The Time Portfolio: Why we struggle to invest in our OWN future!

Over the years, I’ve noticed something uncomfortable about how most of us spend our time — including myself.

We talk about strategy, long-term thinking, compounding, capability building. We admire investors who think in decades. We celebrate companies that invest ahead of the curve. But when it comes to our own time, we behave very differently.

I’ve begun to look at time the way I look at capital — as something that must be allocated deliberately. And through that lens, most daily activity falls into three buckets:  

Equity. Debt. Indulgence.

This simple framing has changed how I look at my calendar.

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1. Equity: The Work That Compounds

Equity activities are those that increase future optionality. They don’t scream for attention. They don’t trigger escalation emails. They don’t create instant applause. But they compound.   Thinking deeply about next year’s architecture. Learning a new domain. Writing. Designing systems. Building relationships before you need them. Investing in health. Reading something difficult.

None of this is urgent.  All of it is powerful.  The problem? Equity rarely feels dramatic in the moment. It often feels slow, quiet, even lonely.

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2. Debt: The Work That Prevents Damage

Debt activities are obligations that need to be served.  They keep the wolf away from the door.  Responding to clients. Closing compliance loops. Reviewing reports. Attending review meetings. Putting out fires.  Ignore Debt and you will feel the pain quickly. That’s why it dominates.

Debt doesn’t compound much — but it prevents collapse. And because it is visible and measurable, it gives the illusion of productivity.  Most of us are very good at Debt.

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3. Indulgence: The Work That Feels Good Now

Indulgence is more subtle today than it used to be.  It’s not just leisure. It’s endless scrolling. Reactive email checking. Attending meetings that don’t require your presence. Consuming more than creating. Being “busy” without building.  Giving into to every distraction that comes from real or digital world.

It feels rewarding in the moment. It relieves boredom. It reduces anxiety. Delivers your dopamine dose,  But unless consciously restorative, it erodes focus and future leverage.

Not to say this is waste of time, but serves purpose if taken in measured deliberate dose only.

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The Uncomfortable Truth

If you don’t consciously manage your time portfolio, it will naturally skew toward:

Debt + Indulgence.

Not because you lack ambition. But because the world is structured that way.

Urgency pulls you.

Notifications pull you.

Expectations pull you.

Fatigue pulls you. 

But …Equity rarely pulls. It must be chosen.  And choosing it often means disappointing someone in the short term — including your own craving for stimulation.

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Why This Is So Hard

In my own experience, three forces make Equity difficult:

1. Immediate pressure always feels louder than future gain.

   Ignoring an email hurts today. Ignoring learning hurts later.

2. The world rewards responsiveness more than reflection.

   Being available is visible. Thinking deeply is invisible.

3. Energy declines through the day.

   By evening, Indulgence becomes easier than Investment.

Left unattended, the system drifts itself — not toward growth, but toward reaction.

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The Real Question

The shift happened for me when I stopped asking, 

“Was I productive today?” and started asking:   Did today increase my future optionality?

I now try to follow three small disciplines:

• Declare one Equity action in the morning. Protect it.

• Pause midday and ask: Am I reacting or compounding?

• End the day by asking: Did today make tomorrow easier or harder?

No spreadsheets. No perfection. Just awareness.

When I skip this reflection, Debt and Indulgence takes charge.

One thing I have stopped doing is to make single mixed list of all todo activities and prioritise them…three different lists for three different objectives. 

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Self-Reflective Questions

I’ll leave you with a few questions I continue to ask myself:

• What is my honest split of time allocated across three buckets?  How far is it from where it should be? 

• If I removed all urgency, what would I choose to work on?

• Which recurring Debt can be systemized or delegated?

• What indulgence am I rationalizing as productivity?

• Does my calendar reflect the future I want?

• If I continue allocating time exactly as I do today, where will I be in three years?

Time cannot be saved.  But it can be invested.  And like capital, it compounds only when treated with intention.

Reflect!

THINK and ACT like Agentic AI: Learnings from the MCP Framework

Problem-solving is at the heart of every business decision, strategic initiative, and personal breakthrough. Yet, mosteven seasoned professionals — do not do it well, consistently and with desired impact, But we expect our digital agents to deliver solutions to our needs with perfection, always.  At least that is the endeavor behind designing the working of Agentic-AI. 

