Go further with AI: the intermediate path

Who this path is for

You already use an AI assistant day to day and want to take it further: make informed choices, understand the agents now showing up in browsers and apps, and use AI at work without exposing sensitive data. This path bridges the gap between everyday use and building your own AI agents. Each step introduces one concept and, where it helps, points you to a tool or data page on the site, updated every week.

The 12 steps

Step 1 — Compare assistants and subscriptions

The free and paid tiers of the same assistant don’t give you access to the same models, usage limits or features (web search, file analysis, image generation, agents). Before subscribing, ask yourself what you’re actually missing today. Then compare plans on the same criteria, and always check the date the prices were last verified.

→ To do: open the AI assistants comparison and write down the features that genuinely matter to you.

Step 2 — Understand browser agents

A browser agent is an AI that drives a web browser for you: it opens pages, clicks, fills in fields, compares offers. You’ll find them in dedicated browsers as well as inside some assistants. Their strength: chaining tedious actions together. Their weakness: they can misread a page, click the wrong button or be manipulated by booby-trapped content.

→ To do: before handing off an online task, assess it with the “Can I trust an agent with this?” tool.

Step 3 — MCP, explained simply

MCP (Model Context Protocol) is an open standard that lets an assistant or agent plug into other tools: a calendar, a folder of files, a database, business software. It’s often compared to a universal adapter: instead of a custom connection for every tool, there’s one shared format. Each connection gives the AI new permissions, so only turn on the ones you really need.

→ To do: keep the glossary open for related terms (API, server, tool) you’ll run into in the settings.

Step 4 — Multi-agent systems

Instead of one agent doing everything, a multi-agent system splits the work among several specialized agents: one researches, another writes, a third checks. This setup can improve quality on complex tasks, but it also multiplies the calls to the model, and with them the cost and the chances of something going wrong. For personal use, a single well-scoped agent is often enough.

→ To do: take a look at the agent frameworks explorer to see how developers organize these teams of agents.

Step 5 — Automate tasks with n8n, Make or Zapier

Automation tools like n8n, Make or Zapier connect your apps to each other: “when an invoice arrives by email, save it to a folder and notify me.” They now include AI steps to summarize, sort or extract information. It’s a great way into AI agents without writing any code. Start with a simple workflow, test it on dummy data, then expand.

→ To do: list the repetitive tasks in your week and pick the simplest, lowest-stakes one for your first workflow.

Step 6 — AI at work and company data privacy

Using a personal assistant with work documents can expose confidential information: customers, contracts, internal figures. Check your employer’s policy first; some companies provide business versions that come with contractual commitments on how data is used. Otherwise, anonymize and share only what’s strictly necessary.

→ To do: see AI in numbers for how AI use is evolving in European Union businesses, according to Eurostat.

Step 7 — Watch out for prompt injection

Prompt injection means hiding instructions inside content the AI will read: a web page, an email, a shared document. The agent may then mistake that text for your instructions and, for example, leak information or take an action you never wanted. It’s one of the main risks for agents that browse or read your messages. On the user side, the best defense is still to limit their access and approve sensitive actions yourself.

→ To do: review the permissions you’ve granted to your agents, extensions and connectors, and remove the ones you no longer use.

Step 8 — Tune your assistant’s privacy settings

Assistants offer settings that many people overlook: turning off the use of your chats for training, starting a temporary chat, managing memory (what the assistant remembers about you from one conversation to the next), deleting your history. The labels vary between companies and change regularly, so make a habit of checking after every major update.

→ To do: find your assistant on the AI assistants page, then go through its privacy settings in the app.

Step 9 — Make sense of benchmarks and rankings

A benchmark is a standardized test that measures a model on one type of task: reasoning, math, coding, general knowledge. No single benchmark tells the whole story: a model that shines on one test may disappoint on your real-world use. Look at what is being measured and when, and cross-check several indicators, including price.

→ To do: check this week’s AI ranking and read the methodology to understand how it’s built.

Step 10 — Open-source or proprietary AI

A proprietary model is only available through its maker’s service. A so-called “open-source” or “open-weight” model can be downloaded and run on your own machines, subject to its license terms. The former is usually easier to use; the latter gives you more control over data and costs, but requires more skills. Always read the license: open doesn’t mean unconditional.

→ To do: browse the open-source models page, paying attention to each model’s license.

Step 11 — The EU AI Act in a nutshell

The AI Act is the European Union’s regulation on artificial intelligence. It sorts uses by risk level: some are banned, others, labeled “high-risk,” are strictly regulated, others still come with transparency obligations (for example, knowing you’re talking to an AI), and many carry no specific obligations at all. Its rules are being phased in gradually. This is general information only: for a specific situation, refer to the official texts or a legal professional.

→ To do: follow AI news to keep track of the next stages of its rollout.

Step 12 — Move on to Build

If you’d like to create your own agents, choose a model for a project or estimate a budget, you’re ready for the next level. Take stock of what you’ve learned first: you’ll know whether a few concepts are worth consolidating before you dive in.

→ To do: take the AI level test, then join the Build path.

If some concepts feel rushed

This path assumes you already know how to write a clear request and check an answer. If that’s not the case yet, no problem: the Getting started path covers those basics step by step. Going back isn’t a waste of time; it’s often what makes the advanced steps truly useful.