by agenticloops-ai · Agent Tool · ★ 58
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Hands-on tutorials for building AI agents from scratch. Learn LLM APIs, prompt engineering, tool calling, and the agent loop through practical examples.
| Stars | 58 |
| Forks | 10 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 45.35/100 |
| Open Issues | 3 |
| Last Updated | 2026-04-16 |
| Created | 2026-01-25 |
| Platforms | python |
| Est. Tokens | ~350k |
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agentic-ai-engineering is Hands-on tutorials for building AI agents from scratch. Learn LLM APIs, prompt engineering, tool calling, and the agent loop through practical examples.. It is categorized as a Agent Tool with 58 GitHub stars.
agentic-ai-engineering is primarily written in Python. It covers topics such as agentic, agentic-ai, agentic-patterns.
You can find installation instructions and usage details in the agentic-ai-engineering GitHub repository at github.com/agenticloops-ai/agentic-ai-engineering. The project has 58 stars and 10 forks, indicating an active community.
agentic-ai-engineering is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agentic-ai-engineering on Agent Skills Hub include mcp-server, AgenticGoKit, llm-reader. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.