AWS pricing for Kiro dev tool dubbed 'a wallet-wrecking tragedy'

Here's a summary of the themes expressed in the Hacker News discussion:

Pricing Realism vs. Exploitation

A central theme is the debate over whether AWS's pricing for AI coding assistance is a reflection of "realistic costs" for these advanced technologies, or if it's a deliberate strategy to overcharge, leveraging enterprise reliance on AWS and its purchasing ease.

• User "stackskipton" initiated this by questioning: "Is pricing due to AWS massively overcharging because they know Enterprise might pay it due to ease of use with purchasing? Or is this realistic pricing for LLM coding assistance and AWS has decided to be upfront with actual costs?"
• "jcm9" elaborated on this, suggesting a dual strategy: "Likely both. AWS was often 70+% more expensive on GPUs for a while and remains typically the most expensive provider when put in competitive scenarios... 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."
• "wiether" echoed this sentiment, questioning if AWS's pricing would set a precedent: "If it was a small player, everybody would laugh and forget about them. 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?"
• "kermatt" pointed out the vendor incentive: "Clear pricing makes it easy for you to control costs. Vibe pricing makes it easy for the vendor to maximize revenue. They have a little incentive to make pricing transparent."
• "Bratmon" stated, "If you're care about how much money you're spending, you're not in AWS's target market."

The High Cost of AI and "VC Subsidies"

Many users expressed concern over the actual operational costs of AI services, with some suggesting that current pricing reflects an early stage where companies are burning through venture capital.

• "gjsman-1000" shared a personal anecdote illustrating the high cost: "Well, having personally used over $120 in Claude API credit on my $200/mo. Claude Code subscription... in a single day, without parallel tasks, yeah, it sounds like the actual price."
• This user continued, highlighting the economic reality: "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."
• "stackskipton" framed current pricing as a signal for future costs: "This is also a signal what what the “real cost” of these services will be once the VC subsidies dry up."
• "ipython" agreed, drawing a parallel to the ride-sharing industry: "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."
• "therobots927" criticized the industry's focus: "It’s incredible to me that AI evangelists have managed to focus the entire conversation on LLM “usefulness” without even mentioning costs. It allows them to play a game of smoke and mirrors where no one actually knows the true cost of an API call and there is no predictable cost model."
• "kace91" believes costs will increase: "I think it’s clear that these tools are going to get more expensive."
• "motorest" clarified the cost dynamic: "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."

Business Perceptions of AI's Value and Impact on Headcount

The discussion touched upon how businesses might view the ROI of AI coding assistants, with some suggesting an expectation of headcount reduction or increased individual output without additional cost.

• "sdesol" reacted to the $2000/mo ceiling, stating: "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" added a darker perspective on management's view: "Oh its much worse than that - they think that most developers don't do anything and the core devs are just supported by the ancillary devs, 80% of the work in core devs and 20% otherwise. 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."
• "bgwalter" suggested a cynical view of value: "The prices are for corporations who buy the hype until they find out in a year that vibe coding is utterly useless."
• "viccis" countered the pricing complaint from an open-source perspective: "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."
• "bdcravens" acknowledged the stated value proposition: "If vibe coding fulfills its promises, even those crazy numbers are a small percentage of the price of a full-time dev. I'm not saying it does, but I'm just following along with the alleged value prop."
• "reactordev" stated a personal limit: "Yup. I’m not giving 1/5th of my salary away."

Model Profitability and Cost Breakdown Concerns

The conversation delved into the actual profitability of AI inference, with questions raised about how companies account for development costs, R&D, and the short lifespan of models.