Machines are inherently dumb, and hence seek full intent clarity, modular decomposition, integration and interdependence protocols, data sources & linkages, optimization function and desired output format to deliver against the problem or request asked of them.  No gaps or skipping of steps allowed!  Hence machines do need to rely on framework, like MCP to gather requirements and deliver outcome in a structured stepwise process.  

I believe even humans will do much better problem solving if we employ MCP framework in our problem-solving approach in a systematic and disciplined manner. 

Multi Component Pipeline (MCP) framework, as the name suggests, breaks down a problem into a sequence of discrete, interlinked components, each responsible for a specific transformation, decision, or analysis or action, and collectively taking the process from problem to recommendation 

Let us do a quick tour through these components:

1. Problem Definition layer: Agent command requires a crisp articulation of the problem with boundaries, context, and measurable goals.  In fact, lots of effort is made to get the intent rightly converted into proper prompt.  Do we insist on same level of shared clarity of the problem, or rush into action basis vague understanding of the expectations?

 

2. Decomposition Engine: Seldom is the real-life complex problem solvable within one module or function or domain.  This component breaks the main problem into sub-problems or modules. It involves deliberate analysis of possible contributors to the problem and defining logical structure, dependencies, and execution order of components

 

3. Input Interface Layer and Preprocessing: Here the focus is to specify exactly what data is needed for each step, and how it should be transformed.  Agents then gather and validate required data, and transform raw input into structured, usable formats.  Given the access Agent has to infinite set of data points, it is paramount for Agent to clearly define the purpose and format for each data point.  Contrast this to our approach, where it is either data deluge, by gathering all available data, or data drought, wherein the assumption is of either data not there or incorrect 

 

4. Task Execution layer: These layers involve equivalent to module leaders or subcomponent leads executing the specific sub-tasks, such as analysis, classification, or routing and creating intermediate outputs.  The clearer the task is the more efficient the delivery.

 

5. Reasoning / Aggregation Layer and Explanation Generator: This component integrates intermediate outputs from task modules and applies rules, heuristics, or logic to compose overall coherent conclusions.  Insights may come from different fields including heuristics, quantitative analysis, best practices, empirical evidence, scientific research and this layer collates outputs.  Further explanation generator produces interpretable outputs, with rationales and confidence levels against each set of conclusions.  

 

6. Recommendation Engine: MCP clearly differentiates the reasoning layer and the recommendation layer, helping creation of multiple recommendations against conclusions.  This component maps conclusions to each actionable outputs, such as decisions, next steps, alerts, or strategy recommendations, and present recommendations with priority or ranking.  As user, if you are looking for accuracy or for variety, you can indicate Temperature level accordingly during the prompt itself.  In our problem-solving approach, we too would gain to ascertain the level of accuracy or creativity expected from the answer, and keep discipline in separating the conclusion and 

 

7. Output Delivery Layer: This component formats and sends final output to the designated system or user, such as a UI, dashboard, workflow tool, or report.  A bit of thinking on how user would prefer to consume the outcome, will greatly enhance the impact and reduce rework.  Choices of charts, words, depth of data, sequencing of arguments, and tabulating of recommendations greatly influence the quality of the recommendations as viewed at the end.

 

8. Governance & Audit Layer: This component logs inputs, processes, versions, and decisions for traceability, compliance, and accountability. It often includes versioning and role assignments.  The discipline of maintaining evidence of decision inputs, decision contributors and influencing assumptions in documented traceable form is essential requirement, often forgotten unless specifically traced to closure.

 

9. Decision Feedback & Learning Loop: To me this component is the most powerful part of the MCP framework.  Based on the results, one can trace and identify components that needs strengthening by updating parameters, models, or resources linked to that component.  The evolution of problem-solving capabilities over time is embedded in the framework itself.  

 

Most of our daily life problem solving approaches fall into avoidable traps: poorly defined problem statements, inadequate or noisy data, uncoordinated module outcomes, jumping to conclusions, or delivering recommendations in unconsumable formats. 

