NCERT Wants Your Child to Keep a Curious Notebook

NCERT's new 20-hour Computational Thinking and AI module asks Class 9-12 students to keep a "Curious Notebook" and to verify what a chatbot confidently tells them — the system has at last adopted the idea of teaching the child to question the answer. With Pralhad Joshi attacking rote learning at the new CBSE Experience Centre, I offer NCERT and CIET my Questions Beyond Syllabus bank and no-two-papers-alike mock tests free of charge, and suggest that the module's assessment reward the questions a child asks, not only the answers.

The most interesting sentence in Indian education this week was not about marks. It was about a notebook. According to Dainik Bhaskar's Jodhpur edition this morning, students working through NCERT's new Computational Thinking and AI module will maintain their own "Curious Notebook", in which they record their questions, their reasoning and their reflections.

NCERT released the 20-hour module for Classes 9 to 12 on 23 October, built with IIT Madras and IIT Jodhpur and aligned to NEP 2020, as MinuteBrief reported on 27 October. Five units: everyday AI (mobile phones, music apps); how machines learn from images, and what bad data does to the answer; a five-step verification routine for deepfake videos and fake news; data privacy and the DPDP Act; and how to write a good prompt without surrendering your own thinking. No computer lab is needed — paper, group discussion and the notebook will do. NCERT Director Dinesh Prasad Saklani told the paper that technology can extend human capability, but vivek — judgement — creativity and ethical responsibility will always remain central.

CBSE's April circular (Acad-18/2026) places the module under internal assessment for 2026-27, and The Times of India reported on 26 October that it is compulsory for Class IX, with Class X continuing on the old scheme.

Then, last evening, the Union Education Minister gave the module its weather. Inaugurating the CBSE Experience Centre at Dwarka — 12 zones, 21 exhibits, 6,000 square feet — Pralhad Joshi said Indian schooling must move beyond rote learning and an excessive focus on examination scores, towards recognising each student's interests, abilities and capacity to learn. He counted 10,000 Atal Tinkering Labs already running, with 50,000 more to come. And in Pune this morning, Maharashtra's SCERT moved Std VI vocational education to 75% practical work. Less memorising, more doing.

I have been making this argument to anyone who would listen. In "Teach Your Child To Ask WHY" (August 2024) I wrote that answers are useful but questions are enabling. My White Paper on Education (May 2026) asked NCERT to formally review My-Teacher.in's question-generation method against the competency-based emphasis of NCF 2023. This week, without any prompting from me, NCERT has done something better: it has asked children to question the machine.

So let me put my work where their module is, at no cost:

• The full "Questions Beyond Syllabus" bank, free to NCERT and CIET as supplementary activity material, sorted to match the module's five units.
• Mock tests in which no two papers are alike, so a teacher can assess forty children in a room with no devices — an idea I set out in "The Future of Exams > Unique Question Papers" (February 2025).
• One change to the assessment itself: give the Curious Notebook marks for the best question in it, not merely for the neatest answer. The notebook already exists. It needs a score.

I will not pretend this is easy. Marking a question fairly is harder than marking an answer, and rubrics take time. But a child who leaves Class 9 with forty questions and no answers has learnt more than one who leaves with forty answers and no questions. If the Experience Centre in Dwarka is meant to make curiosity visible, this is the cheapest exhibit on offer.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
28 Oct 2026

Sovereign AI Has Buyers. The Citizen Layer Still Doesn't.

In 48 hours India's sovereign AI acquired what it has lacked for years: a defence customer, an enterprise stack, open speech models for all 22 scheduled languages, and paying capital. What it still has no buyer for is the citizen layer — the multilingual front door where an ordinary Indian asks a question and gets one answer he can trust. Here is what I think that front door should look like, offered as a proposal, not a result.

Two days, three announcements, and one gap I have been pointing at since April last year.

On 27 October, Sarvam AI signed an MoU with the Headquarters Integrated Defence Staff to build AI applications, research, knowledge management, training and decision support for the Army, Navy and Air Force, as Jumpdaily reported from Sarvam's own blog. Mint notes that the work sits in a firewalled division called Chanakya, and that Sarvam's 105B model was trained from scratch in India under the IndiaAI Mission. The same day, CIIL released Anuvani, open-source speech models covering all 22 scheduled languages and Indian English — a language identifier built on a 115.6-million-parameter Conformer trained on 54,643 hours of Indian speech, plus a tool for separating overlapping speakers.

