You Are Still the Wine
Why the agent economy will reward depth, trust and accountability, not merely the ability to build.
By Rinoo Rajesh · 15 October 2026 · 7-minute read
Earlier this week, a post on my feed set out nine predictions about how AI will change the way we work. It was crisp, provocative and, in places, uncomfortably accurate. One line stayed with me long after I had scrolled past it: the agent is the bottle; you are still the wine.
I have spent more than twenty-five years watching technology waves arrive with the promise of replacing people: telecom automation, IVRs in contact centres, offshore delivery models, RPA and now generative and agentic AI. Each wave genuinely changed the work. None of them removed the need for someone to stand behind it.
That, I believe, is the real story of the agent economy. Not that machines will do the work, but that accountability will become the scarcest and most valuable thing a professional can offer.
AI will make capability abundant. It will make accountability precious.
01 · The work moves. The responsibility does not.
I largely agree with the first prediction. The spreadsheet, the report, the code, the first draft of almost everything: much of this will soon be produced by AI agents rather than by people working line by line. In my own work with enterprises, I already see agents drafting proposals, reconciling data, summarising customer interactions and preparing first-cut analysis in minutes rather than days.
Yet we should be careful not to confuse the production of work with the ownership of outcomes. A regulator does not ask which model generated a credit decision. A customer does not care which agent misrouted a complaint. A board does not accept “the system recommended it” as an explanation. In highly regulated sectors such as banking, insurance, telecom and healthcare, every material output must eventually trace back to a human being who is answerable for it.
The execution layer may become largely autonomous. The accountability layer will remain stubbornly human.
02 · Trust becomes the price signal
The post predicts that companies will pay for agents much as they pay salaries today: monthly, recurring and tied to work done. I think this is directionally right. Many of us are already moving from licence-based to outcome-based commercial models, and agents will accelerate that shift.
The more important insight is what determines the price. Raw capability will be cheap and everywhere. Every organisation will have access to broadly similar foundation models. What will differ is what sits inside the agent: proprietary data, institutional memory, domain judgement and the reputation of the person or firm that stands behind it.
The example of the Chartered Accountant captures this perfectly. An agent built by a CA with twenty years of tax judgement is valuable not because of the model underneath, but because of the thousands of client situations, edge cases and regulatory interpretations that have shaped how it reasons. The model is the engine. The judgement is the fuel.
For enterprises, this has a governance implication. If agents are going to be priced like employees, they must also be managed like employees, with defined roles, clear owners, performance reviews, escalation paths and the ability to be retired when they no longer serve the business. An agent without an accountable owner is not an asset. It is an unmanaged risk.
03 · A power-law economy, and what it asks of institutions
The prediction that professional income will follow a creator-economy curve rather than a salary curve deserves serious reflection. A small number will build agent empires. A larger middle will earn well in narrow niches. Many will earn only a little.
We have seen early versions of this pattern before, in app stores, on content platforms and in the gig economy. What is new is that it may now extend into professions that were once protected by credentials and scarcity of expertise.
The post goes on to suggest that governments will need to tax the agent economy and redistribute its gains, perhaps through some form of Universal Basic Income. It also mentions the more radical view that productivity could grow so fast that money can be created and distributed in abundance without causing inflation.
I would approach the second idea with some caution. Abundance in goods and services is plausible in many sectors. But housing, land, healthcare, quality education and human attention will not scale at the speed of software, and prices in those areas will continue to reflect their scarcity.
Redistribution may well become necessary. It will, however, require careful policy design, fiscal discipline and strong institutions, not merely faith in technology.
For a country like India, with its scale, demographic dividend and diverse economy, this is not an abstract debate. How we prepare our workforce, design our social safety nets and ensure that the gains of AI reach beyond the most privileged pin codes will shape the next chapter of our growth story.
Technology can create abundance. Only institutions can make it fair.
04 · Working on the machine, not in it
Perhaps the most practical prediction is that people will still work, but the shape of work will change. We stop being the doer and become the trainer, the editor and the quality controller of our agents.
This transition is familiar to anyone who has led large transformation programmes. The best project managers rarely do the work themselves. They define outcomes, set standards, remove obstacles, manage risk and decide when something is good enough to ship.
In many ways, the professional of the agent era will need the instincts of a good project leader: clarity of intent, discipline in review and the judgement to know when to intervene.
The skills that matter will therefore shift:
- From producing to specifying. The quality of an agent's output depends heavily on the clarity of the instruction and the context it receives.
- From doing to reviewing. Spotting what is subtly wrong becomes more valuable than producing what is broadly right.
- From individual effort to orchestration. Coordinating several agents, data sources and human stakeholders becomes the core of the role.
- From compliance to stewardship. Ensuring that outputs are fair, explainable and aligned with organisational values becomes a daily responsibility, not an annual audit.
05 · Multiply zero and you get zero
The line I found most powerful in the post was this: AI multiplies what you already have, and if you multiply zero, you get zero.
In my conversations with founders and enterprise leaders, I often see the opposite assumption. There is a belief that building agents is itself the moat. It is not. Building is becoming easier every month. Platforms, frameworks and no-code tools are rapidly democratising the ability to create an agent.
The real differentiators will be what cannot be easily copied:
- Rare knowledge: deep, contextual expertise accumulated over years.
- Rare data: proprietary, well-governed datasets that reflect real-world complexity.
- Rare trust: relationships and reputation that make customers comfortable relying on your output.
- Distribution: access to the customers and communities who need what you offer.
This is equally true for organisations. An enterprise that has not invested in clean data, sound processes and a culture of accountability will find that AI amplifies its weaknesses just as efficiently as it amplifies its strengths.
Transformation does not begin with the agent. It begins with the foundations the agent will stand on.
06 · The premium on the human
The final prediction may prove the most enduring. As machine-generated work becomes the default, “made with real humans” will become a premium.
We will pay more for the teacher who knows our child, the doctor who listens before prescribing, the advisor who has walked with us through difficult decisions, and the craftsperson whose work carries a story.
This should not surprise us. When something becomes abundant, what remains scarce gains value. In an age of infinite content, presence, empathy and judgement will be the new luxuries.
So what is the practical advice for an ordinary professional? I agree with the post's conclusion.
It is not simply to learn to build agents. It is to become genuinely excellent at something narrow and real: tailoring, surgery, tax, teaching, sales, tennis or any craft that rewards depth. Then find ways to bottle that excellence, so that it can serve many more people than you could ever reach alone.
To this, I would add one more responsibility: stand behind what your agents do. Put your name on their work only when you are prepared to answer for it. In the years ahead, that willingness may be the most valuable credential any of us carries.
The agent is the bottle. You are still the wine. Make sure it is worth pouring.
The future of work will not be decided by how intelligent our machines become. It will be decided by how wisely, responsibly and purposefully we choose to use them, and by whether we invest in becoming people worth multiplying.
Rinoo Rajesh
Technology and business transformation leader, entrepreneur, author and professional-community builder
#FutureOfWork #AgenticAI #AILeadership #ResponsibleAI #HumanJudgement #DigitalTransformation #CreatorEconomy #RinooRajesh
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