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AI Agents for Everyone

A 6-chapter course for non-technical Israelis: what an AI agent is, how to set one up on Claude / ChatGPT / Gemini without code, and four real Israeli use cases.

By skills-il·Version v1.0.5·Last updated: 02-06-2026·GitHub
6 chapters~32 minNon-technicalBeginner
5.0Reviews (2)
1,411154

What you'll learn

  • Understand the difference between a chatbot and an AI agent, and identify when each fits
  • Set up a first agent on Claude Projects, ChatGPT GPTs, or Gemini Gems without writing code, and know when to step up to Claude Desktop + filesystem MCP for working on a folder of local files
  • Write prompts using the four foundational patterns: role+task+constraints+format, step-by-step thinking, critique mode, persona
  • Build a complete agent for one of four Israeli use cases (accountant, lawyer, marketer, small business owner), including when to upload files and when to switch to Code Interpreter for real arithmetic
  • Run a verify-before-trust protocol to catch hallucinations, stale data, and privacy failures (Privacy Protection Law Amendment 13) before pasting client data
  • Recognize when chat hits its limit and step up to no-code automation (n8n, Make.com, Zapier)

Who this is for

Israeli professionals and small business owners (accountants, lawyers, marketers, freelancers) who want to understand what an AI agent is and how to use one, without needing to write code.

Course curriculum

Click "Start course" to unlock chapters
  1. 1.
    What is an AI agent (in plain language)
    The simplest way to understand the difference between a chatbot and an AI agent is to compare what each one does for the same request.
    ~3 min
  2. 2.
    The three platforms for non-developers
    You have three serious options for setting up an agent without writing code: Claude Projects (Anthropic), ChatGPT GPTs (OpenAI), and Gemini Gems (Google). Each one lets you save a prompt and a set of instructions once, then re-use them in a clean conversation each time. The differences matter for Israeli users and they matter for which kind of task you are doing.
    ~8 min
  3. 3.
    Prompt patterns that turn a chat into an agent
    A chat is what you do when you ask a question. An agent is what you get when you encode a prompt so well that it produces useful work on the first try, every time, on any new input. The difference is the pattern. There are four patterns worth learning; once you know them, you can mix them.
    ~3 min
  4. 4.
    Real Israeli use cases worked end-to-end
    This chapter shows four complete workflows, one per professional role. For each, you get the agent setup (the instructions you save once), the daily use pattern (what you do every time), and what to verify before acting on the output. Treat these as templates to adapt to your specific situation.
    ~6 min
  5. 5.
    When AI agents fail (and what to do)
    AI agents fail in a small number of predictable ways. Knowing these patterns is the difference between an agent that saves you hours and an agent that quietly inserts errors into your work. This chapter names the six most common failure modes for Israeli users specifically (the sixth is a privacy and data-handling failure that matters for any professional handling client data), and gives you a verify-before-trust protocol.
    ~7 min
  6. 6.
    Graduating to no-code automation
    Chat-based agents (Claude Projects, ChatGPT GPTs, Gemini Gems) are excellent for tasks you do when you have ChatGPT open in front of you. They have an obvious limit: they require you to be there, paste the input, copy the output, and move it to the next system. For tasks that should run on their own schedule, pull from your existing tools, and write to your existing tools, you need the next step up: no-code workflow automation.
    ~5 min

Skills to install to act on what you've learned

What's new

  • 1.0.5
    Hebrew style pass for the AI agents course: replaced Anglicized Hebrew terms such as `prompt`, `workflow`, `boilerplate`, `cutoff`, `tradeoff`, `copy`, and "mental model" with more natural Hebrew wording, while keeping product names and actual UI terms intact.(02-06-2026)
  • 1.0.3
    Added a "Companion skills" section at the end of the body with a structured list of recommended skills and their install commands (`npx skills-il add ...`), so the agent can route readers to the right skill in real time. Also corrected the canonical install command for courses from `npx skills add courses/<slug>` to `npx skills-il add skills-il/courses/<slug>` (the old form did not work: wrong binary name and the path did not resolve to a real repo).(26-05-2026)
  • 1.0.4
    Removed `![](*.png)` image references from SKILL.md and SKILL_HE.md in the public repo. The images themselves are still served by the website (frontend/public/courses/<slug>/), but the public source that CLI installers receive is now clean of image refs so they don't see broken image rows in their AI assistant. An image-rich copy of each file is kept in frontend/scripts/sync-courses/sources/ and used for website rendering only.(26-05-2026)

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