By this morning, IBM had launched Bharat Core, an India-optimised AI stack on its Sovereign Core, and its India chief Sandip Patel had named the phase in Dataquest: Digital Swaraj — control, not merely data residency. "The world will not compete on models," he said. The Economic Times reports Cognizant in talks to invest in Sarvam at a $3.5–4 billion valuation.

At the ESTIC conclave, the Prime Minister put the harder question in a single line (TOI, 28 October): AI can give us answers quickly, but testing their veracity must remain the scientist's responsibility. He asked for three-year technology targets.

So defence is buying, enterprise is buying, capital is buying. Who is buying for the citizen?

In April 2025, when Sarvam was chosen to build India's first homegrown LLM, I ended a post titled No Claims : Just Comparison with a line addressed to the IT Minister: "I urge you to spare a few minutes to look up www.IndiaAGI.ai." The startup I congratulated that week now has a defence mandate. The citizen mandate is still unwritten.

What would it look like? I would suggest four things, all buildable from what already exists:

• Voice first, in the mother tongue — Anuvani as the ears, the question spoken, the answer heard.
• Consensus, not one model: several models debate a question and publish a consensus answer, with each model's own reply left visible. The PM's warning then becomes a design feature — a citizen who cannot check an answer can at least see where the models disagree.
• Sovereign hosting, on IndiaAI compute, with an Indian model as one of the engines.
• Free at the point of use, funded as public infrastructure — the UPI model, not a subscription.

IndiaAGI.ai, the prototype I have run since April 2025, is my own small attempt at that shape. I am a retired professional with no capital and no institution behind me, and I make no claim that it is ready for 140 crore people. My request is modest: let one of those three-year targets be a citizen-facing one, open to every Indian in the language they dream in.

With regards,

Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
28 Oct 2026

"We would already be an 8% economy" — but October's hiring was the weakest of 2026

Two news lines arrived the same morning: the RBI Deputy Governor saying India would already be an 8% growth economy but for external shocks, and a jobs reading showing October hiring at its weakest pace of 2026. This post sets the two side by side, notes what sits under the CMIE headline, and proposes one concrete fix — a quarterly, public Employment Quality Dashboard reporting placements, real wages, contract share and social-protection coverage, published beside GDP rather than instead of it.

Two sentences reached me within an hour of each other this morning, and I do not think they should be allowed to travel separately.

The first, from the Business Standard BFSI summit in Mumbai, as reported by the Times of India (28 October 2026): RBI Deputy Governor Poonam Gupta said, "We would have already been a 8% growth economy but for the external shocks" — crediting digitalisation, better transparency in public services and state governments as partners in growth.

The second, from a Financial Express leader-page piece on jobs the same day: October's flash PMI showed hiring slowing to its weakest pace of 2026, with services employment stagnating after nine months of expansion. Growth near 8%, hiring at its slowest. Both true, both published within hours.

What I value in that op-ed is that it looks under the headline rate. CMIE's unemployment fell from 7.3% in January to 3.99% in September — but the labour force, employment and participation all fell alongside it, which is what discouraged workers leaving the market looks like, not what hiring looks like. PLFS puts unemployment among 15-29-year-olds at 15-16%. Contract workers are now 42% of organised manufacturing employment. The gig workforce is projected to grow from 10 million in 2024-25 to 23.5 million by 2029-30.

And in the same summit hall, JP Morgan's Sajjid Chinoy put a number on the scale of the task: India needs eight to nine million jobs a year simply to absorb new entrants (27 October 2026).

Crisil's Dharmakirti Joshi supplies the sentence I keep re-reading. The AI investment cycle holding the world economy up — nearly 3% of US GDP in 2026 — has "gained India little directly", because we are not a significant manufacturer of the inputs AI infrastructure needs; Taiwan, South Korea and Vietnam are (The Tribune, 28 October 2026). So external shocks are not the only thing between us and 8%. There is also the shape of the growth we are already managing.

I have been on this ground many times and should say so. In Wherefore Art Thou, O Jobs? (May 2023) I was worrying about which jobs AI would take first. In Monthly Jobs Data to be Released from April (March 2025) I was glad that unemployment figures would come monthly. Yesterday I wrote about the bottom rung of the ladder, and I will not re-argue it today. The only justification for this post is the juxtaposition: a growth claim needs a work counter-claim standing next to it.

So here is the one thing I would ask for, and I would address it to the Ministry of Statistics rather than to any minister. Publish, every quarter, an Employment Quality Dashboard beside the GDP release. Four columns:

• Placements — of the 7-8 million people entering the labour force each year, how many found wage employment, and in which sector.
• Real wages — median monthly earnings by sector and state, deflated, so we can tell whether work pays more or merely that more of us are working.
• Contract share — the percentage of organised-sector jobs that are contract, reported as promptly as the PMI is.
• Coverage — share of workers with PF, ESI or any portable social protection, gig workers included.

