Скачать или смотреть Give AI Hands: Build Tool-Powered Agents (Python)

Struggling with LLM agents that feel shallow, generic, or unpredictable — even when you give them detailed prompts?

In this ByteBuilder tutorial, we break down the real reason most agents fail: they don’t have capabilities.
Then we show you exactly how to build a tool-enabled agent that can search the web, verify information, and produce trusted answers using Python and OpenAI’s function-calling workflow.

You’ll learn step-by-step how to:
✅ Understand why LLMs alone can’t reason, act, or access real data
✅ Engineer a capability-driven agent using two complementary tools
✅ Build a Web Search Tool powered by Serper (Google Search API)
✅ Build a Fact-Checking Tool using a second LLM pass
✅ Chain tools together to create verified, reliable outputs
✅ Implement a full tool-oriented agent loop in Python

This tutorial is part of the Agent Engineering Series, where we turn vague agent concepts into real, practical, and scalable systems — helping developers build agents that act intentionally and reliably.

🔗 What’s Inside:
We walk through building a full tool pipeline, wiring function-calling correctly, handling tool responses, and creating a multi-step reasoning loop — so your agents stop hallucinating and start using real, verified data.

🧠 About ByteBuilder
ByteBuilder helps developers master Generative AI and LLM engineering through clear, structured, and practical tutorials. Learn how to design, build, and scale real-world AI systems — one concept at a time.

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