MCP is truly a meta-cognitive scaffold and its adoption as problem solving framework would enhance clarity, objectivity, rigor, explainability, traceability, and acceptance to human endeavors, as much as it does for Agents.

Machine Human collaboration path starts with defining guidelines

Humans are in the driving seat, so get to decide the rules of the collaboration setting. However, as the arrangement evolves, machines may also start taking autonomous execution and restricts flexibility.  

   

Overarching principles and design guidelines 

1. At all times, HR has to be aligned with business goals and organisational stated values.  Talent is a key strategic asset, and its acquisition, growth, deployment for business goals is the core non-negotiable accountability.
2. Building a positive work environment, with shred sense of equity and fairness to maximize productivity and satisfaction remains core.  
3. Accountability towards Legal, ethical, and policy compliance across geographies, especially in multi-sector environments, is non-negotiable.
4. All decisions recommended by Machines (AI) should be explainable and may require human review — especially in critical or ethical contexts. 
5. There should be Intelligence-Led Decisioning ie decisions to be informed by predictive insights, prescriptive analytics, and scenario modeling provided by machines.
6. Agent-Led Execution of the repetitive and logic-based tasks. There is openness to redefine the present processes, workflows and decision rights to make tasks amenable to agent led delivery.  
7. Continually strive towards hyper-personalisation, based on profile, experience, interest, intent, and opportunity capture
8. High standards of Digital Ethics and Transparency supported by Clearly define data boundaries, model transparency, and ethical standards for use of employee data and AI-led decisions
9. Modular & Platform-Based Architecture, allowing for easy integrations with other systems and introduce agents. 
10. Reimagination and experimentation approach supported by feedback loops to continue evolving and moving on the evolution trajectory
11. Pace and realm of transition to accommodate employee's adaption challenges, keeping intact trust while managing negative associations like privacy concerns, algorithimic bias or over de-humanisation. 
12. There is always human escalation path available for any automated processes.      

Translating these principles and guidelines into action would require setting up new institutional structures like joint ethics and governance committees and cross functional teams, enhanced role of CHRO, CDOs and other leaders.  

Besides, this would require reimagining of the role of HR workforce as they share their work with machines going forward.       

Handing over to Machines : The Why and why-not Question?

Like all dimensions of work, the conventional work done by Human resource professional is also under scanner and expected to be given to, fully or partially, to machines.  

The prime motivation is to leverage the tireless energy, unbiased application of decision rules, immense retrieval and computing capabilities and NLP based interactions of new set of digital technologies (RPA, AI ML, Chatbot, Agentic-AI) for the good of employee, managers and organisation.  

The Why-Machine question?

The key motives for introducing machine power in HR context hovers around the following:

1 If Talent is the strategic asset, then machines help identify, acquire and deploy this asset better, and more efficiently. It can provide fitment score. predict the performance outcome, attrition risk and often provide the hidden talent option that is hidden in the remote work location.    

2 If employee experience at workplace is to be as good and personalised as at market-place, we can emulate same solutions for validation, interaction, recommendations and transactions, chatbots for example.    

3 If trust, transparency and auditability behind routine transactions are important, machines deliver better and at scale, using RPA as a disciplined agent.   

4 If machine releases cognitive capacity of the workforce, by taking over routine and rule-based decisions, why not? And machine capacity to adjust to scale is far more than of workforce. 

5  If the outfall of mistake by machine is manageable and not disproportionate from ethical, reputational and economics consideration, lets go ahead.   

In recognition of the above, over 70% big corporations are using machines in HR for some purpose or other.  

The Why-Human question?

At the same-time, need for putting Human in the loop is often felt: 

1 If the decision or action would create negative consequence, (say disciplinary action, dismissal), human judgement is warranted?

2 If there is less confidence in defending explainability of decisions or actions by machines to externl party, keep Human in the loop

3 If the empathy and emotions are as important as the content of the interaction for employee satisfaction, oblige

4 If the reliability of the data sets driving transcations and decisions are a suspect, let humans decide

5 If the decisions require case-2-case considerations with high level of contextual and subjective discretion, humans are not replaceable.

