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Seems to be for me, I came to look at HN because I saw it was the default in CC
where do you see it in CC?
Only on a max (20x) account, not there on a Pro one.
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> 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.
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> 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.
Quote possibly you are doing very common things that are often done and thus are in the training set a lot, the parent post is doing something more novel that forces the model to extrapolate, which they suck at.
How does "supporting 1M tokens" really work in practice? Is it a new model? Or did they just remove some hard coded constraint?
Serving a model efficiently at 1M context is difficult and could be much more expensive/numerically tricky. I'm guessing they were working on serving it properly, since its the same "model" in scores and such.
I’ve tried 2 AI tools recently. Neither could produce the correct code to calculate the CPU temperature on a Raspberry Pi RP2040. The code worked, looked ok and even produced reasonable looking results - until I put a finger on the chip and thus raised the temp. The calculated temperature went down. As an aside the free version of chatGPT didn’t know about anything newer than 2023 so couldn’t tell me about the RP2350
I’ve tried 2 AI tools recently. Neither could produce the correct code to calculate the CPU temperature on a Raspberry Pi RP2040. The code worked, looked ok and even produced reasonable looking results - until I put a finger on the chip and thus raised the temp. The calculated temperature went down. As an aside the free version of chatGPT didn’t know about anything newer than 2023 so couldn’t tell me about the RP2350
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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…
My biggest take so far: If you're a disciplined coder that can handle 20% of an entire project's (project being a bug through to an entire app) time being used on research, planning and breaking those plans into phases and tasks, then augmenting your workflow with AI appears to be to have large gains in productivity.
Even then you need to learn a new version of explaining it 'out loud' to get proper results.
If you're more inclined to dive in and plan as you go, and store the scope of the plan in your head because "it's easier that way" then AI 'help' will just fundamentally end up in a mess of frustration.
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Your first week of AI usage should be crawling your codebase and generating context.md docs that can then be fed back into future prompts so that AI understands your project space, packages, apis, and code philosophy. I guarantee your internal tools are not revolutionary, they are just unrepresented in the ML model out of the box
How do you keep the context.md updated as the code changes?
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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 purpos…
>You always think deeply before giving an answer... Nice try but they're not giving you the "think deeper" level just because you asked.
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.
chatting witch claude and copy/pasting code between my IDE and claude is still the most effective for more complex stuff, at least for me.