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Can AI Really Code?

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My upcoming novel, Catalyst, is set in a world where AI is a major player in shaping the human future. I did some research into how AI is currently being used in software development and found that it has some amazing capabilities, but also some limitations that are a bit concerning. I'd even go so far as to say that those models are a bit of a hoax. They're impressive, but they don't actually solve anything.

Yes, AI coding assistants like Devin and Copilot are impressive in demos and demo videos. In reality, they're not as powerful as you'd think, but they're great for simple tasks like crafting email parsing functions or authentication flows. However, I ran into some issues when I tried to use it in more complex situations. When I asked the AI to "write a connector from a database to ingest data into Spark," it didn't understand and made mistakes. And that is a pure, simple and so well documented task that every non-coder could do that by simply follow the thousands of examples. This shows that AI still has a lot to learn about complex data pipelines and distributed processing. 

This experience shows something really important. AI can be a great tool for automating parts of software development, but it's not quite ready to completely replace human developers. AI is great at handling simple, repetitive tasks, but it struggles with complexity, ambiguity, or when it needs a lot of domain expertise.

AI Is Not a Replacement

Instead of being afraid of AI, let's use it as a helpful tool to improve what we can do. AI can really help with DevOps practices for MySQL optimization and scaling.

  • Query Optimization: AI can look at how queries are being used and suggest ways to make them more efficient, identifying any issues that might slow things down before they happen.
  • Anomaly detection: Machine learning algorithms can spot when something's not right with how the database is being used, so you can take action before things get worse.
  • Predictive Scaling: AI can predict how much resource you'll need, so you can scale up in advance to keep up with growth and avoid any performance issues.
  • Automated Testing: AI-powered testing frameworks can create and run all the tests you need, so you can be sure your code is up to scratch and save time on manual effort.

Human Have Irreplaceable Expertise

While AI can make some tasks easier, human developers are still needed. Complex system design, creative problem-solving, and the ability to understand and anticipate users' needs are areas where human ingenuity is really important. For example, building a large, complex system that depends on lots of different parts together requires a good understanding of software principles and the ability to spot potential problems or areas that could fail. AI can help with things like generating code snippets or optimizing specific components, but the big picture and overall design still come down to human expertise.

Plus, when we're facing new or complex problems that don't have straightforward solutions, we need to think in creative ways and connect different concepts. When the unexpected happens during development, human developers can use their experience and gut feeling to come up with new solutions or think about the problem in a different way. This ability to think in new ways and come up with creative solutions is something that AI still hasn't been able to match.

Finally, understanding what users need and designing interfaces that are easy to use require empathy and the ability to see things from the user's perspective. While AI can analyze user behavior and offer data-driven insights, it lacks the emotional intelligence to truly grasp the nuances of human interaction and create software that feels natural and enjoyable to use. Human developers can use their own experiences and observations to create interfaces that users will really connect with, and that will make them feel satisfied.

To wrap it up

I'd say that's not something AI can do. A well-tuned model can handle basic tasks like data cleaning, deduplication, and writing simple functions or small add-ons for Chrome, PHP scripts, or even a simple RAG. That's about it. It's not really capable of complex, creative solutions or breakthrough research. AI just doesn't have the same capabilities as humans when it comes to planning out a strategy to achieve a goal in software development. It can't combine multiple software stacks into a new solution. 

As I often say, coding is like writing poetry. The future of software development isn't about AI versus humans. It's about AI working with humans. Embrace what AI can do, make the most of its potential, and keep developing the skills that make you who you are. 

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