An AI code assistant is a tool that uses artificial intelligence to help developers write code faster. It does this either by generating code based on input prompts from the developer or suggesting code for auto-completion as you write code in real time. So you may ask, what can AI code assistants do:
- Integrate with your existing code editors.
- It can generate complete code snippets from your own input prompts.
- It can detect code errors or bugs.
- It can detect security vulnerabilities with your code.
- It can comment your or it’s own code so it is easy to refer back to later or for the team to understand
- You can ask it to explain a code snippet.
As you can see it is really quite amazing what it can do and that is why a lot of developers are moving towards using these tools. An example of these input prompts can be the following
Can you write me a function in PHP that takes user input called name and save it into a database once submitted.Example of a prompt by a developer
A growing reliance on AI-powered coding assistants is changing how DevOps teams operate. This move towards coding assistants will only grow and can be a dangerous precedent.
AI coding assistants are becoming integral to boosting productivity according to Forrester’s 2024 cybersecurity and privacy predictions, However, a cautionary note accompanies this technological shift, as Forrester warns of potential pitfalls that could lead to cybersecurity breaches. Their three main predictions for 2024 are :
- At least three data breaches will be publicly blamed on AI-generated code.
- An app using ChatGPT will be fined for its handling of PII.
- Ninety percent of data breaches will include a human element.
Forrester predicts that the combination of inconsistent compliance and governance practices, coupled with the simultaneous experimentation of multiple AI-coding assistants by DevOps teams, may result in flawed code. You can read their full report over here
The adoption of AI-coding assistants is already well underway, with 49 percent of business and technology professionals acknowledging their organisations’ adoption.
By 2028, Gartner forecasts that 75 percent of enterprise software engineers will incorporate AI coding assistants into their workflows—a significant leap from the less than 10 percent reported in early 2023.
The pressure to deliver a high volume of code within tight timelines has led to the widespread use of multiple AI-coding assistants across DevOps teams.
This trend has given rise to a new phenomenon termed ‘Shadow IT,’ where teams experiment with different assistants to determine optimal performance for specific tasks.
As the DevOps landscape continues to evolve, the integration of AI-coding assistants offers both unprecedented efficiency and potential risks. Striking the right balance between innovation and cybersecurity will be crucial for organisations.
We have tried multiple of these AI assistance and in short, they are great if you yourself understand the code that it is writing. We found in some of the code examples much more efficient ways of writing certain functions but saying that it is great to get some code going at least and then you can fine tune it to suit your requirements.
As mentioned, we have tried quite a few of them and according to us these are the the ones with a good solid start.
- GitHub Copilot
- Amazon CodeWhisperer
NOTE : There are also different assistants aimed at specific software. An example of that would be our last mention CodeWP which is aimed at WordPress Development specifically. Let us know in the comments which one’s you’ve tried and if you have any other ones we should try.