Moving work from humans to machines has to be a deliberative, and structured transition, ensuring coordinated readiness around policies, processes, technology and people dimensions, to make it seamless and well recived by stakeholders.         

What is state of your mental Health? A self-check toolkit.

 While we go for regular physical health check-ups, even if otherwise ok, we seldom do mental health checkup! Authors cum practitioners  like Alain De Botton, Dan Arley, Adam Grant, Jordan B Petterson and Browen Berne, do share some insights which can often be collated as barometer for self-checking the state of ones’ mental health. I wander what would a self-check mental health barometer looks like!  

Shy of asking Chatgpt or google, here is my list:

1 Are you able to consciously edit various thoughts emerging in your mind, to select the empowering ones and discard the debilitating ones?  It does not entertain thoughts that reminds us of our unworthiness or fuel the feelings of regret, remorse, resent or conceit.               

2 Are you able to retain the general trust in goodness of humanity and reconcile with selfish acts at the individual level?

3 Can you resist the temptation of comparisons to others, either to feel good or bad?

4  Recognize the unreasonableness of cheerfulness as the only desirable end-state state, and any other as sub-optimal?  “Worldy” people are likely to be less happy than they seem. 

Albrecht Durer (1493)

5 Realise that every explanation that looks plausible may not be real, and that randomness could as well be the real reason?  Not every unsuccessful man is so, because of laziness or stupidity.

6 Able to compartmentalize thoughts and emotions and maintain sense of proportionality of response to the situation.

7 Able to recognize fear as state of being and mange it through recognition and additional dose of curiosity. 

8 In quest of seeking more, not to undermine what is already there.  Recognize that Every situation has the possibility of being worst! Can you express gratitude to crashed pillow that ensures good night sleep.   

9  Once in a while you remind oneself of transience nature of being, and its insignificant presence at cosmic level.

10  Are you comfortable with laying boundaries in relationships and can utter warm sounding but definitiveno, without affecting prevailing level of affection 

11 Appreciate the role of genes, parenting, and early childhood experiences in shaping us, but not hold to these convenient factors to defend your learnt helplessness or laziness.

How much you score and what is the ranking criteria- I cant say- but may be there is some realization where to focus to strengthen our mind!

AI: Powerful Strategic Lever- Define its purpose, plan and deploy it RIGHT

Book is general purpose read on how AI is being used by variety of organization, and understandably these are at different levels of maturity in their leverage of AI for business benefits.

Authors rightly argued three major strategic objectives in using AI: Creating new offerings, Transforming Operations and Influencing Consumer Behavior. Calling out influencing behavior capabilities as distinct objective makes it easy to measure the effectiveness of AI intervention, while the second order benefit may reflect in revenue gains, brand loyalty or reduced cost of serving customers.

AI domain itself comprises multiple type of technologies, classified under Statistical Machine learning, Logic based systems and semantics- based AI, making choice of right technology or combination of two technologies to develop solution becomes critical decision point in AI journey. Different technologies have different uses, and fully evolved AI-fueled organizations may have different combination of AI technologies being applied to address different use-cases.

Authors rightly argues that the effective use of AI need not be full replacement of human effort say by automating the insurance claims for car accidents or designing driverless automobile, but equally by solutions that augment human effort, by providing suggestions and timely assistance. The stories of Morgan Stanley Next BEST Action System and Guardian driver assistance System by Toyota illustrate this strategy quite powerfully.

Business value comes from AI in production and that also when embedded in workflows. Pilots, prototypes and proof of concepts are good for learning but deployment demand much more- planning, data and system integration approach, capacity creation, disruption management and resource commitment.

Interestingly successful cases referred in the book, have CXO level sponsors who had good hands on personal experience in the technology and deep appreciation of need for patience and sustained effort on road to AI-fueled transformation.

People readiness approach towards AI presents challenges, especially coming out of lack of sufficient clarity on the impact on current roles on account of AI infusion, including future in-house capability and capacity requirements. Unprepared communication around AI programs are likely concerns around employment continuity for the existing staff. At the same time, efforts required to upskill and redeploy staff in AI-fueled set-up demand early start.

