Short overview of genAI Coding Assistants

1. Introduction

In today's rapidly evolving tech landscape, AI coding assistants have emerged as game-changing tools for software development teams. These GenAI-powered assistants are not replacements for human developers but powerful amplifiers of their capabilities. This article will guide you through improving your teams productivity by +100%.

As Benjamin Franklin stated, "An investment in knowledge pays the best interest." This guide is designed to help you make that investment in your team's knowledge and skills.

Target Audience

This guide is primarily aimed at:

• Leaders of mid/large developer teams with +15 members
• Teams working with large existing codebases
• Organizations looking to significantly boost productivity and code quality and willing to try Coding Assistants

While the principles outlined here can benefit teams of all sizes, this guide is especially for larger teams. Smaller teams without specialised roles for devops or security will derive even more benefit from these tools but can cut-short the phase wise approach to days instead of weeks.

We will also be updating this article with more examples and experiments as and when we get time to document.

Benefits of GenAI in Software Development

GenAI offers multiple beneficial outcomes for development teams:

1. Reducing technical debt
2. Improving code hygiene and robustness
3. Accelerating bug fixes and feature development
4. Easing integration of new technologies and external products
5. Enhancing security practices
6. Optimizing development environments
7. Streamlining CI/CD processes

With proper training and support, these tools can help regular developers achieve world-class outcomes, rivaling the best in the industry.

2. Understanding GenAI Coding Assistants

Available Tools

The landscape of AI coding assistants is diverse and rapidly evolving. While GitHub Copilot pioneered this space, numerous excellent alternatives have emerged. Some key players include:

• GitHub Copilot
• Tabnine
• SourceGraph Cody
• Codeium
• cursor.sh

Here is a detailed evaluation we conducted a while back: Comparison of different coding assistants

It's worthwhile to periodically re-evaluate these tools based on your specific project needs, as they are evolving rapidly.

Pricing Considerations

The cost of AI coding assistants is relatively nominal considering the benefits they offer. Prices typically range from $9 to $40 per month per user. When weighed against the potential productivity gains, this investment will pay for itself in less than a month.

Here is a limited list of areas where we saw significant benefits from coding assistants.

1. Reducing Technical Debt: AI assistants can help identify and refactor legacy code, improving overall code quality.
2. Improving Code Hygiene: Automating best practices lead to more robust and maintainable code.
3. Accelerating Development: Faster bug fixes and feature implementations through code suggestions and autocompletion.
4. Easing Technology Integration: AI provides very valuable guidance on integrating new technologies or external APIs.
5. Enhancing Security: Suggestions for secure coding and deployment practices. We improved security of ngnix, docker-files, elastic etc.
6. Optimizing Environments: Assistance in configuring development environments and toolchains.
7. Streamlining CI/CD: Help in creating and optimizing CI/CD pipelines.

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