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Outsourcing plus local AI will soon become more economical vs. frontier labs

signalbloom.ai

61–70 of 408 posts

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#61

The current closed source frontier models are more capable than the latest from DeepSeek. But is the capability difference enough to justify a 30x price difference? "Frontier models" are caught in a financial dilemma of their own making --- they have spent such huge sums on development and as a result, they may have inadvertently priced themselves out of the market. Energy costs are a huge factor for AI. He who has t…

> they may have inadvertently priced themselves out of the market. Last week we were all talking about how Anthropic has too much demand, how they had to rent a data center from a competitor, and how the limits they’ve put on their service to deal with the demand are making users angry. DeepSeek is cheap because they’re working hard to attract users. The open weights models released for free weren’t free to train. It…

Yes and no. Just take a look at the OpenRouter providers page:

https://openrouter.ai/deepseek/deepseek-v4-pro/providers

Deepseek v4 Pro is much cheaper when provided by Deepseek itself, likely as a combination of the loss leader strategy you mention and the desire to have more data flow through their pipeline for training. However, the same open weights model, provided by other providers, is somewhere in the $2-3/1M output-tokens range. Compare Opus 4.7 at $25/1M output-tokens.

Unless you mean that releasing open weights models is the loss leader, in which case, you might be right but I hope you're wrong. We've seen some of this from Qwen at least - their latest model is closed only. I hope there's always someone willing to make this bet and release better and better open models.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#62
post #48

When discussing LLM pricing, people are missing the plot. The subscription token price is 10x-40x cheaper than API pricing. Your 90$ Claude subscriptions give you close to $1000 to $4000 in equivalent API token pricing. The second issue is that the quality of the model “operator” makes a massive difference in the outcomes. Highly skilled senior devs who know how to prompt and have high agency will outperform team peo…

> When discussing LLM pricing, people are missing the plot. [ ... snipped ...] Your 90$ Claude subscriptions give you close to $1000 to $4000 in equivalent API token pricing. And you think it is unreasonable to consider this unsustainable?

And the direction is definitely towards removing that subsidy really soon. We can see it with OpenAI's shift to API-equivalent pricing for enterprise customers last month. Anecdotally my company saw OpenAI credit usage grow 2x with stable use across the ChatGPT platform, which is pretty terrifying considering just 2% of the company uses Codex.

For context, ChatGPT business subscriptions give you a fixed pool of credits to use, after which you get billed a la carte at inflated 1.75x rates vs API, or if you don't want to pay, you get access to anything but the non-reasoning models turned off for the month.

We also tried Claude Enterprise, which was unusable as people blew through their monthly limits in a matter of hours.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#64

My friend is an exec at a US software company and they are preparing to lay off a few teams of programmers in their Eastern European locations and replacing them with a small number of US programmers + AI. He said they are much more productive and produce new features much faster.

I think the article is right about outsourcing but not from cheap offshored contractors, good experts will become more independent and be more enabled to support more clients with AI, meaning small and medium businesses won’t need internal as many engineers, finance, marketing, etc

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#65
post #34

Earlier quoted context omitted.

How many of those wtf moments are simply from not “being in the room when it happened?” Most enterprise software is riddled with wtf moments demanded as one compromise or another.

There's always wtf, why did we add this feature, but at least in my experience, once a week or so I run into something in this category. Me: "AI, please cleanup/refactor/improve this thing" AI: "Roger that! I deleted the file so now it's perfectly clean" ... insert W.T.F.

Never seen that once.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#66
post #28

I think this misses the forest for the trees. Working with ChatGPT is eerily similar to working with offshore Indian devs back in my enterprise days. Productive if guided explicitly but if let run wild there's lots of WTF moments. LLMs are likely to replace outsourced devs because your employees that know the context can use LLMs to do what offshore devs did before.

"offshore Indian devs" are no slouches. They have access to the same GPT models and likely cost a tenth of the median US salary. Businesses are always looking to lower marginal cost. They will hire 1 software architect in US to write specs and 10 software developers in India to babysit 100 agents.

This is short-sighted. The problem with offshore Indian devs is the communication friction/overhead. You're 9 hours offset, with people who have decent-but-not-great English skills and wildly different cultural priors. If the product people/decision makers are in the US, you're getting a ~50% savings to suffer all those issues, while the cost of tokens remains unchanged. That 50% savings doesn't look very impressive when you're taking a 20% productivity hit from comms friction and crossed wire, and 35% of your total cost is from tokens anyhow. Then it comes out to be a very marginal savings, at the cost of a VASTLY worse hiring experience and VERY high variance of outcomes.

Offshore Indian devs make sense when you can have a large Indian division so you can amortize communication infrastructure/process management over a lot of heads, and you're building for international customers so you're not paying an English -> X tax inherently.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#67
I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#68

$1100/m for an outsourced engineer… am I missing something? That’s far too low. Even juniors in South America tend to ask for at least double that number before factoring in the DeepSeek cost.

I thought the same thing. The author's reference point for LCOL developer seems a bit outdated. With what we pay our teammates in Colombia, the model pushed out to 22 months before crossover.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#69
I disagree with every part of this.

Local LLMs are great and very useful but if you are claiming that their code quality is in the same ballpark as Claude Code or Codex with their best models I cannot consider you a serious person. I feel like this is analogous to the folks arguing that The Cloud is "someone else's computer." As if billions of dollars of spend gives these companies zero benefit over a Mac mini.

Regarding offshore, at least in my experience, better coding agent output is down to two factors. First, is subject matter expertise. Providing the right context to the coding agent based on the tech you are building for is beyond critical. That's the issue with the Vibe Coded slop projects. No expertise in a technology means no awareness of gotchas, React is the most obvious because the LLM default is to useEffect endlessly.

The bigger issue is that by their very nature LLMs are very sensitive to quality prompting in English. I have seen offshore devs fail endlessly because they don't have the English skills to successfully prompt the machine. That has caused more work for my US based devs to either carefully tune the work ticket so it is basically a coding agent prompt. Or to go through multi day exercises to enforce better prompting.

A single US dev with Claude Code is orders of magnitude better than typical offshore. Adding local models into the mix would make offshore completely useless. I'm sure many companies will see ballooning AI bills and expensive onshore devs and be very tempted to go to TCS or similar. I hope so, because that will give startups plenty of easy targets to disrupt.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#70

I've been pretty happy sticking with codex 5.4 medium. I don't see a good case for switching to 5.5 at the cost of going through my token budget quicker. There are misaligned incentives here between users just trying to get stuff done and AI companies competing on having the "smartest" model that passes benchmarks and continuously does some nobel peace price winning stuff. It's mostly overkill for the more mundane st…

I used to be on 5.4 high for most of my work. I have switched completely to 5.5 medium now. I would highly recommend trying it out - 5.5 is significantly more token efficient than 5.4 - the same task takes often a third of the tokens - because of this, is it also much faster to do the task - you get high "intelligence" per token even after accounting for token efficiency - 5.5 medium is just under 5.4 pro levels of i…

We trialed 5.5 and the same queries produced worse results. Not worth the cost increase. Even if there’s a token efficiency gain the higher cost wipes that out.
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