As it gets cheaper to build more and better features, businesses will face stiffer competition to deliver superior products. This will create work for SWEs to implement those features.
My coding work has already shifted heavily away from writing code first drafts and toward importing, tweaking, debugging, polishing and integrating LLM outputs.
Because I’m more productive, my build-test-refine cycle shortens, so I wind up putting more attention into thinking about business objectives.
Other SWEs may gravitate toward questions like “how do I build a plugin-based pipeline to integrate software A B and C, and hardware X Y and Z, using LLM outputs to control the pipeline?” And there are all kinds of interesting technical issues there for SWEs to solve.
Companies will increasingly focus on continuously importing their data into formats compatible with LLMs—everything from emails, to office layouts, to employee personalities and skill assessments, making it all searchable and interpretable. Despite this, there will always be a bleeding edge of data that hasn’t been integrated into the system (which right now is just the familiar everyday knowledge we have rattling around in our heads, or in our inboxes), and that data-edge will be a thing that individual people define their job roles around. What exactly that is, of course, will be in continuous flux.
I think that in general, people who work in tech will be OK as long as they’re keeping up with the new LLM-based tools and ways of working.
Here’s how I’m tentatively thinking about it:
As it gets cheaper to build more and better features, businesses will face stiffer competition to deliver superior products. This will create work for SWEs to implement those features.
My coding work has already shifted heavily away from writing code first drafts and toward importing, tweaking, debugging, polishing and integrating LLM outputs.
Because I’m more productive, my build-test-refine cycle shortens, so I wind up putting more attention into thinking about business objectives.
Other SWEs may gravitate toward questions like “how do I build a plugin-based pipeline to integrate software A B and C, and hardware X Y and Z, using LLM outputs to control the pipeline?” And there are all kinds of interesting technical issues there for SWEs to solve.
Companies will increasingly focus on continuously importing their data into formats compatible with LLMs—everything from emails, to office layouts, to employee personalities and skill assessments, making it all searchable and interpretable. Despite this, there will always be a bleeding edge of data that hasn’t been integrated into the system (which right now is just the familiar everyday knowledge we have rattling around in our heads, or in our inboxes), and that data-edge will be a thing that individual people define their job roles around. What exactly that is, of course, will be in continuous flux.
I think that in general, people who work in tech will be OK as long as they’re keeping up with the new LLM-based tools and ways of working.