If you are serious about AI, you need to be serious about Data. Most companies have major data management projects underway along or prior to taking AI program, The more proprietary data you can leverage and multiple data sets you can uniquely combine, more differentiated AI outcomes and potential value creation opportunities shall emerge.

Authors have listed use cases of AI across various industries in a very concise bird view manner – covering both the established and emerging use-cases. Given the interest in this subject, there is too much material available across channels on AI- be it published books, free articles, websites and you-tube videos. Where this book scores is providing the holistic view and supporting with real use cases and some experiential insights.

It is good read for early learners in this area, to be followed us with deeper study (elsewhere) in any particular aspect that one finds interesting and relevant.

Megatrends : known threats but include hidden opportunities too…..

Nourel Roubini has pointed out to ten trends that have the potential to hugely redefine our future- and more so in a negative way. Author sees the inevitable coming of stagflation, which is going to be severe and prolonged because of economic decisions taken historically that promote debt and lead to boom-bust cycles, and recent government and central banks' fiscal and monetary responses to meet COVID challenges.

Megathreats emerging from demographic, geopolitical, environmental, and technological fields, with the potential to realize simultaneously, will further exacerbate the situation by imposing supply and demand side shocks to the economy

Some of these threats are well known, and to that extent, the book doesn’t add much to the literature related to these areas. For example, issues coming out of strained China relations, increasing protectionism and changing trade patterns, the growing burden of an aging population and shrinking workforce, the multi-dimensional impact of climate changes, advancement in AI and its impact on employment, weaponization of Dollar and its implications on currency markets, and dangers of crypto-currency going mainstream. These are complex topics that are being intensely debated and researched elsewhere and to that extent, it is not fair to expect the author to be hugely insightful and original in analyzing these trends.

While the book lists what all is and can go wrong, it provides very little guidance or ideas on how to arrest the situation. Author's recommendations for averting these mega-threats are bordering more on hope than a structured plan or a specific set of interventions. His viewpoint that 5 to 6% growth in advanced economies, will help to come out of economic mess hinges on assumption that prosperity generally helps tide tough situations better, and also reduces conflicts. How to make economies that are traditionally growing at 2-3% double their growth rates? And doing it in a way that doesn’t worsen the debt trap, create bubbles, sustain employment, increase inequality etc etc.

Further prosperity distributive mechanisms need to be equally strong, given the toxic effect of inequality on peace in the society, and providing universal basic income type of interventions may not be enough.

Expecting technological innovations to come to the rescue by significantly improving productivity and making growth green, climate-friendly, and sustainable is stating the obvious. Accelerating the speed of innovation and mainstreaming its use in a fragmented world with commercially diverse interests and diverse strategic priorities, is another challenge- so much evident during the recent CoVID Vaccine development and distribution game being played at the global level.

The author has analyzed the global macro-trends with a predominantly American perspective, with some references to Europe and China. Clearly, the implications of these trends may not be equally severe or threatening for all countries across the globe.

Seeing from India's perspective, the decoupling of US- China, demographic shift, changing role of global currency (USD), and shifts in global supply chains. the growing movement towards green technologies and rise of AI may actually be MEGA-BOOSTERS, creating immense opportunities and driving next phase of growth.

As rightly suggested by Roubini, we should recognize the need for revisiting one’s traditional investment portfolio (60:40 Equity-Debt) to potentially include short-term bonds, Gold, and Real-estate, as these are likely to help protect capital in uncertain and inflationary scenarios better.

In short, while the book does reasonable justice to listing the dark sides of major global trends, it severely falls short of any new and fresh advice on how to handle these threats and lessen their likelihood to materialize and improve society’s resilience to manage the overall impact. 

Are you more like Mr Evolving or Mr Comfort in your focus and actions?

My worry is that he has started spending too much time discussing those who got lucky? 

A Comment by Manager about his team member during talent review meeting made me think!

Everyday we indulge in multiple interactions with colleagues at workplace for work and ancillary purposes.  In our engagement set, includes those who are above and those below us in organizational hierarchy- ie seniors and junior folks.

Similarly, we may classify these folks as more or less competent than us, and this classification is purely personal, based on individual assessment of others competence in comparison to self! 

