- On the face of it, you could say a little bit of everything. Checking code, testing it, writing scripts, developing complex cloud services systems, documenting code.
- With AI, it's good to brainstorm ideas and different possible solutions - whether a particular function looks good, how to approach a given problem, what are the possible solutions for the situation at hand.
- The role of AI in this sense is particularly important when working remotely or when there is no technical team around. AI is always ready for an exchange of ideas, and it works at the level of an experienced dev. AI is a very functional virtual rubber duck that responds back.
- AI is also great for learning new things. For example, AI can tell you about a new programming language or framework. By asking follow-up questions, you can learn much faster than if you had to dig into the subject yourself. There is a clear reduction in the need to browse documentation.
- At the heart of coding is that you always have to test and verify, and yes, that's emphasised here too.
- Before AI, there was a lot of use of discussion forums, and yes, you can get really harmful answers there. As I said, finding the right model code, editing it for your own use and verifying it is an essential part of this work, not something that AI will change or remove.
- It was a bit of a threshold at first, it felt like you couldn't get what you wanted out of it. You definitely have to learn how to use it. It takes a few weeks or months, but once you got the hang of it and the benefits, it was revolutionary.
- With AI, you need to get your brain out of the search engine world. AI is more of a conversation partner, and you need to know how to ask the right questions. The more you use it, the more applications you'll find. With AI, you also have to remember that it doesn't know everything about the situation, the problem or the context, but only as much as you tell it. The more you explain and describe the issue in detail, the more you get out of it. AI gives you what you ask it to do, it doesn't directly solve the problem.
- You could say that we are only in the Stone Age of AI, but it is fast becoming the new native interface for people. You could compare this to the development of smartphones.
- In the future, AI will be more and more integrated into the work environment, linked to the organisation's requirements management, architecture, code base and so on. This will allow more to be extracted from it.
- Anonymity must also be kept in mind at all times, confidential information must never be given to it. Hopefully, however, this will change over time, so that models will evolve specifically on a project- and organisation-specific basis, and may even become part of a company's IPR. Those with the most sophisticated AI will improve productivity the most.
- Yes, it definitely speeds things up. For example, things that would have to be done manually, like adding some information to the operating system, can now be done quickly by AI. It used to take hours to develop automation.
- AI can be thought of as a constantly available interlocutor and colleague. With it, you can quickly iterate on problems and solutions and make things clearer to yourself.
- In terms of productivity, it certainly shows. Clearly, less time is spent writing plain old code, and more time and energy is freed up to think about and solve more complex problems. Wasteful brain energy has been eliminated. This also improves quality across the board.
- AI also allows for greater brainstorming in problem solving, as it can be used to explore a number of different options in relative depth with relatively little effort.
