I do not want to game the system, I hate the idea of gaming the system. I just want to be nice, and I think that is precisely the reason why I'm not very rich.
Next time you build a large build try asking the LLM to make it as an AFK build and tell it that you need it to do everything in it's power to complete the build without your intervention. It's going to need a few tiers of tests from unit to smoke and screen tests. Now, I'm not saying this is easy to do. It requires an insane amount of up front thinking BUT if you (for the heck of it) want to make an overnight build this is one way.
FWIW While I have had created and run this kind of build a few times... I did not like the results! In the end, I personally like to be in the loop to test and feel how stuff is turning out as it goes.
They will come with corrective SSD and Ram that will enable stale models to get some amount of self correction. Then after that it will be a typical upgrade path. Actually a nice business model with upgrades built in.
Yes but we're talking about the fullness of time as things play out. Much improvements will be made to OS models via distillation and then you also get 15k sec to make it think better.
Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second?
OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins.
With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
I feel bad saying this because so many folks have not had the best of luck, but it's changed the game for me.
I'm building out large multi-repo features in a 60 repo microservice system for my day job. The AI is very good at exploring all the repos and creating plans that cut across them to build the new feature or service. I've built out legacy features and also completely new web systems, and also done refactoring. Most things I make involve 6-8 repos. Everything goes through code review and QA. Code being created is not slop. High quality code and passes reviews as such. Any pushback I get goes back in to the docs and next time round those mistakes aren't made.
I did a demo of how I work in AI to the dev team at Math Academy who were complete skeptics before the call 2 hours later they were converts.
One thing you could look into is body doubling sites like flow club. It doesn't solve the core issue but might help in a small way outside of work hours. Outside of the internet I keep hearing that Pickleball is the most social sport around! Also have you tried hanging out and working at Starbucks (or similar) after some time (weeks) in the same place it's inevitable to start making connections. Also co-working spaces can offer connections, and they usually have various club goings on on notes on the pin boards etc. One thing I do know is that it takes quite a few times / weeks of time turning up to the same place for conversation to start. Hope this is helpful in some way.
Hmm. TIL: The real exposure isn't Anthropic, OpenIA claiming your code, it's you unknowingly distributing someone else's GPL code because the model silently reproduced it, with essentially zero recourse for the model owner.
> Any idiot can now prompt their way to the same software.
It may look the same, but it isn't the same.
In fact if you took the time to truly learn how to do pure agentic coding (not vibe coding) you would realize as a principal engineer you have an advantage over engineers with less experience.
The more war stories, the more generalist experience, the more you can help shape the llm to make really good code and while retaining control of every line.
This is an unprecedented opportunity for experienced devs to use their hard won experience to level themselves up to the equivalence of a full team of google devs.