another_twist

Amazon simply doesnt have the motivation or the DNA to do groundbreaking innovation especially one thats R&D heavy like machine learning. They are good with distributed systems but are quite bad at almost anything else. We are talking pure software here without the commerce arm.

Wow. Cant you sue for wrongful termination ? I am assuming this was considered and not followed through. What are the legal details here ?

Good to see leaders stand up for what they believe in. Soemtimes I simply do not understand this obsession with controlling the internet by European countries. So ridiculous.

Regulatory capture begins.

I am on the 25 dollar plan and I never even come close to hitting the weekly limit. Still manage to ship quite a bit. Not sure how folks hit their Claude limits. I have handle on the codebase though.

Umm, observability ? I think the article means to say how do you know the agents arent talking nonsense to each other if you use a multi-agent system. Here again a thin layer of o11y would do the trick and also hooking into the wider ecosystem. Thats without having to bother with a proxy.

Took me a while to get used to sealed and I didn't quite see the use. But AI seems to love it for Java so I gave it a go and now I get it. Its like a really good access control mechanism esp if you use DI and want to deprecated some stuff. Apart from ofcourse the pattern matching - which comes in handy for event driven messages where payload shape changes.

Not only is this a huge market, this is a very very good step in the right direction for mozilla. Plenty of integrations can be done browser natively such as phishing site blocking (thats likely the most demanded one). Access controls at this level can also make up for short comings in Web based tools. Not to mention their focus on privacy which benefits the average user. Love it !

LLMs consistently produce better quality code and miss less edge cases imo. I think its ridiculous to assume people don't care about quality. Its also really hard to measure quality so subjective debates around it never end. In the dnd, if LLM produces an output I can understand, I'd rather delegate and move on.

I think its perfectly fine to have AI write and review code but someone needs to keep track of the business logic. Otherwise its difficult to debug what happens when things break or when context misses a few older assumptions. We go into an infinite loop with LLM writing, reviewing, documenting, designing and validating software one feature after the other but right now, we are context limited. Plus if LLM ever gets stuck, it's hard to prompt it away unless somebody understands the output.

> Do you feel like you're getting good value for money if you solve a millenium problem at a fourteen million dollar loss?

Yes you do. If we factor in wages assigned to skilled mathematicians who have worked on this problem, then the 14m for a 1mUSD prize is good value. Also, once things are solved, it on to applications where even more value could potentially be generated. Here its 1m USD simply because theres a proze assigned to it. But once these solution are used in applications, the yield is calculated on the 14m RnD cost. Which (depending on the application) is a good investment.

I am okay with companies shilling their tools. Ultimately I'd want my employer to buy good tools that make our lives easier specifically wrt debugging which I genuinely hate. However this post could have been a better walk through about what Claude found, what was the exact root cause and how it can be fixed instead of the generic Anthithesis found it in 15m.

This is an interesting direction. I wonder if Open LLM models can help with this sort of thing.

I think its also about tolerance for failure. For software that must not fail or where reliability commands a premium you would be wise to invest in formal methods. Core systems at aws for example. For throwaway CRUD code its just easier to try iterations on the problem and call it a day. Its not about respect just RoI.