Learn AI
From zero to expert. Choose your level, learn at your pace. Each article has a quick view (3 min) and a full view to go deeper.
Beginner17 articles
Understand the basics in a few minutes
Skills & MCP: the map before the territory
Step 1/9 of the Skills & MCP learning path. The mental model that makes everything else obvious: a skill is a manual, MCP is a pair of hands, the model is the brain that orchestrates. With the visual map that will follow you through all 9 steps.
I asked 8 AIs which AI is the best
Eight AIs, four questions, one matrix. Who recommends whom, who cites itself, and why half the AIs answer with outdated market knowledge. A study against taking AI recommendations at face value.
AGI: when is it really coming? (2026 analysis without hype)
Sam Altman says 'few years', Yann LeCun '20 years min', expert median 2047. We analyzed predictions, benchmarks, 4 major obstacles, 3 scenarios.
ChatGPT marketing: 50 pro prompts saving 10h/week
50 tested marketing prompts: content, social, email, ads, analytics. With pro prompt anatomy and the golden rule for x3-10 results.
30 pro prompts worth gold (2026 catalog)
A good prompt is worth 10x more than a good AI. We selected 30 pro prompts by category: writing, sales, code, marketing, career, productivity.
GPT-5: everything it really does in 2026
GPT-5 released August 2025: 71% on SWE-Bench (vs 50% GPT-4), integrated Sora, autonomous agents. We tested everything for 6 months, strengths, limits, prices.
AI and jobs: which professions disappear and emerge in 2026?
8% of jobs will truly disappear, 35% will transform, 12% of new AI jobs emerge. Complete mapping of at-risk jobs and 5-point strategy to protect yourself.
AI phishing: the new wave (vishing, smishing) in 2026
95% of security pros say AI makes detection harder. Cloned voice vishing, perfect emails, hyper-personalized SMS: we explain everything with pro diagrams and 6-layer defense plan.
ChatGPT vs Claude vs Gemini: which to choose in 2026?
The 3 AI leaders in 2026 dissected without BS: strengths, weaknesses, prices, French quality, use cases. With a guide to choose based on your needs.
Veo 3, Sora, Kling: creating videos with AI in 2026
Veo 3 (Google), Sora (OpenAI), Kling (China): 3 AIs that generate pro videos from text. We explain how they work, which to choose, costs and killer use cases.
Deepfakes: how to protect yourself in 2026
$25 million lost in one fake video call. Your children's voice cloned in 30 seconds. Deepfakes are the massive 2026 scam. We explain how to spot and protect yourself.
AI and privacy: how to protect your data
Your ChatGPT conversations are not private. Here are the GDPR-friendly best practices to use AI without risking your data: settings, anonymization, local models.
10 truly essential free AI tools
Our selection of 10 free AI tools (no credit card) covering 90% of use cases: chat, image, audio, transcription, translation, code. Enough to replace €300/month of paid apps.
How ChatGPT works in 5 minutes
ChatGPT is just a juiced-up autocomplete that read the Internet. We explain simply, without jargon, how it really works and what it's for.
Pay or not for an AI?
Comparison of free and paid versions, what really changes, and when the subscription (20-30€/month) becomes profitable. With real cost calculations.
Prompt engineering, the normal version
The 7 techniques that work to get better AI responses. No need to be technical: context, precision, examples. With ready-to-copy patterns.
What is a LLM?
Understand in 5 minutes what powers ChatGPT, Claude, Gemini and all the others. From simple analogy to Transformer architecture, everything you need to know.
Intermediate23 articles
Go deeper, understand the mechanisms
AI visibility: getting your site into the answers of ChatGPT, Claude, Perplexity and Copilot
Your customers now ask an assistant, which reads the web on their behalf. This guide explains how these assistants access your site, why most companies block them without knowing it, and gives the full implementation protocol: policy, robots.txt, CDN, firewall, measurement and governance.
Trust Index Barometer #1: what official documentation really says about 38 AI models
Before verification, 37 of 38 models scored 31/100. After reading vendors’ official pages, they range from 44 to 80. Anthropic with no EU region, a European vendor training on your data, Google on top through Vertex AI only.
The Skills & MCP ecosystem: where to find, where it moves, how to evaluate
Step 9/9 of the Skills & MCP learning path. The annotated map of sources, the method to build a watch that lasts, and the checklist to evaluate a third-party building block before adoption. The path closes on its synthesis quiz.
Using an existing MCP server: plug in without getting burned
Step 6/9 of the Skills & MCP learning path. The four-step plug-in ritual: choose, inspect, configure, test. Reading a tool list like a permission list, understanding the configuration line by line, and settling local vs remote.
