Thoughts on the Future of Software Development

But there are still knife craftsman.

You could become a software craftsman/artist if you enjoy writing software.

What we've seen as we transitioned to higher and higher level languages (e.g., machine code → macro assembly → C → Java → Python) on unimaginably more powerful machines (and clusters of machines) is that we took on more complex applications and got much more work done faster. The complexity we manage shifts from the language and optimizing for machine constraints (speed, memory, etc.) to the application domain and optimizing for broader constraints (profit, user happiness, etc.).

I think LLMs also revive hope that natural languages (e.g., English) are the future of software development (COBOL's dream finally be realized!). But a core problem with that has always been that natural languages are too ambiguous. To the extent we're just writing prompts and the models are the implementers, I suspect we'll come up with more precise "prompt languages". At that point, it's just the next generation of even higher level languages.

So, I think you're right that we'll spend more of our time thinking like product managers. But also more of our time thinking about higher level, hard, technical problems (e.g., how do we use math to build a system that dynamically optimizes itself for whatever metric we care about?). I don't think these are new trends, but continuing (maybe accelerating?) ones.

Doesn't Devin run using GPT-4? And as such, with all generative AI technologies, its performance is subject to the common challenges faced by these systems.

Mainly the transformer model, which is the foundation of GPT-4, is known for its linear scalability. This means that as more computational resources are allocated, its performance improves. However, this scalability is subject to diminishing returns, reaching a point where additional resources yield minimal improvements. This theoretical "intelligence" limit suggests that while continuous advancements are possible, they will eventually plateau.

The future of software development will continue to involve human software engineers until we achieve true Artificial General Intelligence. Regardless of when or if AGI becomes a reality, your skills and expertise in your niche domain will remain valuable assets. While companies may leverage AI-powered software engineering tools to augment their workforce and in effect replace you, you as a skilled professional can do the same.

If you possess a deep understanding of your core domain and a passion for building useful products, you can leverage AI software engineering tools, AI-powered design assistants, and AI-driven marketing solutions to launch new startups more efficiently and with less capital investment, especially in the realm of software-centric businesses.

So, the way I see it, it is the businesses that need to be afraid, if AI becomes capable enough to start replacing their workers, as it will also make it easier for most software engineers and product managers to build competing products in their areas of specialization.

Almost every small business I know has an accountant or book keeper position which is just someone who had no formal education and the role is just managing QuickBooks. I don't think the need for formally educated accountants who can handle large corporate books decreased significantly, but I don't have any numbers to back that up. Just making the comparison to say I don't think the hard / cool stuff that a lot of software developers love doing is going away. But these are just my thoughts.