today because their data is valuable will join in as the security layer matures.

2. HOLD ON TO WHAT UPDATES FAST: CLAUDE CODE AND CODEX

Claude Code gets an update almost every day: a new feature in the terminal, a new mode in the app, and now and then a new model. Look at the release notes: between 20 August and 14 October, so in eight weeks, 60 releases came out. Codex is moving at the same speed.

My rule is simple: don’t tie yourself to an agent system whose updates have slowed and that has fallen behind. If you have serious work or a company, at some point you’ll need to really integrate one of them. If you use Claude, Claude Code; if you use ChatGPT, Codex.

There’s another side to this. If you sell a product, a service or consulting, you need to build it so these agents can use it. Your product should be connectable and should solve an agent’s problem. Your customer is sometimes no longer a person, but that person’s agent.

3. NO BUDGET? THE DOOR IS STILL OPEN: OPENCODE AND OPEN MODELS

If you’re a student, in high school, or can’t spend money yet, look at OpenCode. It’s open source, with both a desktop app and a terminal tool. You can plug in cheap or free models like GLM, Kimi, DeepSeek and Qwen. When one model’s limit runs out you switch to another; the project doesn’t stop, and you learn to work with different models.

A 14-year-old I know makes Roblox games with OpenCode and open models, on a theme he picked himself. He spent a weekend not playing games but making one. Kids his age have no budget for Claude Code, but that doesn’t stop them.

If you want to work entirely on your own computer, in a closed box, there are local model tools like Ollama; if you open it to the network, don’t forget a password. An open model doesn’t always mean a local one; very large models don’t fit on a home computer. To try different models with a single key, there’s OpenRouter.

4. IMAGE, VIDEO, AUDIO AND DATA: THE AGGREGATORS WON’T AGE EASILY

Claude has no image or video model of its own. OpenAI has an image model, but Sora was removed from the API too. Unless these two companies become a strong home for image and video, aggregator platforms like fal and Higgsfield won’t go out of date. They bring Seedance, Nano Banana, Kling and Veo together in one place: you connect your agent once and switch models in the prompt. So what you need to learn isn’t a single model, it’s how these aggregators work and how they plug into your project. The two I use most are fal and Higgsfield (Higgsfield is currently my sponsor; this post isn’t sponsored).

For voice and dubbing you can use ElevenLabs, for songs Suno. If you want to try open models without installing them, look at Hugging Face.

Then there’s data: if you want your agent to do good work, you have to give it good data. I pull data with Apify; it takes it from a site, a social media account or a map with ready-made tools, and my agent analyses it. I keep the data in Supabase; database, user login and file storage in one place. And I connect the app to Vercel through GitHub, and it’s live in a few minutes.

Some of these names will have changed by next year. Now to what doesn’t change.

5. TOOLS CHANGE, THE CHAIN STAYS

Tools change, but the structure of the automation we build doesn’t. Every automation has the same four links:

Trigger: your prompt, a timer, or a new email coming in.
Brain: the model that reads the job and makes a plan.
Hands: the agents and tools that do the work.
Output: the result at the end.

We used to build this chain in n8n by connecting boxes with arrows. Today we build the same chain by describing it to Claude Code. OpenAI closing its own drag-and-drop Agent Builder and recommending agents built with code and natural language instead points the same way.

The chain doesn’t depend on your profession either. A doctor drafting notes from a conversation, a lawyer turning contracts into a table, a teacher preparing new questions and quizzes, a psychologist writing a session report: all built with the same chain. In all four, the decision stays with the human.

It’s the same for me. In my morning flow the trigger is a timer and the brain is Claude; my agents do the work and an output arrives at the end. In my reels machine I shoot a new video, tell my agent “I shot a new video” and wait. It does the rest in the background, because that’s how I built the architecture.

6. THE SECOND THING THAT DOESN’T CHANGE: WHICH MODEL FOR WHICH JOB

Using models doesn’t mean picking the strongest one and giving it every job. Every job has its model. I use Fable 5.1 when writing content and articles, and Opus 5.5 for video production and motion graphics. Anthropic’s own recipe is similar: Fable for the really hard job, Opus if you’re unsure, Sonnet or Haiku for subagents and bulk work.

This rule isn’t only for Anthropic models. In image and video generation, in web design too, you need to know which model suits which job. The kid making Roblox games learns exactly this when he switches models after hitting a limit: how to work with which model. Models will change every week; knowing how to work with them will stay.

7. THE THIRD THING THAT DOESN’T CHANGE: YOUR OWN AGENT THAT KNOWS YOU

I keep Hermes Agent separate from Claude Code and Codex. It has a good agent architecture inside and turns it into a personal, model-independent agent. You pick the model; the tasks and the architecture are already there. You talk to it from Telegram, switch the model with /model, and it runs 24/7.

Its real difference is that it learns on its own. The more you use it, the more it writes its own skills and notes: what your latest work is, what you like, which project worked, which one needs redoing. Just as an intern who just joined a company and an employee of ten years don’t have the same experience, an agent of one week and an agent of one year aren’t the same.

A single server is enough to keep it running: a VPS, Docker, or a computer that stays on 24/7. If you don’t want to set anything up, Claude Code has Routines; a task you schedule runs in Anthropic’s cloud even when your computer is off.

8. FIVE HABITS FROM SOMEONE WHO USES IT FIVE HOURS A DAY

Describe what you want down to the finest detail. Whenever I describe it incompletely, I waste tokens. And before starting a new project, I always have it make a plan.
Your voice notes are prompts too. If writing feels hard, explain it by talking with /voice in Claude Code. When an idea comes to you away from the computer, record it and give it to your agent later.
Don’t describe, show. If you want to produce a video, give it the video; if you want something like a site, give it the site as it is. To work out how an app works there’s REA; copies handing out zip files are fake, use only the official repo.
Give corrections with a reason. Instead of “I don’t like it, fix it”, say “this part should be like this”. If you don’t write what you think, the agent has to guess.
Don’t ask for approval of your idea, ask for analysis. Models tend to want to please you. Instead of “I love this idea, what do you think?”, say “I’m thinking this. Analyse it: will it work, put its weak points in front of me.”

So: a new model every week, a new tool every month will keep coming; but the chain, the right model for the right job, and the agent that knows you will stay. You don’t have to learn every new tool perfectly. Pick a project and try those tools on it for hours. My first projects were really bad; they got better by doing. You’ll learn the tools as you build, too, and when the time comes you won’t be late.

Every tool’s link and the alternatives from the strips at the bottom of the screen are in the video description: https://youtu.be/PJ3vjI5qmF0