AI Assisted Coding First, AI Agents Second | #GoogleCloudNext #AIAgents #Coding #Podcast #Shorts
By The New Stack
Key Concepts:
- AI-assisted coding: Using AI tools like Gemini Code Assist to generate and understand code.
- Agents: AI systems designed to automate specific tasks within a workflow.
- Software Delivery Life Cycle (SDLC): The process of planning, creating, testing, and deploying software.
- Toilsome tasks: Repetitive, manual, and often tedious tasks within the SDLC.
AI-Assisted Coding as a Starting Point
The speaker suggests that for developers new to AI, AI-assisted coding should be prioritized over agents. Tools like Gemini, Gemini Code Assist, and Gemini and Firebase AI Studio are recommended. The process involves providing natural language prompts to the AI and then reviewing and editing the generated code. This approach allows developers to treat the AI as a "pair," asking questions and receiving feedback.
Example: Code Explanation
A specific use case highlighted is using AI to explain unfamiliar codebases. The speaker describes using Gemini to get a quick overview of code when debugging or reviewing someone else's work. This allows for a faster understanding of the code's functionality before diving into detailed debugging.
Agents for Automating Toilsome Tasks
After becoming comfortable with AI-assisted coding, the speaker recommends exploring agents. The focus should be on identifying "toilsome" or difficult tasks within the software delivery life cycle (SDLC) that could be automated. If a suitable agent doesn't already exist, the speaker suggests considering building one.
Prioritization Rationale
The speaker explicitly states, "if you're getting started building AI apps I wouldn't start with agents however if you're getting started using AI as part of your development workflow I would definitely put that agents second." This prioritization is based on the idea that AI-assisted coding provides a more accessible and immediately useful entry point for developers new to AI.
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