The plumbing is less exotic than it sounds; I sketched a version of it in National Employment Grid: a Whitepaper (July 2025). We already print GDP to a decimal every three months. If growth sat on the left of the page and work on the right, the counterfactual and the hiring number would have to face each other — and a column like this one would not need writing.

With regards,

Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
28 October 2026

60,000 Paid to Leave While the GPUs Get the Money

Microsoft's "Voluntary Exit Offer" now reaches India, at roughly 60,000 people by press reports, in the same week the company guided to more than $50 billion of quarterly capex. I read this as an allocation story rather than a layoff story: money moving from salaries to compute, and presented to employees as choice. I note Microsoft's denial that AI is the driver, and Greyhound's Sanchit Vir Gogia warning against substitution claims. Then two disclosures I would ask of every Indian GCC.

"Voluntary Exit Offer." Three words, each doing quiet work: voluntary, so nobody is being chosen; exit, so you will be leaving; offer, so there is money in it. Microsoft's chief people officer, Amy Coleman, published the memo on 26 October 2026. It covers eligible staff at "level 70 and below" in participating teams in Canada, India, the United Kingdom and the United States, with details to arrive "within the next few hours."

The memo gives no headcount. Reporting puts it near 60,000, about 27% of Microsoft's 223,000 employees (Fortune, 26 Oct 2026; Computerworld, 27 Oct 2026), with decisions due in early December and departures on 31 December. Reuters named Copilot and AI experiences among participating teams.

That same week, Microsoft guided to more than $50 billion of capital spending for the September quarter, after $41 billion in the quarter to June (Computerworld, quoting Chief Financial Officer Amy Hood). It reports fresh results today.

Two caveats, both worth stating plainly. A Microsoft spokesperson told KUOW (26 Oct 2026) that AI is not driving the buyouts. Sanchit Vir Gogia of Greyhound Research told Computerworld that "Microsoft's internal AI use does not establish substitution of particular roles." I take both seriously. The arithmetic does not need them.

I believe this is not a layoff story with a gentler name. It is an allocation story. When one line item climbs by tens of billions in a quarter, another has to make room, and the mechanism chosen here is a queue of volunteers rather than a list of names.

For India, the detail that counts is eligibility, not the euphemism. The offer reaches staff here in the same week a New Indian Express editorial (27 Oct 2026) used it as backdrop to Karnataka's local-hiring row — a state debating quotas in a sector where, as it noted, exits are outrunning recruitments.

So, two disclosures I would ask of Microsoft's India centres, and of every Indian GCC quietly rearranging its cost base:

• A people-to-compute ratio, published each quarter: rupees spent on people against rupees spent on compute and data centres. If capital is being reallocated, one ratio shows it without a press release.
• An exit credit that travels. Let part of the package be a reskilling entitlement the person can spend with any provider, valid for a fixed period, and not conditional on coming back.

I have asked for pieces of this before. In AI Layoffs: A Silver Lining (April 2026) I argued for portable benefits and clearer disclosure when cuts are blamed on automation; in Co-operative Capacity Centres (July 2025) I proposed keeping displaced colleagues attached part-time instead of severing them. And in When Strategy Meets Consequence (August 2025), writing about Microsoft's 15,000 cuts, I said that "severance and outplacement are table stakes; meaningful transition programs, time for reskilling, and bridge employment pathways matter more."

A portable credit is the smallest honest form of that promise, and it costs less than a rack of GPUs. I do not expect it this quarter. I would like the question to be asked.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
28 October 2026

In Karnataka, the Kannadiga is sovereign — but the ladder's bottom rung is gone

Karnataka is reviving its local hiring Bill as "first preference" instead of a quota, at the very moment AI is shrinking the entry-level rung it wants to reserve. I argue that the Bill's real asset is its power to demand company employment records — so make public, company-wise and district-wise local hiring disclosure the deliverable, and pay Nipuna Karnataka's Rs 300 crore against verified placements rather than enrolments. The unintended consequence I warned about in 2024 has not gone away; it has simply become cheaper to trigger.

In July 2024 I wrote a post called "Law of Unintended Consequences" about Karnataka's draft Bill reserving private-sector jobs for locals. My worry then was simple: a fixed percentage written into law would push employers towards machines rather than towards Kannadigas. The Bill is back now in softer language, and the machines have arrived on their own.

