# Avi Levi — AI, Development & Productivity Blog

> Hebrew-first blog by Avi Levi (אבי לוי) covering AI/LLM integration in the workplace, modern software development with AI tools, organizational learning, and productivity. Primary language: Hebrew (he). English articles available under /en/.

## About

Avi Levi is an Israeli practitioner focused on integrating AI into organizational workflows. The blog documents hands-on experience with LLMs, AI agents, no-code tools, and modern development practices (Vibe Coding, Claude Code). Target audience: professionals, managers, L&D practitioners, and developers adopting AI in their daily work.

- Author: Avi Levi
- Languages: Hebrew (primary), English
- Topics: AI/LLMs, Agentic workflows, Organizational learning, Productivity, Software development, Claude Code
- Site: https://avilevi.co.il
- Contact: /contact

## Blog — Hebrew Articles

- [מה זה Agentic Engineering ואיך בונים סוכני AI אוטונומיים](/blog/agentic-engineering-autonomous-ai-agents): Agentic Engineering explained through the practical harness around autonomous AI agents — context, tools, memory, permissions, orchestration, observability, and a comparison of Claude Code Agents, OpenClaw, and Hermes.
- [מהם סקילים בעבודה עם סוכני AI](/blog/ai-skills-guide): A beginner's guide to AI agent "skills" — what a skill is, the four core concepts (prompt, context, skill, agent), the six questions a good skill answers, how to structure skills in a project (SKILL.md / references / scripts), a worked meeting-summary example, a build checklist, and common mistakes.
- [ניהול חלון הקשר ב-Claude Code](/blog/manage-claude-code-context-window): Context window management in Claude Code — why tokens burn before you type a word, and 6 principles for a lean context: short CLAUDE.md, right model per task, project-scoped settings/skills/MCP, and specific prompts.
- [מה זה API בבינה מלאכותית ולמה זה כל כך חשוב?](/blog/ai-agents-using-api): What is an API in AI and why does it matter? A practical guide with examples, tools and tips — from GPT to AI agents that work like employees.
- [רק 5% מהחברות מצליחות לייצר טרנספורמציה באמצעות AI](/blog/ai-implementation-challenges): MIT research shows only 5% of AI initiatives deliver business value. Why organizations fail and what they can do differently.
- [האם בינה מלאכותית משפיעה על האושר שלנו בעבודה?](/blog/ai-workplace-happiness): Harvard Business School research: using AI not only improves efficiency but also increases workplace happiness and reduces anxiety.
- [מה ההבדל בין Automation Workflow ל-Agentic Workflow](/blog/automation-workflow-vs-agentic-workflow): Breaking down the differences between classic automation and intelligent agents, with real n8n examples.
- [שרשרת המחשבה (CoT) — השיטה שמשמשת מודלי Reasoning](/blog/chain-of-thought): Chain-of-thought prompting explained — the technique powering reasoning models.
- [Claude Code — איך לבנות צוות סוכני AI שעובד בשבילכם](/blog/claude-codeubagents): Claude Code and subagents — how to build an automated AI team that manages content across social networks.
- [איך לחבר את Claude עם MCP ולתת לו לסדר את הקבצים](/blog/claude-mcp-file-organization): Practical guide to connecting Claude with MCP to your local file system.
- [AI FOMO — איך מתמודדים ולא נשארים מאחור](/blog/dealing-with-ai-fomo): Strategies for dealing with AI fear-of-missing-out without getting overwhelmed.
- [Disposable Apps — בונים פתרון אישי תוך 10 דקות](/blog/disposable-apps): Building personal digital solutions in minutes using AI — the era of one-off throwaway apps.
- [מה הם Tokens ואיך הם משפיעים על מודלי שפה](/blog/how-tokens-affect-llms): Understanding tokens, context windows, and how to work with LLMs efficiently.
- [מה זה MCP ואיך זה משנה את הדרך שבה אנחנו משתמשים ב-AI](/blog/mcp-ai-protocol): Model Context Protocol — the new standard enabling AI agents to access tools, files, and external systems.
- [קבצי Markdown ו-Context Engineering בעבודה עם סוכני AI](/blog/markdown-yaml-ai-agents): How Markdown and YAML files serve as context engineering foundations for AI agents.
- [מיקור חוץ למוח — Second Brain](/blog/outsourcing_your_second_brain): Outsourcing cognitive load using the Second Brain methodology.
- [שיחות משוב והערכה הן לא ״מטלה ניהולית״](/blog/performance-review): Performance reviews as a tool for connection, growth, and team engagement.
- [מה זה PRD ולמה הוא חשוב בעידן של סוכני AI](/blog/prd-in-the-age-of-ai-agents): Product requirements documents as context engineering for AI agents.
- [RICE Framework — הפרומפט שיתן לכם תוצאות מדויקות](/blog/prompt_frameworks): RICE prompt framework for getting accurate, specific results from language models.
- [מה זה RAG Chatbot ואיך זה משפר את חווית המשתמש](/blog/rag-chatbot): Retrieval-Augmented Generation explained — combining LLMs with data repositories.
- [הסקילסט החדש שכל מי שעובד עם AI חייב לפתח](/blog/the-new-ai-skillset): The three core skills everyone working with AI must develop — explanation, systems thinking, product mindset.
- [בינה מלאכותית בניתוח נתונים של תהליכי למידה](/blog/using-genai-for-learning-analysis): Using AI for learning analytics and L&D data analysis.
