You might have opinions about the growing chatter on how ChatGPT will replace us, writers. I don’t think we are there yet, and I still see the existing AI tools as impressive and helpful. Here is a blog post about the existing AI technologies and how to make the best use of them and adapt to the changing landscape.
People who talk about AI replacing writers may talk about many things AI is evil at, but I’m focusing on tasks you can do today and improve your work.
Table of contents
- Create Jira dashboards
- Get help with Git errors and commands
- Ask AI to explain error logs
- Create scripts
- Clear mental blocks
- Use multiple AI tools
- Word of caution
Create Jira dashboards
Introducing AI into your workflow doesn’t mean it can magically create a fully functional dashboard with a single command. However, AI can undoubtedly assist you in creating JQL queries, which are essential components of a Jira dashboard. By leveraging AI tools like ChatGPT, you can streamline the process of creating complex JQL queries and optimize your Jira dashboard to boost productivity.
One way AI can assist you in creating a Jira dashboard query is by generating JQL queries that you can use with a Rich filter controller. Let’s take a look at an example:
Prompt: I need help creating a Jira dashboard query to track open issues assigned to me with different priority levels. Can you assist me with that?
Response: Certainly! Here’s a JQL query you can use for your dashboard:
project = 'YourProjectName' AND assignee = currentUser() AND resolution = Unresolved ORDER BY priority DESC. This query will retrieve all open issues assigned to you, sorted by priority in descending order.
This example shows that providing a specific prompt to ChatGPT generates a JQL query tailored to your requirements. You can customize the query based on your project, user, and other criteria to fit your needs. By using AI tools like ChatGPT to generate JQL queries for your Jira dashboards, you can save time and effort in manually crafting complex queries. The assistance provided by AI technologies can help you focus on the creative aspects of dashboard design and data visualization while leaving query generation to AI-powered tools.
Get help with Git errors and commands
When working with Git, encountering errors and remembering various commands can sometimes be challenging. However, with the help of AI, you can simplify your Git workflow by receiving prompt and accurate guidance on specific Git commands.
Prompt: I’m facing trouble getting a remote branch from GitHub onto my local computer. Could you help me with the appropriate Git command for this?
Response: Certainly! To get a remote branch from GitHub onto your local computer, use the following Git command:
git fetch origin <branch-name> && git checkout -t <branch-name>. This command fetches the branch from the remote repository and creates a local tracking branch.
By leveraging AI’s ability to understand the context and generate appropriate responses, you can confidently execute Git commands and overcome obstacles without extensive manual searching or trial and error. It enables you to focus more on your work and spend less time searching for solutions and deciphering complex commands.
Ask AI to explain error logs
Error logs can be challenging to interpret; fortunately, AI can lend a helping hand by providing explanations for error logs, enabling you to understand better and troubleshoot issues. If required, you can use this tip to understand the error message and write it in your own words, helping you save precious time off from to-fro conversations with engineers.
Prompt: Explain this Kubernetes error message:
'Warning Failed 100s (×4 over 3m6s) kubelet, dali Failed to pull image "imiell/bad-dockerfile-private": rpc error: code = Unknown desc = failed to resolve image "docker.io/imiell/bad-dockerfile-private:latest": no available registry endpoint: pull access denied, repository does not exist or may require authorization: server message: insufficient_scope: authorization failed'
Response: Certainly! The error message you encountered indicates a problem with pulling the image
imiell/bad-dockerfile-privatefrom the ‘docker.io’ registry. The error ‘no available registry endpoint: pull access denied’ suggests that there may be an issue with the accessibility or authorization for the repository. The message ‘insufficient_scope: authorization failed’ implies that the user attempting to access the image may lack the necessary privileges or credentials. To resolve this, you may need to ensure the repository exists, check the authorization settings, and provide appropriate credentials to access the image.
Automation plays a crucial role in streamlining workflows and increasing productivity. AI can be a valuable tool in helping you create scripts to automate repetitive tasks, reducing manual effort and saving time. In addition, AI can assist you in script creation and empower you to learn programming concepts more effectively.
Prompt: I want to create a Git alias that takes user input in the format of a GitHub branch name from a pull request
<author>:<branch-name>and then switches to that branch. Can you help me with the necessary script or steps to accomplish this?
Response: Certainly! To create a Git alias that facilitates switching to a branch using user input in the format of
<author>:<branch-name>, you can follow these steps:
- Open your Git configuration file using the command
git config --global --edit.
- Add the following alias to the [alias] section:
switch-pr = !sh -c 'git fetch origin && git checkout -b $(echo $1 | cut -d \":\" -f 2) origin/$(echo $1 | cut -d \":\" -f 2)' -
- Save and exit the file.
Now, you can use the Git alias by executing
git switch-pr <author>:<branch-name>, which will fetch the branch from the remote repository and switch to it locally.
In this example, AI provides a step-by-step explanation of creating a Git alias to handle user input in the specified format and automate the branch-switching process. As a result, you can create scripts that enhance your workflow and eliminate repetitive manual tasks by leveraging AI’s knowledge and guidance.
With the assistance of AI, you can accelerate your learning process by understanding the necessary steps and commands involved in script creation. Whether new to programming or seeking to expand your scripting abilities, AI can provide valuable insights and support in achieving your automation goals.
Bonus Tip: Ask AI to optimize your existing script. For example, provide your CI configuration file and ask AI how to optimize it to run the test builds faster.
Clear mental blocks
As writers, we sometimes encounter mental blocks that impede our creative flow and make it challenging to create engaging content. AI can serve as a valuable resource to help clear these mental blocks by providing content suggestions and alternative perspectives.
Prompt: Help me rewrite the following sentence in Simplified Technical English: ‘With ABS version 1.1, you can use the web UI to configure compliance policies.’ Also, provide a few more lines I can use to kickstart this section.
Remember that AI only assists, and your expertise as a technical writer remains essential in producing high-quality content.
Use multiple AI tools
ChatGPT isn’t the only one; there are some other good AI tools worth exploring:
- Bing Chat: Unlike ChatGPT, Bing Chat is connected to the internet and can help you by providing the latest information.
- Google Bard: Similar to chatGPT, but also allow you to view other draft responses for your query.
Other than these, many more tools specialize in generating marketing copy, email subject lines, blog articles, and images. Maybe I’ll pick them up in another blog post.
Word of caution
While these tools offer immense value and assistance in various tasks, it’s essential to be aware of specific considerations. Here are a few points to keep in mind:
- Privacy: The tool’s developers will store and analyze the data you provide, including prompts and queries. It’s essential to be mindful of the sensitivity of your information. Avoid sharing any personally identifiable or sensitive data.
- Quality and Bias: AI models like ChatGPT are trained on vast amounts of data and learn patterns from available information. It’s essential to evaluate the outputs and exercise your judgment critically.
- Contextual Understanding: AI tools may not always grasp the full context of a given query or prompt. They operate based on patterns and statistical associations in the data they were trained on. Please don’t rely solely on their output.