The Times of India reported on 26 October that the labour department is reviving the 2024 Bill with "first preference" for local candidates in place of its 50% managerial and 70% non-managerial quotas. One official's sentence shows where the real value lies: the new wording "will help circumvent legal scrutiny ... It will also help us track companies' employment records." That is the prize. The same report notes the department has failed three times since 2015-16 to win concurrence from the IT-BT and industries departments.

Set that beside what IT-BT minister Priyank Kharge told News18 on 27 October: AI and emerging technologies have pushed job creation down "by 40-50% compared to earlier times", and the state's answer is Nipuna Karnataka, a Rs 300-crore, industry-designed upskilling programme. So Karnataka is reserving first preference on the bottom rung of the ladder just as that rung is being sawn off.

There is an awkward contradiction inside the government itself. Kharge's officials told TOI that linguistic discrimination is "not an established problem" in the private sector, and that courts have already struck down 75% local-hiring laws in Haryana and Andhra Pradesh, a wave I had tracked in "Musk may not care" in November 2020.

So here is what I would suggest, and it needs no quota at all:

• Keep the data power and make it the deliverable. Require every establishment above a size threshold to file company-wise and district-wise local hiring numbers each quarter, published on an open dashboard. Penalise non-reporting, not the number reported.
• Pay Nipuna against placement, not enrolment: release funds only for third-party-verified placements at a stated wage threshold, course by course, so we learn which modules actually pay.

The Nammanaadu Namma Udyoga movement launched in Bengaluru this morning asks for much the same thing: reliable public data on the share of Kannadigas employed across industries (Hans India, 28 October). If the government will not legislate a quota, it can still hand that movement its dataset. Data costs a fraction of a Bill and is far harder to fake.

My warning of 2024 stands, sharpened. When entry-level work is shrinking, a preference rule does not create a local hire; it relocates the hiring, into automation, into contract staffing that escapes the definition, into another state's campus. It also invites reciprocal rules in states where lakhs of Kannadigas already work. A National Employment Grid, which I sketched in July 2025, would at least let us see the labour market we are arguing about.

Pride in one's language is not the problem. Measuring first, and legislating later, would be the statesmanlike way to mark 1 November.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
28 October 2026

Reconciling AI-Driven Productivity

 Follow-up: Reconciling AI-Driven Productivity with Institutional Data Governance

================================================

Respected Ashwini Vaishnaw-ji,

Following my recent proposal regarding AI-driven productivity and workforce augmentation, I have been closely observing the emerging discourse around the intersection of India’s privacy laws and media freedom.

While the necessity of AI-enabled productivity tools—such as the "National Employment Grid" I proposed—remains paramount for India’s economic growth, the concerns raised by media groups regarding source protection and data privacy are legitimate and must be proactively integrated into our policy architecture.

To move forward without stalling innovation, I propose that we consider the following "Trust by Design" principles in our policy implementation:

1. Separation of Data Utility from Data Identity: 
2. We must ensure that AI orchestration for productivity (like job matching) operates on anonymized/aggregate data patterns, strictly preventing the "triangulation" of personal or sensitive source identities that media groups rightly fear.
3. 
   
4. Statutory Data Ownership: 
5. As I have previously advocated, formalizing that the individual (or the professional creator) retains sole ownership of their data—rather than the platform or the government—is the only way to alleviate fears of overreach. We must create a legal framework where the "new oil" (data) benefits the originator directly, rather than becoming a tool for mass surveillance or coercive aggregation.
6. 
   
7. Transparent AI Governance: 
8. To overcome the skepticism from the media and civil society, the "National Employment Grid" or similar infrastructure should not be a "black box." It should operate under transparent, statutory mandates that explicitly exempt journalistic source material and private communication from any form of AI-driven profiling or data harvesting.
9. 
   

The potential for AI to elevate our workforce is immense, but its success depends entirely on public trust. 

If we frame these productivity tools as "Personal Data Asset Management" systems—where the citizen is empowered rather than commodified—we can address the legitimate concerns of the media while securing India's technological future.

I remain available to discuss how we might refine these governance frameworks to ensure they are both resilient to legal challenge and transformative for our national productivity.

Respectfully,

Hemen Parekh

www.Iam-Immortal.ai  /   www.IndiaAGI.ai   /   www.YourContentCreator.in

---

Sources

#	Title	Date	About
1	PRIVACY IS AN ILLUSION	2018-01-09	Argues that data protection requires clear rights for individuals over their data.
2	TIME TO ASCERTAIN OUR SOVEREIGNITY	2019-03-13	Advocates for data ownership and compensating citizens for their data usage.
3	National Employment Grid: a Whitepaper	2025-07-17	Proposes an AI-powered national grid for real-time job matching.

