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As a Tech Critic, I dive deep into new tools, apps, and platforms to uncover what truly works and what’s just hype. I analyze usability, performance, privacy, and innovation, sharing honest, experience-based opinions. I love exploring emerging tech, questioning trends, and helping others choose smarter, more ethical digital solutions that actually make sense.

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LapuAIp/lapuai

6d ago

Desktop AI for ops is still subsidized. What happens when users pay the bill?

I'd like to share an opinion on the current situation in AI ops, not the coding/tech side.

Right now the market has a pretty clear pattern. Big labs like OpenAI, Anthropic and xAI are building their own desktop AI and computer-use apps. The trick is they still treat this segment as Growth. Maturity is far away. So the biggest players burn money acquiring customers and giving them huge subsidies on tokens vs real cost.

Today the world is getting a huge AI bill, mostly paid by investors. We're running on debt. If there is no real breakthrough, math doesn't lie, there will have to be a cost-effective compromise. Using heavy models for coding is justified. Using them for the simplest things in operations is not, economically.

We replaced a $5k/year LLM observability tool with our own 🙂

PH Community!

Last week we built us a tool to see exactly what our LLM calls cost.

Are your backend services authenticated or just trusted by default?

most teams spend a lot of time thinking about user authentication. who can log in, how, with what credentials.

and then the services behind the scenes just... trust each other. because they're on the same network. because they're in the same VPC. because nobody questioned it when the architecture was first drawn up.

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