The pricing really turned me off after a fantastic initial experience.
I know he thought it was "not terrible" at first, I'm excited to see his take on the pricing now :)
The prices are for corporations who buy the hype until they find out in a year that vibe coding is utterly useless.
Windsurf started out as just extensions, as did continue.dev.
I wonder what is the delta in the API support needed to use vscode + paid extension vs. code OSS + bundled extensions.
Well maybe you shouldn't be using an enterprise AI coding toolset to do work that has historically been done for the love of coding and helping others. AI to do uncompensated labor is almost never going to work out financially like this. If it's really good enough to replace a decent engineer on a team, then those costs aren't "wallet-wrecking", it just means he needs to stay away from commercial products with commercial pricing. It's like complaining about the cost of one of VMWare's enterprise licenses for your home lab.
I will also add that it's rare these days to see a new AWS product or service that doesn't cost many times what it should. Most of these things are geared towards companies who are all in on the AWS platform and for whom the cost of any given service is a matter of whether it's worth paying an employee to do whatever AWS manages with that service.
Honestly I liked some of the non-AI content a lot more (but AI seems to be more of a focus lately). He also had such an amazing run of fantastic guests: its nonsense to say this, but he's running through the list of awesome people to talk to fast, and I hope he's not afraid to invite many of these fantastic people back again!
> "AWS now defines two types of Kiro AI request. Spec requests are those started from tasks, while vibe requests are general chat responses. Executing a sub-task consumes at least one spec request plus a vibe request for "coordination"".
I still don't understand why pricing can't be as simple as it was initially and presented in a clear and understandable way: token cost this much, you used this many tokens, and that is it. Probably because if people would see how much they actually consume for real tasks, they would realize that the "vibes" cost more than an actual developer.
Vibe pricing makes it easy for the vendor to maximize revenue.
They have a little incentive to make pricing transparent.
LLMs are highly useful.
AI-assisted services are in general costly.
There are LLMs you can run locally on your own hardware. You pay AI-assisted services to use their computational resources.
What is not clear to me is that they’ll get expensive enough to not be worth it for a company.
A good engineer costs a lot of money and comes with limitations derived from being human.
Let’s say AI manages to be a 2x multiplier in productivity. Prices for that multiplier can rise a lot before they reach 120k/year for 40 hours a week, the point at which you’re better off hiring someone.
I'm working on a new fictional meta-narrative where AGI with the dominant belief in commerce, above all else, above nations, above politics, above war, above morality is what happens when super-intelligence emerges.
China is massively building out solar power to meet their needs. https://www.youtube.com/watch?v=MX_PeNzz-Lw&t=50
Also data retention Gemini has which you have to download a vs code extension to turn off for the CLI.
It isn’t an enterprise product it’s a way to get data for tool calling for training as far as I see it (as it currently stands).
But now we're talking about AWS... so aren't other players going to see this as an opportunity to start increasing their pricing and stop bleeding millions?
Now the cost of using their tools like Kiro will just make AWS laugh at all the free money they are getting including their hidden charges on simple actions.
Ask yourself if you were starting a startup right now if you really need AWS.
Remember, you are not Google.
Their infrastructure is a commodity at best and their networking performance woes continue. Bedrock was a great idea poorly executed. Performance there is also a big problem. They have the Anthropic models which are good, but in our experience one is better off just using Anthropic directly. On the managed services front there’s no direction or clear plan. They seem to have just slapped “Q” on a bunch of random stuff as part of some disjointed panicked plan to have GenAI products. Each “Q” product is woefully behind other offerings in the market. Custom ML chips were agin a good idea poorly executed, failing to fully recognize that chips without an ecosystem (CUDA) does not make a successful go to market strategy.
I remain a general fan of AWS for basic infrastructure, but they’re so far behind on this GenAI stuff that one has to scratch your head at how they messed this up so badly. They also don’t have solid recognized leaders or talent in the space and it shows. AWS still generally doing well but recent financial results have shown chinks in the armor. Without a rapid turnaround it’s unlikely they’ll be the number one cloud provider for much longer.
I too would like to see them just admit they’re behind, state it’s not a priority, and focus on what they do well which is the boring (but super important) basic infrastructure stuff.
