My experience with the current tools so far: 1. It helps to get me going with new languages, frameworks, utilities or full green field stuff. After that I expend a lot of time parsing the code to understand what it wrote that I kind of "trust" it because it is too tedious but "it works". 2. When working with languages or frameworks that I know, I find it makes me unproductive, the amount of time I spend writing a goo…
I really find your experience strikingly different than mine, I'll share you my flow: - step A: ask AI to write a featureA-requirements.md file at the root of the project, I give it a general description for the task, then have it ask me as many questions as possible to refine user stories and requirements. It generally comes up with a dozen or more of questions, of which multiples I would've not thought about and fo…
Claude Sonnet 4 now supports 1M tokens of context
601–610 of 706 posts
Re: Claude Sonnet 4 now supports 1M tokens of context
#602Earlier quoted context omitted.
> I really desperately need LLMs to maintain extremely effective context The context is in the repo. An LLM will never have the context you need to solve all problems. Large enough repos don't fit on a single machine. There's a tradeoff just like in humans where getting a specific task done requires removing distractions. A context window that contains everything makes focus harder. For a long time context windows we…
> But they have to get better at understanding the repo by asking the right questions. How I am tackling this problem is making it dead simple for users to create analyzers that are designed to enriched text data. You can read more about how it would be used in a search at https://github.com/gitsense/chat/blob/main/packages/chat/wid... The basic idea is, users would construct analyzers with the help of LLMs to extrac…
Re: Claude Sonnet 4 now supports 1M tokens of context
#603Earlier quoted context omitted.
> Makes me wonder if people spoke this way about “using computers” or “using the internet” in the olden days. There were gobs of terrible road metaphors that spun out of calling the Internet the “Information Superhighway.” Gobs and gobs of them. All self-parody to anyone who knew anything. I hesitate to relate this to anything in the current AI era, but maybe the closest (and in a gallows humor/doomer kind of way) is…
Remember the ones who loudly proclaimed the internet to be a passing fad, not useful for normal people. All anti LLM rants taste like that to me. I get why they thought that - it was kind of crappy unless you're one who is excited about the future and prepared to bleed a bit on the edge.
For me they're very different and they sound much more the crypto-skepticism. It's not like "LLMs are worthless, there are no use cases, they should be banned" but rather "LLMs do have their use cases but they also do have inherent flaws that need to be addressed; embedding them in every product makes no sense etc.". (I mean LLMs as tech, what's happening with GenAI companies and their leaders is a completely different matter and we have every right to criticize every lie, hypocrisy and manipulation, but let's not mix up these two.)
Re: Claude Sonnet 4 now supports 1M tokens of context
#604Re: Claude Sonnet 4 now supports 1M tokens of context
#605Earlier quoted context omitted.
I disagree, I may not have the whole codebase in my head in one moment but I have had all of it in my head at some point, and it is still there, that is not true of an LLM. I use LLMs and am impressed by them, but they just do not approximate a human in this particular area. My ability to break a problem down does not start from listing the files out and reading a few. I have a high level understanding of the whole p…
Additionally, the more information you put into the context the more confused the LLM will get, if you did dump the whole codebase into the context it would not suddenly understand the whole thing. It is still an LLM, all you have done is polluted the context with a million lines of unrelated code, and some lines of related code, which it will struggle to find in the noise (in my experience of much smaller experiment…
The bigger the context, the more stuff "decays" sometimes to complete different meanings
Re: Claude Sonnet 4 now supports 1M tokens of context
#606Many people are confused about the usefulness of 1M tokens because LLMs often start to get confused after about 100k. But this is big for Claude 4 because it uses automatic RAG when the context becomes large. With optimized retrieval thanks to RAG, we'll be able to make good use of those 1M tokens.
How does this work under the hood? Does it build an in-memory vector database of the input sources and runs queries on top of that data to supplement the context window?
Re: Claude Sonnet 4 now supports 1M tokens of context
#607Earlier quoted context omitted.
For me it’s meant a huge increase in productivity, at least 3X. Since so many claim the opposite, I’m curious to what you do more specifically? I guess different roles/technologies benefit more from agents than others. I build full stack web applications in node/.net/react, more importantly (I think) is that I work on a small startup and manage 3 applications myself.
> Having spent a couple of weeks on Claude Code recently, I arrived to the conclusion that the net value for me from agentic AI is actually negative. > For me it’s meant a huge increase in productivity, at least 3X. How do we reconcile these two comments? I think that's a core question of the industry right now. My take, as a CTO, is this: we're giving people new tools, and very little training on the techniques that…
1. LLMs seem to benefit 'hacker-type' programmers from my experience. People who tend to approach coding problems in a very "kick the TV from different angles and see if it works" strategy.
2. There seems to be two overgeneralized types of devs in the market right now: Devs who make niche software and devs who make web apps, data pipelines, and other standard industry tools. LLMs are much better at helping with the established tool development at the moment.
3. LLMs are absolute savants at making clean-ish looking surface level tech demos in ~5 minutes, they are masters of selling "themselves" to executives. Moving a demo to a production stack? Eh, results may vary to say the least.
I use LLMs extensively when they make sense for me.
One fascinating thing for me is how different everyone's experience with LLMs is. Obviously there's a lot of noise out there. With AI haters and AI tech bros kind of muddying the waters with extremist takes.
Re: Claude Sonnet 4 now supports 1M tokens of context
#608Earlier quoted context omitted.
The brain can literally not process any piece of information without being changed by the act of processing it. Neuronal pathways are constantly being reinforced or weakened. Even remembering alters the memory being recalled, entirely unlike how computers work.
I've always find it interesting that once I take a wrong turn finding my way through the city and I'm not deliberate about remembering this was, in fact, a mistake, I am more prone to taking the same wrong turn again the next time.
You may want to stay home then to avoid getting lost.
Re: Claude Sonnet 4 now supports 1M tokens of context
#609This is definitely one of my CORE problem as I use these tools for "professional software engineering." I really desperately need LLMs to maintain extremely effective context and it's not actually that interesting to see a new model that's marginally better than the next one (for my day-to-day). However. Price is king. Allowing me to flood the context window with my code base is great, but given that the price has su…
I’m assuming the credits required per use won’t increase in Cursor.
Hopefully this puts pressure on them to lower credits required for gpt-5.
Re: Claude Sonnet 4 now supports 1M tokens of context
#610It used to always pitch answers at the right level, but recently it just seems to have left its common sense at the door. Gemini just gives much better answers for non-technical questions now.