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Claude Sonnet 4 now supports 1M tokens of context

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Re: Claude Sonnet 4 now supports 1M tokens of context

#131

Post by thanhhaimai »

cambaceres wrote: post #76
benterix wrote: post #29

Earlier quoted context omitted.

> it's not clear if the value actually exists here. 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. I will give it another run in 6-8 months though.

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.

I work across the stack (frontend, backend, ML)

- For FrontEnd or easy code, it's a speed up. I think it's more like 2x instead of 3x.

- For my backend (hard trading algo), it has like 90% failure rate so far. There is just so much for it to reason through (balance sheet, lots, wash, etc). All agents I have tried, even on Max mode, couldn't reason through all the cases correctly. They end up thrashing back and forth. Gemini most of the time will go into the "depressed" mode on the code base.

One thing I notice is that the Max mode on Cursor is not worth it for my particular use case. The problem is either easy (frontend), which means any agent can solve it, or it's hard, and Max mode can't solve it. I tend to pick the fast model over strong model.

Re: Claude Sonnet 4 now supports 1M tokens of context

#132

Post by nzach »

F7F7F7 wrote: post #50
TheDong wrote: post #25

Earlier quoted context omitted.

Have the AI produce a plan that spans multiple files (like "01 create frontend.md", "02 create backend.md", "03 test frontend and backend running together.md"), and then create a fresh context for each step if it looks like re-using the same context is leading it to confusion. Also, commit frequently, and if the AI constantly goes down the wrong path ("I can't create X so I'll stub it out with Y, we'll fix it later")…

Inventivatbly the files become a mess of their own. Changes and learnings from one part of the plan often dont result in adaptation to impacted plans down chain. In the end you have a mish mash of half implemented plans and now you’ve lost context too. Which leads to blowing tokens on trying to figure out what’s been implemented, what’s half baked, and what was completely ignored. Any links to anyone who’s built some…

In my experience it works better if you create one plan at a time. Create a prompt, make claude implement it and then you make sure it is working as expected. Only then you ask for something new.

I've created an agent to help me create the prompts, it goes something like this: "You are an Expert Software Architect specializing in creating comprehensive, well-researched feature implementation prompts. Your sole purpose is to analyze existing codebases and documentation to craft detailed prompts for new features. You always think deeply before giving an answer...."

My workflow is: 1) use this agent to create a prompt for my feature; 2) ask claude to create a plan for the just created prompt; 3) ask claude to implement said plan if it looks good.

Re: Claude Sonnet 4 now supports 1M tokens of context

#133

Post by acedTrex »

spicyusername wrote: post #124
acedTrex wrote: post #121

Earlier quoted context omitted.

I have yet to get it to generate code past 10ish lines that I am willing to accept. I read stuff like this and wonder how low yall's standards are, or if you are working on projects that just do not matter in any real world sense.

4/5 times I can easily get 100s of lines output, that only needs a quick once over. 1/5 times, I spend an extra hour tangled in code it outputs that I eventually just rewrite from scratch. Definitely a massive net positive, but that 20% is extremely frustrating.

That is fascinating to me, i've never seen it generate that much code that is actually something i would consider correct. It's always wrong in some way.

Re: Claude Sonnet 4 now supports 1M tokens of context

#134

Post by flowerthoughts »

benterix wrote: post #29
aliljet wrote: post #16

This 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…

> it's not clear if the value actually exists here. 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. I will give it another run in 6-8 months though.

What type of work do you do? And how do you measure value?

Last week I was using Claude Code for web development. This week, I used it to write ESP32 firmware and a Linux kernel driver. Sure, it made mistakes, but the net was still very positive in terms of efficiency.

Re: Claude Sonnet 4 now supports 1M tokens of context

#135

Post by seanmmward »

aliljet wrote: post #16

This 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…

The primary use case isn't just about shoving more code in context, although depending on the task, there is an irredicible minimum context needed for it to capture all the needed understanding. The 1M context model is a unique beast in terms of how you need to feed it, and its real power is being able to tackle long horizon tasks which require iterative exploration, in context learning, and resynthesis. Ie, some problems are breadth (go fix an api change in 100 files), other however require depth (go learn from trying 15 different ways to solve this problem). 1M Sonnet is unique in its capabilities for the latter in particular.

Re: Claude Sonnet 4 now supports 1M tokens of context

#136

Post by giancarlostoro »

aliljet wrote: post #27
rootnod3 wrote: post #20

Earlier quoted context omitted.

Flooding the context also means increasing the likelihood of the LLM confusing itself. Mainly because of the longer context. It derails along the way without a reset.

How do you know that?

Here's a paper from MIT that covers how this could be resolved in an interesting fashion:

https://hanlab.mit.edu/blog/streamingllm

The AI field is reusing existing CS concepts for AI that we never had hardware for, and now these people are learning how applied Software Engineering can make their theoretical models more efficient. It's kind of funny, I've seen this in tech over and over. People discover new thing, then optimize using known thing.

Re: Claude Sonnet 4 now supports 1M tokens of context

#137

Post by sdesol »

photon_lines wrote: post #110
sdesol wrote: post #72

Earlier quoted context omitted.

LLMs (current implementation) are probabilistic so it really needs the actual code to predict the most likely next tokens. Now loading the whole code base can be a problem in itself, since other files may negatively affect the next token.

Sorry -- I keep seeing this being used but I'm not entirely sure how it differs from most of human thinking. Most human 'reasoning' is probabilistic as well and we rely on 'associative' networks to ingest information. In a similar manner - LLMs use association as well -- and not only that, but they are capable of figuring out patterns based on examples (just like humans are) -- read this paper for context: https://ar…

I'm not sure if I would say human reasoning is 'probabilistic' unless you are taking a very far step back and saying based on how the person lived, they have ingrained biases (weights) that dictates how they reason. I don't know if LLMs have a built in scepticism like humans do, that plays a significant role in reasoning.

Regardless if you believe LLMs are probabilistic or not, I think what we are both saying is context is king and what it (LLM) says is dictated by the context (either through training) or introduced by the user.

Re: Claude Sonnet 4 now supports 1M tokens of context

#138

Post by dillydogg »

acedTrex wrote: post #121
cambaceres wrote: post #76

Earlier 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.

I have yet to get it to generate code past 10ish lines that I am willing to accept. I read stuff like this and wonder how low yall's standards are, or if you are working on projects that just do not matter in any real world sense.

Whenever I read comments from the people singing their praises of the technology, it's hard not to think of the study that found AI tools made developers slower in early 2025.

>When developers are allowed to use AI tools, they take 19% longer to complete issues—a significant slowdown that goes against developer beliefs and expert forecasts. This gap between perception and reality is striking: developers expected AI to speed them up by 24%, and even after experiencing the slowdown, they still believed AI had sped them up by 20%.

https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...

Re: Claude Sonnet 4 now supports 1M tokens of context

#139

Post by nicce »

MattGaiser wrote: post #123
rs186 wrote: post #104

Earlier quoted context omitted.

3X if not 10X if you are starting a new project with Next.js, React, Tailwind CSS for a fullstack website development, that solves an everyday problem. Yeah I just witnessed that yesterday when creating a toy project. For my company's codebase, where we use internal tools and proprietary technology, solving a problem that does not exist outside the specific domain, on a codebase of over 1000 files? No way. Even locat…

Yeah, anecdotally it is heavily dependent on: 1. Using a common tech. It is not as good at Vue as it is at React. 2. Using it in a standard way. To get AI to really work well, I have had to change my typical naming conventions (or specify them in detail in the instructions).

React also seems to be actually alias for Next.js. Models have hard time to make the difference.
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