AWS was built by exceptional technical leaders like James Hamilton, Werner Vogels, and Tim Bray and I would include Bezos also, who people seem to forget has a Computer Science degree. But the company has consistently underpaid developers, while relying heavily on H-1B workers, and treating technical talent as poorly as Amazon treats delivery drivers.
When skilled engineers can get better opportunities elsewhere, they leave. AWS below market compensation, has driven away the technical expertise needed for innovation.
AWS has shifted from technical leadership to MBA driven management, and lately aggressively hiring senior middle management from Oracle. The combination of technical talent exodus, cultural deterioration and MBA style management made AWS poorly positioned for the AI era, where technical excellence and innovation speed are everything.
During major technological shifts like AI, you need a engineering first culture and inhouse technical skills. AWS has neither.
The way AWS is structured with strongly owned independent businesses just doesn’t work, as GenAI needs a cohesive strategy which needs
1. An overall strategy
2. A culture that fosters collaboration not competition
Or at least an org charts to make them not compete with each other. (Example: Q developer vs Kiro)
I bet if you looked at the org charts you would see these teams don’t connect as they should.
That way you have:
* the ability to use regular VSC instead of a customized fork (that might die off)
* the ability to pick what plugin suits your needs best (from a bunch available, many speak with both OpenAI and Ollama compatible APIs)
* the ability to pick whatever models you want and can afford, local ones (or at least ones running on-prem) includedHow can you trust a tool that refuses to do the work to just take more money from you?
stackskipton•2h ago
gjsman-1000•2h ago
The future is not that AI takes over. It's when the accountants realize for a $120K a year developer, if it makes them even 20% more efficient (doubt that), you have a ceiling of $2000/mo. on AI spend before you break even. Once the VC subsidies end, it could easily cost that much. When that happens... who cares if you use AI? Some developers might use it, others might not, it doesn't matter anymore.
This is also assuming Anthropic or OpenAI don't lose any of their ongoing lawsuits, and aren't forced to raise prices to cover settlement fees. For example, Anthropic is currently in the clear on the fair use "transformative" argument; but they are in hot water over the book piracy from LibGen (illegal regardless of use case). The worst case scenario in that lawsuit, although unlikely, is $150,000 per violation * 5 million books = $750B in damages.
sdesol•1h ago
I don't think businesses sees it this way. They sort of want you to be 20% more efficient by being 20% better (with no added cost). I'm sure the math is, if their efficiency is increased by 20% then than means we can reduce head count by 20% or not hire new developers.
hobs•1h ago
In many workplaces this is true. That means an "ideal" workspace is 20% of the size of its current setup, with AI doing all the work that the non-core devs used to do.
tsvetkov•1h ago
Source? Dario claims API inference is already “fairly profitable”. They have been optimizing models and inference, while keeping prices fairly high.
> dario recently told alex kantrowitz the quiet part out loud: "we make improvements all the time that make the models, like, 50% more efficient than they are before. we are just the beginning of optimizing inference... for every dollar the model makes, it costs a certain amount. that is actually already fairly profitable."
https://ethanding.substack.com/p/openai-burns-the-boats
JCM9•52m ago
AnimalMuppet•48m ago
I suspect that the answer is almost all of the training data, and none of the weights (because the new model has a different architecture, rather than some new pieces bolted on to the existing architecture).
So then the question becomes, what is the relative cost of the training data vs. actually training to derive the weights? I don't know the answer to that; can anyone give a definitive answer?
Insanity•2h ago
Amazon / AWS might not want (or need) to play that game.
verdverm•1h ago
stackskipton•1h ago
Obviously, they are not taking VC money but using revenue from other parts of the company.
JCM9•1h ago
Whereas others are willing to loose a bit to get ahead in a competitive space like GenAI, AWS has been freaking out a bit since of the cloud gets driven to lose margin competition then Amazon is in big trouble. This they’ll do everything possible to keep the margins high, which translates to “realistic” pricing based on actual costs in this case. And thus yes seemingly hoping enterprises will buy some expensive second rate product so they can say they have customers here and hoping they don’t notice better cheaper offerings are readily available.
This is also a signal what what the “real cost” of these services will be once the VC subsidies dry up.
ipython•45m ago
Sooooo true. Waiting for AI’s “uber” moment aka when uber suddenly needed to actually turn a profit and overnight drivers were paid less while prices rose 3x.