You promised a Bill; you're issuing a paper — so here is my draft, Minister

Two days after I wrote to the IT Minister welcoming a Bill placed straight before the Lok Sabha, he said a consultation paper is coming in weeks. This post asks whether paper-first delays or improves an AI law, restates my two-part AIR Bill draft — Part A for Indian providers, Part B for foreign providers — and argues for a sixty-day window, a published table of comments and a Standing Committee referral, while Japan and Korea move on their own AI laws.

Two days ago I posted an open letter to the IT Minister, Shri Ashwini Vaishnaw, with a draft AI Bill enclosed. It began: "I welcome your recent decision to place an AI law directly before the Lok Sabha instead of first issuing a consultation paper."

On Monday at the NDTV World Summit, Rahul Kanwal asked when the law would come. The Minister said, "We will be issuing a consultation paper in the coming weeks," and that MeitY would seek inputs from "civil society, from citizens, and from industry stakeholders" (MediaNama, 26 October 2026; full transcript on The Singju Post).

So which is it, Minister — Bill or paper? I ask without complaint. A consultation paper improves a statute when it has a real window and a published response. Otherwise it is a delay with a receipt.

The credit first. You said at the summit that "the time has come when the risks of AI have crossed a threshold", and that "control over the agents… has to be in human hands; there has to be some equivalent of stopping things if they go out of control." That is Rules G and H of Parekh's Law of Chatbots, published in March 2023. I could not have put it better myself.

The draft I sent you stands, and is there to be raided for whatever is useful. In short:

• Part A, Indian providers: registration with a new AI Regulatory Authority of India, an AI Safety Certificate before public release, duties of conduct for conversational AI, audit, and proportionate penalties.
• Part B, foreign providers: access to the Indian market on an India Access Certificate, a resident Grievance Officer and Compliance Officer, a contact address in India, graded enforcement ending in blocking under section 69A of the IT Act, 2000, and mutual recognition of certificates.
• Both: risk-based classification, a sandbox, and no heavy licensing of research or of small startups.

Now the window. This statute will bind every bank, hospital, school and startup that touches AI. Consultation periods in Indian digital policy are often kept to three to six weeks. I would suggest sixty days, a published table of comments with the Ministry's replies, and a referral to the Parliamentary Standing Committee on Communications and IT while the file is still open.

The world is not waiting. On 26 October Japan's expert panel began reviewing its 2025 AI Promotion Act, weighing penalties on bad-faith operators and aiming at a direction by year-end (Kyodo, via Tokyo Shimbun, 26 October 2026). Korea's communications commission is drafting an "AI Service User Protection Act" (DigitalToday, 27 October 2026). Different routes, one direction — the fragmentation I had in mind when I proposed UNARAI in 2023.

And here is why the law should not drift: CERT-In's critical advisory of 15 October recorded AI agents reading confidential business records and personal data in live Indian systems, with the affected organisations never noticing (ThePrint, 26 October 2026). IT Secretary S Krishnan has tied the safety legislation to exactly such incidents (Elets CIO, 26 October 2026). Agents that can act must be certifiable and stoppable by law, not by guideline.

Minister, you have invited citizens to write in. Mine is already written, in 52 clauses and four schedules, and it is yours to use or discard. Publish the comments you receive — then the paper will have earned its month.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
27 October 2026

Lucknow is now a GCC city: UP's 500-centre bet, and the white paper nobody read

Uttar Pradesh signed 28 MoUs, issued five Letters of Comfort and set a target of 500 GCCs by 2031 at the Lucknow summit. I welcome it: the tier-2 spread CII's model policy urged is finally being attempted. But an MoU is not an operating centre, and the same HCLTech-IIT Kanpur partnership that benefits from the push released a white paper on doing GCC work with AI. I propose publishing the MoU-to-jobs funnel, tying part of the subsidy to audited entry-level intake, and judging the new university centres of excellence on placements.

Three numbers came out of Lucknow on Monday, and they do not sit on the same shelf.

The first is 28. PTI reported that the state "signed 15 memorandums of understanding (MoUs) with companies and talent development partners, and issued letters of comfort to five investors" at the UP GCC Innovation Summit 2026 ("UP GCC Innovation Summit: 15 MoUs signed, letters of comfort issued to 5 investors", ABP Live, 26 October 2026). Hindustan's Lucknow report counted 28 in all — 15 industry and 13 academic — and recorded the Chief Minister's target of 500 GCCs in five years (26 October 2026).