• "tsvetkov" refuted claims of high costs, citing a source: "> Claude's API is still running on zero-margin, if not even subsidized, AWS prices for GPUs; combined with Anthropic still lighting money on fire and presumably losing money on the API pricing. Source? Dario claims API inference is already “fairly profitable”. They have been optimizing models and inference, while keeping prices fairly high." The user linked to a substack article quoting Dario.
• "jcm9" pointed out a missing cost factor: "Most of these “we’re profitable on inference” comments are glossing over the depreciation cost of developing the model, which is essentially a capital expense. Given the short lifespan of models it seems unlikely that fully loaded cost looks pretty."
• "animalmuppet" questioned the salvageability of previous models: "What about MS and Copilot? 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?"
• "nojito" stated: "Tools that don’t control the model as well are doomed to fail due to costs."

Criticism of AWS's Generative AI Strategy and Execution

Several users expressed disappointment and skepticism regarding AWS's approach and implementation of generative AI products, viewing it as reactive, poorly executed, and lagging behind competitors.

• "jcm9" was critical: "AWS is so far behind on GenAI they’re just flailing at this point. Their infrastructure is a commodity at best and their networking performance woes continue. Bedrock was a great idea poorly executed."
• This user continued: "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."
• "jcm9" also commented on hardware: "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."
• "leptons" suggested AWS should focus on its core competencies: "I'm fine if AWS doesn't pursue AI that much, they should focus on infrastructure. It's a solid business as-is. AWS doesn't need "GenAI" to continue to do what they've been doing for a long time."
• "jcm9" agreed on AWS's leadership issues: "They also don’t have solid recognized leaders or talent in the space and it shows."
• "belter" attributed AWS's struggles to a shift in culture and talent: "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."
• "slowdog" described internal competition: "It’s less that they’re flailing and more that it’s become some sort of lord of the flies culture with senior leaders directly competing with each other to try to take their bite of the pie."
• "rvz" cynically viewed AWS's position: "The AWS logo is always smiling when startups who attempt to scale as if they are Google want to use their services and burn all that VC money and continue to raise every month to avoid shutting down. 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."

The Inconvenience and Obfuscation of Pricing Models

Some users expressed frustration with the complexity and lack of transparency in AI pricing schemes, contrasting them with simpler, more predictable models.

• "mns" described the pricing structure as comical: "Reading the article and the linked Github post, as well as the original pricing announcement and the clarification post afterwards, this whole thing seems like some sort of Monty Python sketch. I can't believe that an actual enterprise targeted product comes up with something like: > "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"".
• This user continued, advocating for clarity: "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."
• "ranie93" simply stated: "Just give me dollar amounts, I feel like I'm paying these companies with vbucks at this point."
• "motbus3" shared a negative user experience with the pricing model: ""Vibe requests are useless because the vibe agent constantly nags me to switch to spec requests, claiming my chats are 'too complex'" How can you trust a tool that refuses to do the work to just take more money from you?"

The Future of AI Integration and User Choice

The discussion also touched upon the evolving landscape of AI tools, the importance of user choice in selecting models and platforms, and the potential for more flexible, cost-effective solutions.

• "shepardrtc" expressed mixed feelings: "The pricing really turned me off after a fantastic initial experience. I started using it this weekend to build a greenfield project from scratch. Vibe requests ran out very quickly, so I just opened up VS Code in another window and had Copilot's Agent handle those. I just use Kiro for the Spec requests at the moment, which it does quite well. I think its a great tool, but if someone can copy what they're doing into Copilot, then I'll go back to using Copilot exclusively."
• "hbarka" mentioned a potential competitor: "Google’s free Gemini CLI might be catching up to the $200/month Claude Code."
• "chrismustcode" questioned the product's nature: "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)."
• "KronisLV" suggested a more flexible approach: "Past a certain point, using tools like RooCode or anything else that lets you connect to arbitrary APIs feels like the way to go - whether you want to pay for one provider directly, or just use something like OpenRouter. That way you have: * the ability to use regular VSC instead of a customized fork..., * the ability to pick what plugin suits your needs best..., * the ability to pick whatever models you want and can afford, local ones..."
• "add-sub-mul-div" warned about future "enshittification": "And it's still the early customer-acquisition era for all of this stuff. Wait until the dust settles and you see what pricing and user experience will be like in the coming enshittification era."