Category Archives: Etc.

From Khadgam to Chatbots: Letting Go, Leveling Up, and Loving the AI Ride

From Khadgam to Chatbots-image created by author and ChatGPT-5

“Roads? Where we’re going, we don’t need roads.”
— Back to the Future (1985)

1. Letting Go of the Old Model

Sticking to your old mental model—your tried-and-tested habits—is like refusing to give up a horse and buggy when Teslas are whizzing past. We cling to the familiar because it’s comfortable, but in AI adoption, that comfort zone can be a trap. Whether it’s how you work, how you communicate, or how you solve problems, if you keep doing things “the old way,” you’ll be left behind in the digital dust.

2. Transformation Fatigue Is Real

Even when people are open to change, organizations often overload them with AI tools and mandates—without enough context or support. The result? Transformation fatigue: a quiet killer of enthusiasm where teams feel exhausted and distrustful. As one recent report put it, “AI’s problem isn’t the tech. It’s trust” (TechRadar Pro, Aug 2025). Gradual rollouts, real training, and clear communication matter far more than flashy launches.

3. The Experience Paradox

In Khadgam, Prithvi proudly says he has “30 years’ industry experience.” But if those decades were just spent replaying the same script, is that really experience? In AI adoption, true experience comes from evolution, not repetition. It’s about outgrowing your current role, experimenting with new tools, and—even if it stings a little—making parts of your job redundant so you can focus on higher-value work.

4. The Skills Gap and Adoption Lag

Across Asia—and especially in India—skill shortages remain a serious hurdle. A recent study found that 58% of Learning & Development leaders cite skill gaps and slow AI uptake as their biggest challenge (TOI, Aug 2025). Without structured upskilling, AI risks becoming another expensive tool gathering dust.

5. The Infrastructure Reality

AI isn’t just a chatbot in your browser—it’s GPUs, data pipelines, storage systems, APIs, and energy costs humming in the background. Choosing the right infrastructure—cloud, hybrid, or on-prem—can make the difference between scalable success and a costly dead end . This decision needs both technical foresight and financial prudence.


A Fun Wrap-Up

Adopting AI isn’t a one-off switch—it’s an ongoing mindset shift. You don’t have to become a machine-learning engineer overnight, but you do have to:

  • Let go of outdated habits.
  • Build trust, not just compliance.
  • Redefine what “experience” means.
  • Close the skill gap.
  • Strengthen your tech foundation.

Because in the end, AI’s role isn’t to replace us, but to elevate us—if we’re willing to take the ride.

“Train to be a plumber.”-Geoffrey Hinton

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(Above image generated using a prompt from Claude Opus 4 and ChatGPT-4o)
(Below Snippet from summary generated using Google AI studio+Gemini 2.5 Pro (free), using the youtube transcript)

Final Messages & Outlook (1:17:19 – 1:19:33, 1:24:08 – 1:25:39, 1:28:10 – End)

  • To World Leaders: We need “highly regulated capitalism.”
  • To the Average Person: Individual actions have limited impact (like separating plastics for climate change). The key is to pressure governments to force large companies to invest heavily in AI safety research.
  • Call to Action on Safety: There’s still a chance to figure out how to develop AI that won’t want to take over. Enormous resources should be dedicated to this, because if not, AI will take over.
  • Hopefulness: He is “agnostic” and genuinely doesn’t know the outcome. When depressed, he thinks humans are “toast”; when cheerful, he thinks “we’ll figure out a way.”
  • Urgency: “Unless we do something soon, we’re near the end.”
  • Plumber Advice Not a Joke: He reiterates his earlier advice seriously, as plumbers are well-paid and their physical work is harder for AI to replicate soon.
  • Other Concerned Experts: He notes a surprising number of people within the AI field now share his concerns but are less public, perhaps due to ongoing employment. He, being older and retired, can speak more freely.

(Below snippet from summary generated using Claude opus 04(paid))

Advice and Predictions

Career Advice in AI World

  • “Train to be a plumber” – physical manipulation jobs safer longer
  • Paralegal assistants won’t be needed much longer
  • Wealth inequality will increase dramatically
  • Universal Basic Income might prevent starvation but won’t provide purpose/dignity

For Those in Power

  • Need “highly regulated capitalism”
  • Force companies to use resources for safety research
  • Current politicians don’t understand technology
  • International cooperation needed but unlikely

For Average People

  • Not much individuals can do
  • Like climate change – not solved by recycling
  • Can pressure governments to force companies to work on AI safety

Timeline Predictions

  • Superintelligence: possibly 10-20 years (maybe less, maybe 50)
  • Job displacement: Already happening
  • University graduates already struggling to find jobs
  • CEO example: Company reduced from 7,000 to 3,000 employees due to AI

Hope for the Future

  • “There’s still a chance” to develop safe AI
  • Should put “enormous resources” into safety research
  • Personally “agnostic” about outcomes
  • When depressed: “people are toast”
  • When cheerful: “we’ll figure out a way”

Key Quotes and Analogies

  • “If you want to know what life’s like when you’re not the apex intelligence, ask a chicken”
  • On superintelligence taking over: “We need to figure out how to make them not want to take over”
  • Mother-baby analogy: Evolution made babies control smarter mothers through crying
  • Tiger cub analogy: Must ensure it never wants to kill you when grown
  • On human specialness: “We thought we were at the center of the universe… white people thought they were special… we just tend to want to think we’re special”
  • Final warning: “We have to face the possibility that unless we do something soon, we’re near the end”

Current State of AI Leaders

  • Some privately believe in dystopian future but lie publicly
  • Motivated by power more than money
  • Sam Altman previously said AI “will probably kill us all,” now says don’t worry
  • Disconnect between public statements and private beliefs

Final Message

The biggest threat to human happiness is joblessness – people need purpose and to feel useful. Mass unemployment is “definitely more probable than not” and is already beginning. Urgent action is needed but the political systems are “all going in the wrong direction.” His advice if you don’t have money: “Train to be a plumber.”

Full video–>https://www.youtube.com/watch?v=giT0ytynSqg