Moving From Cost Arbitrage To Innovation Arbitrage.
Edition #175
Introduction
Welcome to The ContraMind Code.
The ContraMind Code provides you with a system of principles, signals, and ideas to aid you in your pursuit of excellence.
The newsletter shares the source code through quick snapshots for a systems thinking approach to be the best in what you do.
The Code helps you reboot and reimagine your thinking by learning from the best. It also enables you to draw a blueprint for what it takes to get extraordinary things done. You can share your valuable thoughts and comments and start a conversation here.
Take a journey to www.contraminds.com. Listen and watch some great minds talking to us about their journey of discovery of what went into making them craftsmen of their profession, to drive peak performance.
Is All Micromanagement Bad?
When you become a leader, you believe you don’t want one thing your boss or manager probably did to you - micromanage. Many of us have grown up hearing this advice - ‘Don’t ever micromanage if you really want to get the best out of people.’ Is micromanagement really as bad as it is made out to be? When you become a leader of a team or a manager, or a senior leader, the compelling reasons for you to do it hit you hard. This article in First Round Review breaks traditionally held myths around micromanaging.
Here are some key thoughts on why, how and when to micromanage effectively!
“One good way to use micromanagement is for standard setting and demonstrating the calibre of thought, work and effort that you want to see,” - Jack Altman, Co-founder Lattice.
"Leaders shouldn’t live in the dashboard. When the anecdotes disagree with the data, you've got a problem. You have to go and see for yourself.” - Matt MacInnis, COO, Rippling.
“It was about improving the work rather than questioning the strategy. Set 20% and 80% checkpoints.” - Krithika Shankarraman, Stripe.
“ Great managers are like porpoises, the aquatic mammals that can swim at both the surface and the depths of the ocean” - Mike Brown, Uber.
“The number one way that I see new engineering leaders struggle when they come into a new place is that they assume the context from their previous company applies as is,” - Will Larson, CTO, Imprint.
“I am hands-on until I trust you. Once I trust you, I’m hands-off and we’ll collaborate as you need me or when I bring you ideas for us to work through together,” - Jay Desai, Former Founder and CEO, PatientPing.
“Instead of giving people a list, good leaders offer them a box and fill it with interesting ideas.” - Michael Lopp, Apple Engineering Leader
You can read the entire article here.
What Is An AI Agent?
Today, there is so much chatter around Agentic AI that it is important to first define, distinguish, and differentiate what an AI Agent is. This episode in the a16z podcast provides a good perspective on this.
Here are some thoughts on AI agents that were shared in this conversation:
“An agent is just something that does complex planning and something that interacts with outside systems.”
An agent, according to Anthropic, “this is an LLM in a loop with a tool”
“The LLM takes the output of a prompt, feeds it back into itself and based on that, makes decisions on what the next prompt should be.”
“It's like a multi-step LLM chain with a decision tree.”
“There's one type where the agent is replacing humans, work with humans. There's the other type of agents as more low-level system processes. They work with each other, they hand off tasks to each other.”
“How should companies think about pricing their agents? Per seat?
Per token? Per task? Price(It) based on the margin, but price based on the value you add, whatever that could be(Is key).”
“The winners will be the specialists, not the foundational models. It's the people who will build on top of the foundational models, who are fine-tuning the foundational models.”
“If you just think of it as normal, right, like water or electricity or the Internet or things like that, I think that's the world we're kind of headed towards. An agent is this kind of way to help us get there.”
You can also listen to the entire episode or learn more about AI agents on:
How Work From Anywhere Will Transform Businesses - Prof. Raj Choudhury, Harvard Business School
The COVID years permanently changed the way businesses functioned and how people worked. More recently, there has been a push to ‘Back-To-Office’ by leading companies, and there has been resistance and backlash against these policies. What we really need is answers to the following questions:
“What is the best definition and effective process of working from anywhere?”
“Does working away from the office really improve or deplete productivity?”
“Can companies remain the way they have hired and employed people over the last 100 years without any HR policy changes or transformation?”
“What support does work from anywhere need from local governments?”
“Finally, what kind of work ethic, work culture and maturity do people have to develop if they want more companies to embrace work from anywhere?”
This conversation, which is a two-part series between Prof. Raj Choudhury, Harvard Business School and Indrajeet Gupta, Founding Fuel, provides a lot of answers and insights to these questions.
You can click on the above link and watch the video.
