Well, I’d be spending that work on a re-usable platform / framework. So if the argument is “it’s as much work as doing the work yourself anyway,” then I think it may be worth it.
Same argument we had for building the SQL engine. It’s a lot of work upfront but maybe we can benefit from its functionality for long after that.
I wouldn’t be building a project-scoped work harness. I’d be building a work harness for projects.
Edit: downvote me all you want. The comparison to the SQL engine was a good one.
It’s about increasing the baseline of readily-available information, boiler-plate, test data, POCs… between the times (T1) that I have an idea and (T2) that I’m ready to start working on that idea. It’s not about having the agent do the work. Not at all. That’s a static benefit which is created once then reused countless times for the foreseeable future — like SQL.
You want me to write an entire library for a brand new sensor that just came off the market, by parsing through and reading a hundred page datasheet manual, understanding i2c or SPI communication timings, configuration packets, etc…
When I can just drag and drop the PDF into ChatGPT and say “make a library for this sensor” and it spits out something that has been working without issue for the past 2 years?
I hear crazy claims like this but haven’t seen anything close to this with my own eyes (yet).
I shudder at the idea that SPI or i2c are considered complex for someone supposed to interact with hardware. What will you do if a problem arises and you don’t even know which pin does what?
I2C/SPI - and indeed most hardware interfaces - are of course trivial to anyone skilled in the art. Digging through badly written vendor documentation though, then comparing it with the reference implementation that was buried on a website behind a sign that says “beware of the leopard” and which directly contradicts the documentation on various key points, is a non-trivial and ultimately unproductive use of time - and AI tools can be pretty good at that shit.
Generative AIs are a useful tool. Most of the criticisms of AI vendors are also valid (apart from the water one, that’s just bullshit,) but that doesn’t stop them being a useful tool - and engineers who learn to use them as a tool will be more productive and will be more employable than those who stick their fingers in their ears and insist on only producing artisinal code hand-whittled with their grandfather’s tools.
If you spend that much effort, you might just do it without AI. Same amount of work, and you know it’s not going to have non-deterministic behavior.
Well, I’d be spending that work on a re-usable platform / framework. So if the argument is “it’s as much work as doing the work yourself anyway,” then I think it may be worth it.
Same argument we had for building the SQL engine. It’s a lot of work upfront but maybe we can benefit from its functionality for long after that.
I wouldn’t be building a project-scoped work harness. I’d be building a work harness for projects.
Edit: downvote me all you want. The comparison to the SQL engine was a good one.
It’s about increasing the baseline of readily-available information, boiler-plate, test data, POCs… between the times (T1) that I have an idea and (T2) that I’m ready to start working on that idea. It’s not about having the agent do the work. Not at all. That’s a static benefit which is created once then reused countless times for the foreseeable future — like SQL.
You want me to write an entire library for a brand new sensor that just came off the market, by parsing through and reading a hundred page datasheet manual, understanding i2c or SPI communication timings, configuration packets, etc…
When I can just drag and drop the PDF into ChatGPT and say “make a library for this sensor” and it spits out something that has been working without issue for the past 2 years?
Why? Why would I be that stupid?
I hear crazy claims like this but haven’t seen anything close to this with my own eyes (yet).
I shudder at the idea that SPI or i2c are considered complex for someone supposed to interact with hardware. What will you do if a problem arises and you don’t even know which pin does what?
I2C/SPI - and indeed most hardware interfaces - are of course trivial to anyone skilled in the art. Digging through badly written vendor documentation though, then comparing it with the reference implementation that was buried on a website behind a sign that says “beware of the leopard” and which directly contradicts the documentation on various key points, is a non-trivial and ultimately unproductive use of time - and AI tools can be pretty good at that shit.
Generative AIs are a useful tool. Most of the criticisms of AI vendors are also valid (apart from the water one, that’s just bullshit,) but that doesn’t stop them being a useful tool - and engineers who learn to use them as a tool will be more productive and will be more employable than those who stick their fingers in their ears and insist on only producing artisinal code hand-whittled with their grandfather’s tools.