- [AI בכלי עבודה — כיצד ארגונים מיישמים בפועל](/blog/ai_in_ld): How organizations are actually implementing AI in learning and development.
- [Claude Notion MCP — חיבור Claude ל-Notion](/blog/claude-notion-mcp): Connecting Claude to Notion via MCP for knowledge management workflows.
- [Gartner Hype Cycle 2024 — AI](/blog/gartner_hype_cycle): Analysis of the Gartner Hype Cycle and where AI technologies stand.
- [יצירת סימולטור עם Amazon PartyRock](/blog/creating_simulator_with_amazon-partyrock): Building an AI simulator with Amazon PartyRock (no-code).
- [אבטחת סייבר במודלי שפה גדולים](/blog/cyber-security-in-llms): Cybersecurity considerations and vulnerabilities in LLMs.
- [Embedding — הכי חשוב שלא מדברים עליו](/blog/embedding): Vector embeddings explained — the foundational technology behind semantic search and RAG.
- [GPT-4o vs Diffusion Models](/blog/gpt-4o-vs-diffusion): Comparing GPT-4o and diffusion models for image generation tasks.
- [כיצד אנשים באמת משתמשים ב-AI בעבודה ב-2025](/blog/how-people-are-really-using-genai-2025): Research findings on how professionals are actually using generative AI in 2025.
- [בניית אפליקציית סיכום קולי ללא קוד](/blog/how-to-build-a-voice-summary-app-using-nocode-tools): Step-by-step guide to building a voice summary app with no-code AI tools.
- [איך לבחור LMS ולא להשתגע](/blog/how-to-choose-lms-and-stay-alive): Selecting an LMS in the age of AI — criteria and pitfalls.
- [ניתוח פנימי ארגוני עם AI](/blog/internal-organizational-investigation): Using AI for internal organizational investigations and surveys.
- [ניתוח פערי ידע — חלק 1](/blog/knowledge-gap-analysis-part1): Using AI for knowledge gap analysis in organizations.
- [LLM Temperature — מה זה ואיך זה עובד](/blog/llm-temp): Understanding LLM temperature parameter and how it affects model output.
- [LoRA — Fine-tuning מודלים בזול](/blog/lora_modle): LoRA (Low-Rank Adaptation) for efficient model fine-tuning.
- [מה זה PRE-BOARDING ו-Vibe Coding](/blog/pre-boarding-vibe-coding): Pre-boarding onboarding workflows enhanced with Vibe Coding.
- [כלי ניהול פרומפטים](/blog/prompt-manager-tools): Overview of prompt management tools for teams and individuals.
- [למידה קצרה — Short Form Learning](/blog/short-form-learning): Short-form learning content in the age of AI — design and strategy.
- [עתיד מקצועות 2025-2030 — דוח World Economic Forum](/blog/the_future_of_jobs_report_2025_2030): Analysis of the WEF Future of Jobs report 2025-2030.
- [AI לניתוח שימוש בלמידה ארגונית](/blog/ai-job-interview-assistant-no-code): AI-powered job interview assistant built with no-code tools.
- [מה קורה כשמעצב פתרונות למידה נכנס לכיתה?](/blog/digital-learning-course-hit): Insights from teaching a digital learning design course at HIT — combining learning design triangles, AI, and sensing checks.
- [מה ההבדל בין למידה מונחית לבלתי מונחית בלמידת מכונה](/blog/supervised-vs-unsupervised-learning): Supervised vs Unsupervised Learning — two core approaches in machine learning, when each fits, and how they produce different insights.
- [Vibe Coding — לבנות אפליקציה בשיחה עם AI](/blog/vibe-coding): How to build apps without writing code using Replit, Claude, and Lovable — a step-by-step guide with tool comparisons.
- [איך יוצרים וידאו בקוד עם Remotion](/blog/vibe-coding-to-video-with-remotion): Creating professional video and animations with React code — how to turn React components into video using Claude Code and Remotion.
- [What Is Reinforcement Learning — הדרך לאלף AI](/blog/what-is-reinforcement-learning): Reinforcement Learning explained — how AI agents learn through reward and punishment, analogous to training a dog, with real-world applications.
- [מה אפשר ללמוד על למידה של בני אדם מלמידת מכונה?](/blog/what_can_we_learned_about_human_learning_from_machine_earning): What machine learning principles can teach us about human learning — insights on contextual learning, feedback loops, and knowledge transfer.
- [איך AI לומד? Zero-shot ו-Few-shot Learning](/blog/zero-and-few-shot-learning): Zero-Shot and Few-Shot Learning explained — how AI models perform complex tasks with no or minimal examples, and practical applications.

## Projects

- [View all projects](/projects)

## Tools

- [Skill Builder](/tools/skill-builder): Guided Claude Agent Skill builder with SKILL.md preview, validation, ZIP export, and admin-reviewed publishing.
- [Skill Store](/tools/skills): Curated public store of approved Agent Skills created through the builder.

## English Content

English articles and translated content are available at:
- [English blog archive](/en/blog)
- [What Is Agentic Engineering and How Do You Build Autonomous AI Agents](/en/blog/agentic-engineering-autonomous-ai-agents): English version of the autonomous agents article, covering agent harnesses, agentic workflows, autonomous-agent requirements, and the Claude Code Agents / OpenClaw / Hermes comparison.
- [English homepage](/en)
- [Proof of Work](/en/proof): Receipts, not slides — decision records, failure logs, and a live AI system doing instructional-design work; the evidence behind Avi Levi's LearnOps toolkit for instructional designers adopting AI.

## Optional

- [Sitemap](/sitemap-index.xml)