MCP: the protocol explained, without the fog
Step 5/9 of the Skills & MCP learning path. The problem MCP solves (M×N → M+N), the host-client-server architecture, the three primitives tools / resources / prompts, and the full sequence of a tool call, numbered, diagram included.
Skills in the enterprise: the governance that prevents the worst
Step 4/9 of the Skills & MCP learning path. Who writes, who validates, who maintains, the full life cycle of a skill library, the threat model of the malicious skill, the pre-adoption audit checklist, and the AI Act Article 4 bridge.
Create your first skill: the five-step method
Step 3/9 of the Skills & MCP learning path. The complete method for writing a skill that triggers and holds up: scoping, description, instructions, testing, iteration, with the full SKILL.md of our connecting thread as a deliverable.
Anatomy of a skill: the SKILL.md dissected
Step 2/9 of the Skills & MCP learning path. A SKILL.md file dissected line by line: the frontmatter, the trigger description, the instruction body, the bundled scripts. Why 20 well-structured lines can be worth three weeks of development.
Building your first AI agent: from a repetitive task to production in one day
An agent is a 40-line loop around a model and three tools. What makes it useful is everything else: the right task, a clear job description, guardrails before intelligence, and five real cases to decide whether it ships. Complete guide, from choosing the task to going live.
LLM cost optimization: the 10 levers, from mental model to code
Your AI bill is exploding because you pay for tokens nobody reads. This guide gives you the mental model, the 10 levers grouped by family, a 30-60-90 day battle plan for the CIO, and the Python code for each lever.
AI Agent Drift: Why Your Agent Works in a Demo but Breaks in Production
A flawless agent in a demo can fall apart the moment it meets the real world. Here's what drift is, why it happens, how to detect it, and above all how to prevent it upstream.
Persistent Memory: Why Your AI Assistant Forgets You : and How to Fix It
By default, an AI forgets everything from one session to the next. Here's why, how a real three-layer memory works, why RAG isn't enough, and how to give an agent persistent memory, without neglecting GDPR.
AI Agents in Enterprise: What ANSSI's April 2026 Warning Actually Says
CERT-FR advises against AI agents in production. Decoding bulletin CERTFR-2026-ACT-016, 5 technical risks, 3 workstreams, 5-day checklist.
Agentic systems with Claude: architecture and theory explained
Understand how Claude orchestrates multiple agents that collaborate. Orchestrator-worker pattern, nO loop, inter-agent communication. No jargon.
Choosing your AI API in 2026: OpenAI vs Anthropic vs Mistral vs Google
OpenAI, Anthropic, Mistral, Google, DeepSeek... 5 major APIs, prices varying 50×, very different strengths. Decoding which provider to choose based on your use case, budget, and constraints. Practical decision matrix.
MCP (Model Context Protocol): the standard that finally connects AI to your tools
The Model Context Protocol is the USB-C of AI. One standard to connect Claude, ChatGPT, Gemini to your 50 tools (Slack, GitHub, Notion, Drive...) without coding 50 integrations. Adopted by Anthropic, OpenAI, Google in 2026. Why it's the silent revolution.
Chinese AI (DeepSeek, Qwen, Kimi): should we be wary in 2026?
DeepSeek R1 beat OpenAI at 50x cheaper. Qwen is the #1 open-source model on Hugging Face. But censorship, data sent to China, regulatory risks: complete unbiased analysis.
Shadow AI: the invisible danger in business
78% of your employees use personal ChatGPT at work. Your data may be going to OpenAI without you knowing. We explain the phenomenon, real incidents, and 30-day remediation plan.
Securing your business against AI risks in 2026
67% of businesses had an AI incident in 2026. Average cost €4.9M. We explain the 4 risk vectors, frameworks (SAIF, OWASP), AI Act, and 90-day action plan for CISOs/managers.
GEO: the new SEO in the AI era (Google AI Overviews)
Google AI Overviews dropped organic CTR from 28% to 17%. GEO (Generative Engine Optimization) is the new discipline to stay visible. We explain the 5 pillars and the 90-day action plan.
Vibe coding: coding with AI in 2026 (Cursor, Claude Code)
Vibe coding is the new way of coding where you dialogue with AI. We explain how Cursor, Claude Code, Copilot and Windsurf radically change the dev job. 2-5x productivity, but not magic.
Understanding AI hallucinations
Why does ChatGPT invent references? Why did Bard make Google lose $100 billion? We explain how AI hallucinations work, how to detect and avoid them.