These two parameters combined puts all the fellowmen we interact with, into four categories.  How and how-much one interacts with people in each category, helps one get labeled as from Mr Evolving or My Comfort camp.

Mr Evolving has his set of friends like Mr Positive, Mr. Enthusiast, Mr. Trusting, Mr. Learning, Mr Curious and Mr. Experimenter, who together share certain set of characteristics when deciding how much time is to be spent with colleagues placed in each quadrant and 

what set of assumptions would drive those interactions.

What is the most differentiating feature is this  camps focus on encouraging and respecting competence across levels with intent to learn and also mostly under-playing the role of luck in driving outcomes. They do not spend effort or energy on arguing too much on so-called system aberrations or difficult to fathom deviations.  

 

 

 

Contrast this to Mr Comfort, who has friends like Mr Sceptic, Mr Justifying, Mr. Precedence,  Mr. Avoidant, would spend most of their time in lower quadrant seeking assurance of their competence level from those below and also presenting oneself as the under-valued, victim of the system, making selective convenient reference to those above in hierarchy.

 

  

Indeed, leaders of both the camps are effective communicators, use good set of examples in support of their PoV and display immense ability to sway loyalty and grow their followers base.  

Unless, seen in the form of pattern, each of the arguments presented by these leaders appeal as persuasive, realistic and worthy of merit. 

Like most of us who say hello to all colleagues, we may also be spending some time with members from both the camp and do attempt to understand their perspective.

But do we really know, which camp is our resting place? For it matters in the long run. And unless consciously resisted, the shift to Mr Comfort camp may happen without much notice.

Is our understanding of position same as that our colleagues associate with us? When was the last we validated this?

Here is a self-revealing exercise:  

1. How is the total time split across four quadrants?

2. How often is luck or system referred to as reason to justify outcomes (positive or negative)?

3. How often have I advocated competence enhancement as step to growth? 

4. How many conversations have been about gaining new experiences with associated discomfort? 

5. Is there NEED to rebalance time allocation and attention shift from Luck to Competence?    

Be in the camp of your choosing and not luck…it matters !

I am a CEO too……………..So are you!

Everyone is a CEO of the organisation called “myself” .  Do we live like one and how effectively? Is the key question.

Corporate world has put CEO term at high pedestal, with so much of aura, mystique attractiveness, and expectations attributed to this word.  Most of us are not, nor will we, get to wear this title in our lives.  What does it mean- is all advice and research around CEO excellence and effectiveness not of any use to us? 

And now that we don’t wear that title, can our expectations from ourselves be any lower? Not really. 

How about living our lives as CEOs of our respective organizations called “myself”. 

Are we steering our “Self” organizations using similar frameworks and practices that we expect formal CEOs use to run professional organizations?

Consider the following:

1    Effective CEO defines and displays what the organization stands for…..consistently.  Have we defined our personal values, priorities and aligned our behavior is sync with the same?  Are we comfortable making trade-offs in line with stated goals and priorities? Have we defined the our brand preposition or have we left world to interpret us as per their convenience?

2    Effective CEO is clear about the performance measures that matter and is rigorous in their evaluation.  Have we defined balance scorecard equivalent, that covers various dimensions of life- social, health, wealth, etc, both for the short and long term?  Do we keep keen eye on our assets and liabilities and have established objective ways of measuring their strengths continually? Are we honest and strong enough to acknowledge to ourselves the true picture or readily accept convenient explanations?

3    Effective CEO monitors and adapts to the ever-changing demands of ecosystem:  Do we spend time understanding the context and needs of all set of stakeholders (parents, kids, neighbors, colleagues etc.) and have designed way to engage with them?  How sharp are our abilities to sense weak signals and shifts, and how dynamic are we to realign to the changed situation?

Above three are illustrative nudges that will provoke one to define the personal agenda to transform into an effective CEO.

In essence, being a CEO means embracing few non-negotiables, and being prepared to live by them: ie

Accepting Accountability for outcomes (its consequence of one’s choices with no-one to blame),

Engage in Continuous Learning (and reinvention, while tied to Values) and

Respect and Humility (whatever the provocation)

Take charge and experiment living like a CEO of “Myself” for a week and share your feedback with fellow CEOs!