71–80 of 266 posts
Oh no, remote MCP servers. Security was nice while it lasted!
MCP is a flawed spec and quite frankly a scam.
The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point. LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of d…
I agree with your overall message - rapid growth appears to encourage competition and forces companies to put their best foot forward. However, unfortunately, I cannot shower much praise on Claude 3.7. And if you (or anyone) asks why - 3.7 seems much better than 3.5, surely? - Then I’m moderately sure that you use Claude much more for coding than for any kind of conversation. In my opinion, even 3.5 Haiku (which is a…
The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point. LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of d…
None of those reports are any good though. Maybe for shallow research, but I haven't found them deep. Can you share what kind of research you have been trying there where it has done a great job of actual deep research.
Earlier quoted context omitted.
I disagree. They can walk and chew gum, do both things at once. And this practical stuff is very important. I've been using the Atlassian MCP for nearly a month now, and it's completely changed (and eliminated) the feeling of having an overwhelming backlog. I can have it do things like "find all the tickets related to profile editing and combine them into one epic" where it works perfectly. Or "help me prioritize the…
> If you look at my JIRA comments now, you'd wonder how I had so much time to write such thorough comments. I don't, Cursor and whatever model is doing it for me. How do your colleagues feel about it?
I think all the retail LLM's are working to broaden the available context, but in most practical use-cases it's having the ability to minimize and filter the context that would produce the most value. Even a single PDF with too many similar datapoints leads to confusion in output. They need to switch gears from the high growth, "every thing is possible and available" narrative, to one that narrows the scope. The "hal…
Throw in all context --> ask it what is important for problem XYZ --> curate what it tells you, and feed that to another model to actually solve XYZ
Earlier quoted context omitted.
I disagree. They can walk and chew gum, do both things at once. And this practical stuff is very important. I've been using the Atlassian MCP for nearly a month now, and it's completely changed (and eliminated) the feeling of having an overwhelming backlog. I can have it do things like "find all the tickets related to profile editing and combine them into one epic" where it works perfectly. Or "help me prioritize the…
> If you look at my JIRA comments now, you'd wonder how I had so much time to write such thorough comments. I don't, Cursor and whatever model is doing it for me. How do your colleagues feel about it?
One of them said “yeah I was wondering cuz you never write that much” - as a leader, I actually don’t set a good example of how to leave quality JIRA comments. And my view with all these things is that I have to lead by example, not by orders.
With the help of these kinds of tools, we can improve the quality of these comments. And I wouldn’t expect others to write them manually, more that I wanted to show that everyone’s use of JIRA on the team can improve.
Earlier quoted context omitted.
> If you look at my JIRA comments now, you'd wonder how I had so much time to write such thorough comments. I don't, Cursor and whatever model is doing it for me. How do your colleagues feel about it?
My colleagues' LLM assistants think that my LLM assistant leaves great JIRA comments.
I also don’t want to read too many unnecessary words.
The integrations feel so rag-ish. It talks, tells you it’s going to use a tool, searches, talks about what it found… Hope one day it will be practical to do nightly finetunes of a model per company with all core corporate data stores. This could create a seamless native model experience that knows about (almost) everything you’re doing.
why is finetuning talked about so much less than RAG? is it not viable at all?
I'll leave it to you to guess which one is harder to do.
The integrations feel so rag-ish. It talks, tells you it’s going to use a tool, searches, talks about what it found… Hope one day it will be practical to do nightly finetunes of a model per company with all core corporate data stores. This could create a seamless native model experience that knows about (almost) everything you’re doing.
why is finetuning talked about so much less than RAG? is it not viable at all?
The leap frogging at this point is getting insane (in a good way, I guess?). The amount of time each state of the art feature gets before it's supplanted is a few weeks at this point. LLMs were always a fun novelty for me until OpenAI DeepResearch which started to actually come up with useful results on more complex programming questions (where I needed to write all the code by hand but had to pull together lots of d…
I agree with your overall message - rapid growth appears to encourage competition and forces companies to put their best foot forward. However, unfortunately, I cannot shower much praise on Claude 3.7. And if you (or anyone) asks why - 3.7 seems much better than 3.5, surely? - Then I’m moderately sure that you use Claude much more for coding than for any kind of conversation. In my opinion, even 3.5 Haiku (which is a…
I haven't been able to use Claude research yet (it's not rolled out to the Pro tier) but o1 -> o3 deep research was a massive jump IMHO. It still isn't perfect but o1 would often give me trash results but o3 deep research actually starts to be useful.
3.5->3.7 (even with extended thinking) felt like a nothingburger.