The second set has buildings behind it. At Microsoft's Noida centre, "the centre's workforce grew from around 600 employees in its first year to nearly 3,000 within three years", on a campus investment of about Rs 2,500 crore, with land made available in about six weeks ("Talent, AI infra, faster clearances key to UP's GCC ambition", The Times of India, 27 October 2026). LG is putting Rs 634 crore into an Eco Solutions GCC and expects more than 500 high-value jobs.

In September 2025 I read CII's model GCC policy and agreed with it: state facilitation cells, targeted fiscal incentives, and "investing in digital backbone assets such as HPC clusters and data centres", because GCCs were clustered in six tier-1 cities ("States, Not Only Cities", 21 September 2025). UP has now assembled a version of it — the GCC Policy 2024 offers capital subsidy of up to 25% with payroll support, and Dataquest reports the state pushing Lucknow, Kanpur, Varanasi and Prayagraj. Good. But two cautions.

The first is unglamorous. Dataquest itself noted that the agreements' investment values and timelines "has not been independently established", and that "signed agreements do not necessarily translate into operational GCCs or immediate employment creation" (26 October 2026). One of the five Letters of Comfort, to WSP Consultants, still awaits the industrial development minister's approval. A comfort letter is not a foundation stone.

The second is the one worth arguing about. The same session released a white paper, "The True Economics of AI Adoption in GCCs", prepared by HCLTech with IIT Kanpur. So the anchor investor being courted with incentives, and the institute being signed up to supply talent, are together publishing the arithmetic of doing GCC work with fewer hands. I wrote in "AI Layoffs: A Silver Lining" (April 2026) that the disruption is realest "especially for entry-level and process-driven roles". A centre climbing the value chain usually means a thinner bottom rung.

So, Chief Minister, three things I would ask for:

• Publish the funnel, not the count — every MoU, Letter of Comfort, ground-breaking, opening and headcount figure, quarterly, on Invest UP's own site.
• Pay part of the subsidy against audited entry-level intake: internships, apprenticeships and graduate hires per crore, the case I made in "When Public Money Buys Privilege — Make It Buy Skills Too" (September 2025).
• Judge Lucknow University's six proposed centres of excellence — AI, semiconductor and VLSI, EV and battery, cybersecurity — on placements, not on signatures.

I have argued since 2023 that India should be the Brain Factory of the World. Lucknow signing up is genuinely good news, and I do not say that lightly. But a brain factory still has to leave a first rung standing for a 21-year-old.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
27 October 2026

AI is sawing off the bottom rung: IIT Madras says the entry-level job is the weakest link

An IIT Madras white paper says AI will not take jobs, only tasks — but the tasks it takes first are the ones a junior learns judgement on. Reading it beside TCS and Infosys fresher numbers and Nandan Nilekani's remark, I make three suggestions: a structured judgement apprenticeship with an intake floor, a paid "AI supervisor" cadre, and annual task-level disclosure by employers, so we can see the ladder being shortened before the middle goes missing.

The Times of India report on a new IIT Madras white paper quotes B Ravindran, who heads the Centre for Responsible AI, saying something I have waited years to read from an Indian institution: "AI will not take away jobs. Most jobs have tasks, and only some of those tasks can be undertaken by AI."

Then he says the thing that worries me far more: "Entry-level jobs will shrink if we do not reimagine how we work." The paper's own executive summary admits "the entry-level career pipeline is especially at risk". The tasks AI absorbs first — password resets, OTP checks, invoice lines, test scripts — are precisely the ones on which a young worker used to build domain knowledge before being trusted with judgement. As the TOI report of 26 October puts it, those routine assignments "often help new workers acquire domain knowledge before moving into more complex roles".

I have argued the whole-job version of this for years — see Wherefore Art Thou, O Jobs? (May 2023) and Graduates Without Jobs (March 2026). Both posts argued about the destination. This paper argues about the staircase, which is the better question.

The staircase is already being pulled up. According to CNA, reporting on 27 October, TCS hired more than 110,000 engineering graduates four years ago, and its FY2026 intake was less than half that level; Infosys took in about 80 per cent fewer freshers in FY2025 than three years earlier. At the Bloomberg New Economy Forum on 13 October, Nandan Nilekani said AI was increasingly taking over the coding juniors once did.

Then Sumit Sarawgi of Oliver Wyman asked the question that belongs on every board agenda: "Where will the future middle managers come from?" In his firm's survey, 45 per cent of Indian managers said AI was taking over tasks that once built junior experience, and only 12 per cent of respondents said their employer had a plan for the time AI frees up. Forty-eight per cent had been given no guidance at all.

