Should I apologize for being excited about something I built and use daily and for wanting people to try it, discuss it, critique it? Not sure by the tone of your message.
Read the room. What you "built" is neither exciting, nor something most people want to "try". Why? Because just like other AI boosters, you are still trying to somehow optimise the usage of natural language to make it work. But it will never "work" because the way the stochastic ML system is built, it has a failure built into the system.
Totally agree it's not exciting, even though I am personally excited by it, and I also agree it's not something most people want to try, even though some people do want to try it-- and I found a few of them right here on HN.
Disagree on the bit about it "never going to work" though.
Failure-prone stochastic ML systems produce testable, auditable code... just like failure-prone human brains can produce testable, auditable code. And in fact, in both cases, changes to our process can reduce the amount of failures that slip past testing and audit. Or can reap other rewards. Finding the a better process is what I'm interested in right now.
Don't apologize. Keep writing and trying things. Ignore the haters and non-curious, listen to the (even if salty) interested.
There's a fair amount of talk right now about the value being in the verification layer -- once there's a hard verification loop, the agents can do amazing things without getting (permanently) sidetracked. I think what you're working on is half way there -- in essence, you're probably relying on the LLMs notion of what a spec is and should be to the codebase.
What's not currently solved, and what I think is very interesting is how much automation can be added to the creation of verification. We all would unlock a lot more speed and productivity for even moderate gains on that side.
Should I apologize for being excited about something I built and use daily and for wanting people to try it, discuss it, critique it? Not sure by the tone of your message.
Read the room. What you "built" is neither exciting, nor something most people want to "try". Why? Because just like other AI boosters, you are still trying to somehow optimise the usage of natural language to make it work. But it will never "work" because the way the stochastic ML system is built, it has a failure built into the system.
Totally agree it's not exciting, even though I am personally excited by it, and I also agree it's not something most people want to try, even though some people do want to try it-- and I found a few of them right here on HN.
Disagree on the bit about it "never going to work" though.
Failure-prone stochastic ML systems produce testable, auditable code... just like failure-prone human brains can produce testable, auditable code. And in fact, in both cases, changes to our process can reduce the amount of failures that slip past testing and audit. Or can reap other rewards. Finding the a better process is what I'm interested in right now.
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Don't apologize. Keep writing and trying things. Ignore the haters and non-curious, listen to the (even if salty) interested.
There's a fair amount of talk right now about the value being in the verification layer -- once there's a hard verification loop, the agents can do amazing things without getting (permanently) sidetracked. I think what you're working on is half way there -- in essence, you're probably relying on the LLMs notion of what a spec is and should be to the codebase.
What's not currently solved, and what I think is very interesting is how much automation can be added to the creation of verification. We all would unlock a lot more speed and productivity for even moderate gains on that side.
Totally agree. This is 100% where I want to be focusing my energy next! A lot to learn and explore still, just need to find the time.
No need to apologize, just don’t act surprised when people call you out.
A tried and true content marketing strategy. The 100+ upvotes suggest he's doing something right.