Every developer knows the pain of losing momentum. Constantly switching contexts, reading endless documentation, and setting up frameworks can stifle creativity and slow progress. Google’s latest updates to the Agent Development Kit (ADK) and the Gemini CLI aim to solve this, helping you move seamlessly from idea to working AI agent with minimal friction.
The llms-full.txt Advantage
The new, streamlined llms-full.txt file is now more than 50% shorter, it distills the entire ADK framework, components, functions, and best practices, into a concise format. This is especially valuable when working with large language models (LLMs), as it:
- Saves context window space: Fit more of your conversation within the LLM’s memory for smoother interactions.
- Boosts code accuracy: Gemini CLI is equipped to generate idiomatic, correct ADK code without extensive prompting.
- Speeds up prototyping: Spend less time on boilerplate and more time iterating on your ideas.
From Idea to Working Agent in Minutes
To showcase this frictionless workflow, imagine building an AI agent that labels GitHub issues automatically. Here’s how ADK and Gemini CLI keep you in the coding zone:
Step 0: Download the Essentials
Start by grabbing llms-full.txt from the ADK repository and placing it in your project directory so Gemini CLI has everything it needs.
Step 1: Brainstorm and Plan
Gemini CLI acts as your AI collaborator. Share your goal, like applying labels to GitHub issues, and let Gemini map out a step-by-step plan, from project setup to authentication, tool creation, agent logic, and building a CLI interface.
Step 2: Instantly Generate Agent Code
Prompt Gemini CLI to turn the plan into Python code using ADK. Instantly, you get:
- An Agent set up for your labeling tasks
- Custom tools for interacting with the GitHub API fetching issues, listing labels, and applying them
- A CLI entry point to run your agent
With core logic generated for you, there’s no need to wrestle with repetitive code.
Steps 3 & 4: Test, Iterate, and Refine
Testing your agent is straightforward. When tweaks are needed, like adding a new label or refining outputs, just ask Gemini CLI. It remembers your context and adapts the code, letting you stay focused and productive.
Step 5: Embrace the New Iterative Loop
- Ideate your agent’s behavior naturally
- Generate code in seconds
- Test and review results instantly
- Improve via conversational tweaks
This cycle repeats as needed, letting you rapidly evolve your agents without breaking your flow.
Key Takeaway: Build Without Breaking Momentum
With the ADK’s lean llms-full.txt and the conversational Gemini CLI, agent development becomes fast, intuitive, and continuous. Developers can focus on solving real problems, not struggling with frameworks or context loss. It’s a smarter, faster way to bring your AI ideas to life.
Source: Google Developers Blog
Stay in the Zone: How ADK and Gemini CLI transform Agent Development