Browse Comments — Clean (de-noised)
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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They had it coming
I fundamentally believe that AI cannot drive the growth companies expect by removing human work force. However, it can definitely be a force multiplier for people and companies who learns to work with it. I think doing this will save more money for businesses than the tangible /Intangible benefits of replacing humans with AI and sharing some direct benefits companies will have. 1. Reduced OpEx because it makes teams 10x productive and efficient 2. More time/bandwidth/headspace for teams to focus on things where AI cannot be trusted or used. 3. Companies save money on rework due to human errors.
SAURABH SINGH AI is a powerful copilot, but enterprise-level reasoning, critical thinking, understanding business context, and architecture is still a human responsibility. AI can speed up execution, but it does not reduce the mental effort.
Exactly. AI is powerful, but many companies treated it like a replacement strategy instead of a productivity tool. The real value still comes from human judgment, creativity, and problem solving,AI just accelerates it.
AI industry uses the Jio model of dependency. Give products at very cheap rates make them dependent and charge higher and higher.
This is the correction phase of the AI hype cycle that many experienced engineers expected. AI absolutely boosts productivity, but “replace engineers” was always a flawed framing. Engineering is not just code generation — it’s architecture, trade-offs, debugging ambiguous failures, domain understanding, operational ownership, and long-term maintainability. What many companies underestimated:• Token economics at enterprise scale• Context-window inefficiencies on large codebases• Human review overhead• Hallucination-driven rework• The cost of bad architectural decisions generated confidently at high speed The real winning model is likely to be:Small, highly skilled engineering teams + AI augmentation — not AI replacing teams entirely. The companies getting the best ROI from AI today are usually the ones using it as a force multiplier for senior engineers, not as a wholesale substitute for engineering judgment.
This is a much-needed reality check on the current AI economics. The Microsoft Claude Code example is particularly telling, high token burn with no clear productivity multiplier that justifies the cost. Treating AI as a blanket headcount replacement instead of targeted leverage is where most companies are getting the math wrong. Sobering post.
The industry is moving from AI hype to AI accountability. The real question was never whether AI can replace humans — it’s whether companies can use it sustainably, strategically, and at scale. The future belongs to organizations that combine human expertise with AI efficiency, not those trying to choose one over the other.
Soon down the road, at this scale, AI will likely run out of compute capacity too. Recently, in North America, so much push back is coming against new AI data centers. Even, some environmental agencies are scrapping proposals of new AI data centers as studies are out about surrounding environmental impacts of such infrastructures. Even on local computation infra, when we observe the mac mini shortage, it tells the same story, not able to keep up with computation demand. Economics is all about demand and supply & when one gets disbalanced, we know what comes next.
This is why companies should treat AI as a productivity multiplier, not a complete replacement for human talent. The winners will likely be those who balance automation with skilled people instead of chasing cost-cutting hype.
it's ok there's plenty of jobs for police officers and soldiers. Felons do all the manual labor. Utopia is here.
CloudSoft Technology we are hiring
Can we stop this nonsense?
AI is not costly compared to humans. AI is costly because companies are trying to build things at a scale humans alone could never execute.
People has started to use LLM models for simple task automations as well. Identification of genuine use cases and optimizing the usage of tokens using very refined prompt engineering will define the success.
A power tool in skilled hands - that’s the key
Not if you go local. And we are doing exactly that for Indian businesses. Helping them deploy Local AI. Preventing US tech giants from from stealing business ideas, information, pii and everything and making AI available for cheep for Indian companies. Not your LLM, not your AI. Don’t share your business info and customer data to some external black box. Let Zosma AI help you do the same using local ai at scale.
AI is incredibly powerful, but clients today are looking beyond the hype. The companies winning with AI are not the ones replacing people blindly, but the ones combining strong talent with the right AI tools. In sales, relationships, trust, negotiation, and understanding client pain points still require human intelligence. AI can accelerate can accelerate pour workflows, research, outreach, and analytics, but it works best as an enabler, not a replacement.
It is going to take a long time before hiring managers figure this out and they cannot be told this. They just assume you are full of it or are stubbornly clinging to relevance as a developer. Most developers will drop out some of us can just take a year or two vacation keeping resume/CV active and just travel the world a bit in th3 mean time while the industry learns to take their heads out of their rectal cavities.
Human Centric frameworks that puts AI-Forward is a good balance. But orgs who put AI-First without having that Human I. The loop are starting to realize the drawbacks.