Yes Cline is more reflective of the actual price of inference from frontier models. It's not realistic to offer 500 requests at $20/month without severely limiting what these models can do.

People who have become adamant Cline users over a significantly cheaper option have found the ROI of a higher performing AI coding tool far outweighs the inference costs. Even $500/month is negligible if it can 5x (or more) the output of a high-salary engineer.

Mine ranges around $2-20 per day depending on how much I use it and how complex the task and size of the project

That’s a lot compared to $20/month for cursor, no?

Yes, but Cursor usually doesn't solve the tasks I have

Very true! but sometimes the $0.04 and 25 tool calls, cannot get you to the right solution no matter how many times you re-prompt. And that's where Cline has been better for me.

It's almost like hiring. Would you pay a premium for the very best dev, or would you pay less for an average dev. :)

I wonder what the dev speed-up would have been if they used Unity with Coplay

How often do whale collisions happen?

I've found it useful for controlling Unity from within Cursor while doing game development.

I guess if someone like Anthropic builds a proper registry, then the user wouldn't have to decide and the AI can decide itself?

I understand the value of infinite NPC dialogues and story arcs, but why do we need live scene generation? Don't we already get that with procedural generation?

Would love stem cells for gum recovery!

"A key issue with AI-powered search is that it is just too slow compared to classic Google. Even if it generates a better answer, the added latency is discouraging."

Is this true? I feel like most complaints I have and hear about is how inaccurate some of the AI results are. I.e. the mistakes it confidently makes when helping you code.

From hitting enter to seeing something, ofc it's slower.

From hitting enter to a set of relevant answers loaded into your brain, though? Isn't that the goal that should be measured? Against that goal, the two decade old approach seems to have peaked over a decade ago, or phind wouldn't find traction.

For the 20 year old page rankers, time from search to a set of correct answers in your brain is approaching “DNF” -- did not finish.

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PS. Hallucinations or irrelevant results, both require exercising a brain cell. On a percentage basis, there are fewer hallucinations than irrelevant results, it's just that we gave up on SERP confidence ages ago.

It's one of those triangles with speed \ accuracy / cost.

You can have a small model that's cost effective to serve, and gives fast responses, but will be wrong half the time.

Or you can have a large model that's slow to run on cheap hardware, but will give more accurate answers. This is usually only fast enough for personal use.

And the third option with a large model that's fast and accurate, and you'll have to pay Nvidia/Groq/etc. a small fortune to be able to run it at speed and also probably build a solar powerplant to make it cost effective in power use.

This is true in my experience. Before searching for something I often try to guess whether it will take me more time to quickly go over Google results or watch Perplexity Pro slowly spitting the answer line-by-line.

I think they're both key issues - when the results are accurate, they're too slow; and you can't trust the results when you get there because they're often inaccurate