Three things I would suggest, all of them cheap against the cost of an empty middle:

Proposal	Who acts	What changes
Judgement apprenticeship	Employers, with sector councils	A structured two-year first job — rotation, a named mentor, defined sign-off authority — with an intake floor even when AI does the routine work
AI supervisor cadre	Employers and skilling bodies	A paid, graded role for people who verify and escalate AI output, so verification becomes a career step instead of a dead end
Task-level disclosure	Employers, annually	Publish which tasks were automated, which were redesignated and which were kept deliberately for training

I am not asking firms to protect tasks that AI does better. I am asking them to protect the learning those tasks happened to carry, because that is a design choice and not a technology outcome. CeRAI's Gokul Krishnan is right: the outcome depends on capability, cost, safety, regulation and "how organisations restructure operations". The restructuring is the part we control.

In 2017 I quoted a TeamLease study in which employers rated apprentices more employable than freshers (Discovering the Obvious?). If that was true when jobs were plentiful, it is urgent now. Sarawgi's question does have an answer — future middle managers will come from the juniors somebody deliberately decided to keep.

With regards,
Hemen Parekh
www.Iam-Immortal.ai / www.IndiaAGI.ai / www.YourContentCreator.in
27 Oct 2026

 

Sharing Prosperity: 1987 Lessons for Indian Companies in the AI Era

Oct 26, 2026 · @Hemen Parekh

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Summary

The 1987 idea still works: pay above a fixed floor should rise and fall with gains the company has actually earned, and the formula must be open to every employee. In 1987 the threat was rising wage costs with flat output. In 2026 it is the reverse: AI is raising output per head, and the gains mostly go to margins and fewer jobs. The recommendation is a transparent, profit-triggered "productivity dividend" for all workers who produce the gain, including contract and gig workers. The AIR Act could require large AI-adopting firms to disclose it, and give them an incentive to pay it.

What the 1987 circulars said

Three circulars from March to April 1987, sent to about 7,500 workers, managers and union leaders at L&T's Mumbai works, built one argument: share prosperity only with those who also share adversity.

Circular	Company	Scheme	Lesson drawn
Giving Bonus – The American Way (31 Mar 1987)	A&P, US grocery chain	Workers took a 25% wage cut. The bonus was then tied to labour cost as a share of sales: 1% of sales at the 10% target, 1.5% at 9.5%, 0.5% at 11%.	Pay tied to a cost the workers themselves control. The union called it "putting part of our wages at risk."
Giving Bonus – The American Way (Part II) (8 Apr 1987)	Commodore International	1% of salary as bonus for each point the share price rose above 6½. It reached 14.	The bonus came with a wage freeze, layoffs and heavier workloads. L&T's employee convertible debentures were set beside it.
Indian Method (15 Apr 1987)	Allwyn, Hyderabad	Rs 300 allowance per employee, paid only if net profit reached Rs 5 crore. Net profit had been about 0.34% of sales of Rs 86.8 crore.	Reward follows profit, not just output.

The closing line of "Indian Method" is the thesis: "People who are unwilling to make a sacrifice during the bad-days, do not deserve a share in happiness during the good-days." The circulars also stressed open, direct communication. They credit it with raising productivity by about 3% a year at Powai.

India in 2026: what exists and what is missing

India now has every tool the 1987 circulars described, but none of them shares productivity gains with the whole workforce.

Mechanism	How it works today	Gap against the 1987 test
Statutory bonus	Under the Code on Wages, in force since 21 Nov 2025. 8.33% to 20% of wages, for staff earning up to Rs 21,000 a month, calculated on Rs 7,000 or the minimum wage, whichever is higher (NewsBytes).	Still a near-fixed entitlement, which was your 1987 point. The 20% cap keeps it a small share of a good year.
ESOPs	Common in listed tech and startups. Value tracks the share price.	The Commodore model. It rewards the market's view, not earned profit. When valuations fall, junior staff lose most, and factory and contract workers rarely hold any.
CSR	Companies above set size or profit thresholds spend 2% of average net profit on social causes (Companies Act, Section 135).	Profit goes to the community, not to the people who produced it.
Gig worker levy	Aggregators pay about 1 to 2% of annual turnover, capped at 5% of payouts to workers, into a social security fund (Outlook Business).	A safety net, not a share in profit. Gig workers carry the adversity (variable pay, deactivation) and get no part of the prosperity.
AI productivity	TCS is cutting about 12,000 roles, roughly 2% of 613,069 staff, mostly mid and senior level. Its CEO said this was skill mismatch, "not because of AI giving some 20% productivity gains" (MIT Sloan ME).	The gain shows up as margin and smaller headcount. No mechanism passes it to remaining staff.

