Kubernetes 1.33 was released today.
There's no buzzier technology right now than ChatGPT and for good reason. Because while the hype over how blockchain was going to transform trust, financial systems and even the business of selling art has yet to materialize, ChatGPT and, more broadly, generative AI are already delivering real value. In fact, ChatGPT is already so powerful, there are many who worry that generative AI will ultimately replace creative and information workers.
ChatGPT is not yet ready to produce code unsupervised
When it comes to software development, I personally believe that there will always be a need for talented human tech practitioners who are able to solve difficult, complex problems. But whatever your beliefs on that matter, the fact is, ChatGPT is not yet ready to produce code unsupervised, and doesn't take much time working with it to see why. Ask it enough complex questions, and while you'll always get something that sounds good, do a bit of digging and you may discover that it has completely invented some of what it says and may have even manufactured non-existent references. That said, in my experience, the code it produces can be helpful. In fact, in the hands of a seasoned developer, ChatGPT can be a very powerful tool.
Developer Use Cases for ChatGPT
ChatGPT can significantly increase the speed of development and the time it takes to create a solution … so long as it's used properly. As I noted above, it's not safe to use the code it generates without checking it first, which is why it's important that developers hone their instincts for what looks like well-formed code and what doesn't.
We've all pulled code from forums and sites like Stack Overflow, and no responsible developer would use that kind of code sight unseen. Treat code from ChatGPT in the same way. After all, it's likely the AI lifted the code from a site just like Stack Overflow and, perhaps, modified it a bit.
But even though it needs to be checked, the code ChatGPT generates is great for producing a framework on which to build. Note, however, that ChatGPT is best at creating code for specific, relatively simple tasks that are frequently repetitive. I often use it, for example, to create code for software testing and data connectors between applications. The more unique or complicated the task is, though, the more likely ChatGPT will produce flawed code.
ChatGPT is also an excellent tool for training developers and building knowledge. Hazy on how to create a higher-order function in Typescript? Fire up ChatGPT and type, "Explain the concept of higher-order functions in Typescript and provide three examples."
You're an expert with Ruby, but just getting your feet wet in Python? Type "Explain how to form class objects in Python and provide several examples."
Finally, ChatGPT is great at creating documentation, a task that most developers truly dislike doing. Again, you don't want to use ChatGPT to document complex, unique code, but for simple, straightforward code such as the expected outputs and inputs for a connector, the AI does a good job. You'll want to read through and edit it, of course, but that's much faster than creating the documentation from scratch. As a result, developers can spend more time doing what they truly love: building.
ChatGPT Best Practices
ChatGPT is a new tool in the developer's repertoire, but already, best practices are emerging.
■ Understand what an accurate answer will look like: ChatGPT is not a great tool in the hands of a programmer who's still wet behind the ears, because you need to have a clear understanding of what the code should look like so you'll know right away if anything is out of whack. Without this understanding, there's no way to use ChatGPT efficiently and safely.
■ Create prompts that are very specific, especially about the context of your query: Context is very important when you ask ChatGPT to provide code. Also, don't forget that you can specify in what format you want it to produce information. You don't have to settle for a wall of text and a snippet of code. For example, you might say, "I'm using React as my language, and as a programming assistant, I need to connect an AWS-hosted Postgres database to another application. Provide a connection string that substitutes any connection parameters with a curly brace. If I need more, I'll provide follow-up questions."
■ Never share identifying or proprietary information: Researchers can read your input and use it to further train the AI, which means there's a possibility that any code or information you give ChatGPT could show up as output for someone else at some point in the future. The ChatGPT FAQ is clear on this. If you're using the API, the terms say that your input won't be used in training — even so, it's best to err on the side of caution.
There's little doubt that ChatGPT and other forms of generative AI are going to change how developers work, and it's only going to get better over time. Smart, experienced developers should begin now learning how to use these tools to generate frameworks, improve their knowledge, and become more efficient. The future is here — we'd all best prepare.
Industry News
Docker announced a major expansion of its AI initiative with the upcoming Docker MCP Catalog and Docker MCP Toolkit.
Perforce Software announced the release of its latest platform update for Puppet Enterprise Advanced, designed to streamline DevSecOps practices and fortify enterprise security postures.
Azul announced JVM Inventory, a new feature of Azul Intelligence Cloud designed to address the complexity and risk of migrating off Oracle Java.
LaunchDarkly announced the acquisition of Highlight, a powerful, open source, full-stack application monitoring platform known for its error monitoring, logging, distributed tracing and session replay capabilities.
O’Reilly announced AI Codecon—a groundbreaking virtual conference series dedicated to exploring the rapidly evolving world of AI-assisted software development.
Veracode unveiled new capabilities offering proactive risk mitigation and automated security at enterprise scale.
Snyk launched Snyk API & Web, delivering a dynamic application security testing (DAST) solution designed to meet the growing demands of modern and increasingly AI-powered software development.
Check Point® Software Technologies Ltd. announced that it has ranked as a Leader and the only Outperformer for its Check Point Quantum Security Solutions in GigaOm’s latest Radar for Enterprise Firewall report.
Postman announced new releases designed to help organizations build APIs faster, more securely, and with less friction.
SnapLogic announced AgentCreator 3.0, an evolution in agentic AI technology that eliminates the complexity of enterprise AI adoption.
GitLab announced the general availability of GitLab Duo with Amazon Q.
Perforce Software and Liquibase announced a strategic partnership to enhance secure and compliant database change management for DevOps teams.
Spacelift announced the launch of Saturnhead AI — an enterprise-grade AI assistant that slashes DevOps troubleshooting time by transforming complex infrastructure logs into clear, actionable explanations.
CodeSecure and FOSSA announced a strategic partnership and native product integration that enables organizations to eliminate security blindspots associated with both third party and open source code.