Open source vs proprietary: which LLM to choose?
Mistral, Llama, DeepSeek vs GPT, Claude, Gemini: open or closed? We help you decide based on your volume, GDPR constraints and real budget (with TCO calculation).
Advanced16 articles
Master advanced technical concepts
CCA-F Domain 5 : Context Management & Reliability (15%): the complete lesson
The reliability domain: what consumes the context window and how to budget it, compaction and structured summaries, persistent memory across sessions, graceful degradation (timeouts, fallbacks, partial results), error propagation between agents, source attribution and normalization of heterogeneous formats. Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 4 : Prompt Engineering & Structured Output (20%): the complete lesson
The prompt domain: explicit criteria over vague instructions, few-shot with reasoning, structured output via tool_use and JSON schema, nullable fields against hallucination, validate-and-retry, extended thinking, Batch API (-50%, 24h, custom_id) and multi-instance review. Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 3 : Claude Code Configuration & Workflows (20%): the complete lesson
The most factual domain of the certification: the CLAUDE.md hierarchy, @import, glob-scoped .claude/rules/, commands vs skills (context: fork, allowed-tools, argument-hint), plan mode vs direct execution, iterative refinement, and Claude Code in CI/CD (-p, --output-format json, --json-schema). Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 2 : Tool Design & MCP Integration (18%): the complete lesson
The tools domain: how an agent picks the right tool, why it gets it wrong, how a tool should fail, how many tools to give whom, tool_choice, MCP server configuration and Claude Code's built-in tools. Diagrams, traps, night-before checklist and corrected scenario questions.
CCA-F Domain 1 : Agentic Architecture & Orchestration (27%): the complete lesson
The heaviest domain of the Claude Certified Architect exam, broken down point by point: the agentic loop, hub-and-spoke, subagents, programmatic guardrails, hooks, task decomposition and sessions. With diagrams, traps, a night-before checklist and corrected scenario questions.
Securing your MCP servers: the attack surface and the countermeasures
Step 8/9 of the Skills & MCP learning path. The full attack surface of a tool-equipped agent, indirect injection, confused deputy, exfiltration by chaining, and the defense in depth that neutralizes it, from least privilege to supervision. The step your CISOs will read first.
Build your minimal MCP server: the loop closes
Step 7/9 of the Skills & MCP learning path. The two tools of our connecting thread in line-by-line annotated Python: server structure, trigger docstrings, write guardrails, errors designed for the model, and the skill + MCP loop finally complete.
RAG in production: architecture, pipeline and governance
A demo RAG fits in 40 lines. A production RAG is five stages, three cross-cutting layers, and a decision you must make before writing code. Complete guide: decision tree, reference architecture, Python code per stage, continuous evaluation, multi-tenant governance and security.
Passing the Claude Certified Architect (CCA-F): The Complete Guide
The reference guide to earning Anthropic's first official technical certification: the 5 weighted domains, the exact format, SVG schemas, worked sample questions, the traps, a study plan, the free official courses, and a full AI/Claude glossary.
Building a multi-agent system with Claude: practical guide (SDK + MCP)
Complete tutorial to deploy Claude agents that collaborate. Comparison Agent SDK vs API + MCP. Python code, real case, production deployment.
Multi-agent systems: AI agent teams for pros (2026 architecture)
Multi-agent systems are the #1 pro topic of 2026. 4 orchestration patterns, frameworks (LangGraph, CrewAI, AutoGen), 5 fatal mistakes, 4-week roadmap.
Securing an AI project end-to-end: complete 2026 framework
Complete framework to secure your AI in 2026: 5 layers, STRIDE-AI model, 60-point checklist, 90-day program, tooling stack, AI Act/ISO 42001 compliance.
AI red-teaming: attack your own LLMs before others do
Complete 2026 methodology: MITRE ATLAS framework, 6 attack categories, monthly cadence, tools (Garak, PyRIT), AI Act compliance.
Prompt injection: the critical LLM flaw in 2026
Ranked #1 OWASP Top 10 LLM for 3 consecutive years. LLMs cannot distinguish instructions from data, the fundamental flaw. Real cases, 8 attack vectors, defense-in-depth.
AI Agents: the next revolution
Claude Computer Use, OpenAI Operator, Devin... AI agents act in the world, not just answer. We explain how they work, the top 2026 frameworks and the real risks.
RAG explained simply
RAG is the technique that connects an LLM to your documents for grounded, hallucination-free answers. We explain the mechanism, technical stack and optimizations that make a difference.