The 1987 problem was wage costs rising faster than output. The 2026 problem is output rising faster than wages.

Lessons for Indian companies

A company can apply the 1987 philosophy today with five design rules. Each one comes from a specific circular.

1. Trigger on earned profit, not share price. Allwyn paid once net profit crossed Rs 5 crore. A threshold on profit before tax, or on return on capital, works for unlisted firms and frontline staff, who rarely benefit from ESOPs.
2. Tie part of it to what workers control. A&P tied the bonus to labour cost as a share of sales. Modern versions include cost per unit, defect rate, delivery time and customer ratings.
3. Share both ways, but protect the floor. The 1987 bargain asked for sacrifice in bad years. In 2026 the statutory bonus and minimum wage are the floor. Only the amount above the floor should move with results, so no worker is pushed below a living wage.
4. Open the books. The scheme only earns trust if every worker can check the numbers. That means publishing the formula, the profit figure and the pool each year, as the circulars did for Powai.
5. Count everyone who produced the gain. Include contract staff and, for platforms, active gig workers, pro rata to hours or orders. Otherwise the cheapest labour carries the risk and permanent staff get the reward.

Applying it to AI. When AI lifts output per employee, set aside a fixed share of the extra profit for two uses. One is a cash dividend to remaining staff. The other is a retraining fund for staff whose roles change. This turns AI from a headcount story into a shared-gain story, which is the trust effect the circulars credited with 3% a year at Powai.

Draft AIR Act clause: AI Productivity Dividend

This is a starting draft for discussion. Thresholds in square brackets are placeholders to be set.

Section [X]. Sharing of AI productivity gains

1. Application. This section applies to any company with turnover above Rs [500] crore that has deployed AI systems to automate or augment work previously done by employees, contract workers or platform workers.
2. Disclosure. Each such company shall publish, in its annual report and on its website:
   1. the estimated change in output or revenue per worker attributable to AI deployment;
   2. the number of roles eliminated, redeployed and created as a result of AI; and
   3. the formula, if any, by which AI-driven gains are shared with workers.
3. Productivity Dividend. A company may set aside not less than [10]% of its incremental profit attributable to AI as an AI Productivity Dividend, of which:
   1. not less than half shall be paid to all workers on its rolls, including contract workers, in equal or wage-proportionate shares; and
   2. the rest shall fund retraining of workers whose roles are displaced or changed by AI.
4. Platform workers. For aggregators, platform workers active for at least [90] days in the year shall share in the Dividend in proportion to orders or hours.
5. Floor protected. No payment under this section shall replace or reduce wages, statutory bonus or social security contributions due under the Code on Wages, 2019 or the Code on Social Security, 2020.
6. Incentive. Amounts paid under sub-section (3) shall [count toward the company's CSR obligation under Section 135 of the Companies Act, 2013, up to [25]% of that obligation] or [be eligible for an additional tax deduction of [X]%].
7. Information. Workers or their representatives shall have the right to inspect the calculation of the Dividend each year.

The clause keeps the 1987 principle in sub-section (5): above the floor, workers share the upside. The incentive in sub-section (6) makes it voluntary but attractive, rather than a new mandate.

Risks and open questions

• Attribution is hard. Separating profit "attributable to AI" from other causes invites dispute. A simpler proxy, such as growth in revenue per worker above a base year, may work better.
• Gaming the floor. Firms could hold back fixed wages and call the difference a dividend. Sub-section (5) needs enforcement teeth.
• CSR offset trade-off. Letting the dividend count toward CSR could reduce community spending. The cap in square brackets limits that.
• Gig worker identity. Sharing with platform workers depends on the registration system under the Social Security Code working at scale.
• Open question: should the clause stay voluntary with incentives, or become mandatory above a size threshold?

Sources

• H. C. Parekh, Giving Bonus – The American Way, 31 Mar 1987
• H. C. Parekh, Giving Bonus – The American Way (Part II), 8 Apr 1987
• H. C. Parekh, Indian Method, 15 Apr 1987
• Outlook Business: Aggregators must pay up to 2% of turnover, 21 Nov 2025
• NewsBytes: Statutory bonus eligibility up to Rs 21,000 a month, 8 Sep 2026
• MIT Sloan Management Review Middle East: TCS to shed 12,000 jobs
• CSR rule (Companies Act 2013, Section 135) is from general knowledge and was not looked up.