Moving From Cost Arbitrage To Innovation Arbitrage.
Listening to ‘What is AI Agents’ and watching the video conversation ‘The World is your office’ fueled a lot of thoughts and ideas.
There seemed to be one common theme that was emerging, we are currently going through an era of convergence of technology and workplace transformation. This kind of change happens once in 100 years, and this is really when virtually new cities, new industries and new job profiles emerge and get built.
For example, take the scenario when the Industrial Revolution happened, Manchester(UK), Birmingham(UK), Glasgow(UK), Lowell, Massachusetts( USA), Detroit(USA), Pittsburgh(USA), Essen(Germany), and Osaka(Japan) were built. New industries threw up new work-related skills that were required, leading to new jobs like factory workers, machine operators, mechanical and civil engineers, railway workers, coal miners, telephone operators, clerks and typists, automobile engineers, etc.
The same thing happened when the tech and internet revolution took place, leading to creation of new cities like Silicon Valley(USA), Shenzhen (China), Ho Chi Min(Vietnam), Bangalore(India), Tallinn (Estonia), Dubai(UAE) and new job profiles like Computer programmers, IT technicians, System Analysts, Electronic engineers, etc. emerged. The business and jobs moved to geographies where cost arbitrage provided a huge advantage to businesses like China and India, when it came to manufacturing, programming, etc.
However, cost arbitrage is not sustainable forever as wage growth, quality of life and aspirations rapidly change during these phases of hyper-growth. Between 1865 and the 1930s, the US resembled the low-cost economies of today, but soon had to shift gear to become an innovator to sustain high wages and plateauing productivity output. China has gone through this phase and is transforming itself into an innovator in areas like automotive(electric vehicles), AI(Deep Seek), etc.
Similarly, India needs to pivot from being a cost-arbitrage economy to an innovation arbitrage economy. This requires a fundamental transformation in thinking, research & development and application innovation. India can no longer afford to ‘throw people’ at problems, because AI Agents, as and when they get mature, will do the jobs at a far more cost-effective price and value. India’s workforce productivity is abysmal, and therefore, unit costs of output are increasing every day. There will be newer job profiles that will emerge, like digital twin specialists, smart factory technicians, drone operators, etc. This requires a mindset shift in moving from ‘low value work’ to ‘high value work’.
The US missed the opportunity of ‘Skill Transformation’ of its workforce and is facing a deep crisis today. For example, as of 2023, it is estimated that the United States employed approximately 12.9 million workers in the manufacturing sector and about 139,400 computer programmers. This resulted in a ratio of roughly 93 factory workers for every 1 computer programmer. When manufacturing jobs vanished in the US and technology jobs emerged, it led to a serious workforce crisis.
Similarly, India needs to manage this transformation, and the hard truth is that the responsibility lies with each one of us. Businesses will move their operations to where they can make more profit and grow stakeholder value. India will need to build ‘smart cities’ with the right digital and social infrastructure that can house digital twin specialists, smart factory engineers, etc.. All of them first need to have a deep and extensive domain knowledge of managing high-value jobs remotely. Workplace professionals of the future need to compete with the world’s best not on price but on value.
Any country’s research and patents inventory, which will drive this kind of innovation, needs to radically scale, including those of India. For example, today the US has 1,801 patent applications per million people, China has 1,191 patent applications per million people, and India stands at 45 patent applications per million people. India needs to rejig its workforce mindset and innovation ecosystems.
The brutal reality is that it needs to start at an individual level. Even a mature economy and country like the US could not manage this skill transformation change at a policy level. It’s the private players - companies, educational institutions, working professionals themselves - who have to drive this transformation. Otherwise, India will face the ‘Factory worker-Programmer per million crisis’ that the US faces today.
Countries, including China and India, need to move from a ‘Cost-Arbitrage’ economy to an ‘Innovation Arbitrage’ economy.
Each one of us at work needs to move away from a ‘scarcity-led cost arbitrage’ mindset to an ‘expertise-led value arbitrage’ mindset. Geographies, paying a premium due to scarcity of available resources and costs, may cease to matter anymore. Work will move to where expertise resides.
Some of the lessons we learnt from this week’s mission:
Micromanagement is not the problem. Adding value and inspiring people is more important than simply micromanaging their day-to-day tasks and deliverables.
An AI agent is a multi-step LLM with a decision tree. It does complex planning and interacts with external systems.
Companies need to prepare themselves for a world where work from anywhere will become the norm.