Let Children Explore: Free Online Resources for Kids Under 11 to Discover Their Passions

Every child has the potential to discover something they love. One child might enjoy drawing, another might be fascinated by space, while another might spend hours building things, solving puzzles, dancing or inventing imaginary worlds.

But how does a child discover what they truly enjoy? They need opportunities to try different things.

Parents do not need to enrol their children in expensive classes or purchase specialised equipment to get started. The internet offers a wealth of free learning resources that can help children explore art, music, science, coding, storytelling, gardening, chess and many other activities from home.

The goal is not to turn every child into an expert. It is to let children explore different possibilities, discover their interests and gradually develop the skills they enjoy.

1. The Importance of Exploration Before Specialisation

Children under 11 are still discovering the world around them. Their interests can change quickly, and something they find fascinating today might not interest them a few months later.

Instead of expecting a child to choose one activity and stick with it for years, parents can provide opportunities to explore several activities before deciding which ones deserve more time and attention.

For example, a child might try drawing, chess, music, gardening, storytelling, coding and simple science experiments over several months. They may discover a love for drawing and gardening while deciding that chess and coding are not for them.

That is perfectly fine. Exploration has helped the child discover personal preferences without unnecessary pressure or expense.

Trying different activities also gives children opportunities to develop creativity, patience, problem-solving skills, coordination, communication and confidence.

2. Explore Art, Drawing and Creative Crafts

Art is one of the easiest activities to explore at home. A pencil, paper and a few colours can provide hours of creative opportunities.

Free Online Resources

• Art for Kids Hub: Step-by-step drawing tutorials covering animals, cartoon characters, objects and much more. Website: https://artforkidshub.com/
• Tate Kids: Art games, creative challenges and activities that encourage children to explore artistic ideas. Website: https://www.tate.org.uk/kids
• Origami Way: Instructions for creating paper animals, shapes and other objects through origami. Website: https://origamiway.com/

Try this at home: Ask the child to draw an animal, create a paper toy or invent a character. Display the finished work and encourage the child to explain the idea behind it.

3. Discover Music, Singing and Rhythm

Children can begin exploring music even if the family does not own a musical instrument. Rhythm, melody and sound can be discovered through singing, clapping, tapping and experimenting with digital music tools.

Free Online Resources

• Chrome Music Lab: Interactive experiments that let children explore rhythm, melody and sound. Website: https://musiclab.chromeexperiments.com/
• Musicca: Free tools for practising musical notes, rhythm, ear training and basic music theory. Website: https://www.musicca.com/
• Hoffman Academy: Piano lessons and music-learning videos, with free lessons alongside additional offerings. Website: https://www.hoffmanacademy.com/

Try this at home: Let children create a rhythm using claps, household objects or simple percussion instruments. They can also experiment with creating their own melodies using a digital music tool.

4. Explore Coding and Game Creation

Coding is not only about preparing children for future technology careers. It can also teach them to break problems into smaller steps, think logically and create something of their own.

Free Online Resources

• ScratchJr: A visual programming app designed for young children, generally around ages 5–7, to create interactive stories and animations. Website: https://www.scratchjr.org/
• Scratch: A free programming environment where children can create games, animations and interactive stories using visual blocks. Website: https://scratch.mit.edu/
• Code.org: Beginner-friendly coding lessons, puzzles and computer science activities. Website: https://code.org/

Try this at home: Encourage the child to create a simple animated story or a game in which a character moves around the screen. The objective is to create something, not merely complete a lesson.

5. Discover Chess, Puzzles and Strategic Thinking

Games that require planning can help children practise patience, pattern recognition and decision-making. Chess is one option, but logic puzzles, mazes, memory games and strategy games can also be useful.

Free Online Resources

• Lichess: Free chess games, puzzles and training tools. Website: https://lichess.org/
• ChessKid: A child-focused chess learning platform offering lessons and puzzles, with some features subject to account or subscription restrictions. Website: https://www.chesskid.com/

Try this at home: Introduce a simple chess puzzle, a maze or a building challenge. Let the child experiment with different solutions rather than immediately showing the correct answer.

6. Become a Young Scientist or Inventor

Children are natural question-askers. Why does a shadow change size? How do plants grow? Why do some objects float while others sink? What makes a paper aeroplane fly?

Parents can encourage this curiosity through simple experiments and age-appropriate science resources.

Free Online Resources

• NASA Space Place: Space, astronomy and Earth science activities designed for children. Website: https://spaceplace.nasa.gov/
• Exploratorium Science Snacks: Hands-on science activities that demonstrate scientific principles using practical experiments. Website: https://www.exploratorium.edu/snacks
• PhET Interactive Simulations: Free interactive simulations for exploring scientific and mathematical concepts. Website: https://phet.colorado.edu/
• Tinkercad: A free browser-based tool for exploring 3D design and basic circuit modelling. Website: https://www.tinkercad.com/

Try this at home: Build a paper bridge, test which objects float in water, grow a crystal-growing kit only with appropriate adult guidance, or design a tower using cardboard and paper. Ask the child to predict what will happen before testing the idea.

Adults should supervise experiments, especially those involving water near electrical devices, heat, chemicals, sharp tools or small objects that could be swallowed.

7. Explore Gardening and the Natural World

Gardening gives children an opportunity to learn about living things through direct experience. They can observe seeds germinating, compare leaf shapes, measure plant growth and understand the importance of water, sunlight and soil.

Free Online Resources

• KidsGardening: Gardening projects, educational activities and ideas for involving children in growing plants. Website: https://kidsgardening.org/
• iNaturalist: A platform for documenting and exploring observations of plants, insects and other living things. Website: https://www.inaturalist.org/

Try this at home: Grow coriander, fenugreek or beans in a small container. Let the child record when the first shoots appear and observe how the plant changes over time.

Even a small balcony, windowsill or suitable container can provide a starting point.

8. Develop Storytelling, Drama and Communication Skills

Children can learn to express themselves through storytelling, role-playing, puppet shows and short presentations. These activities encourage imagination and help children practise speaking, listening and organising their thoughts.

Free Online Resources

• StoryWeaver by Pratham Books: Illustrated children's stories in multiple languages, including Indian languages. Website: https://storyweaver.org.in/
• Drama Notebook: Drama games, theatre exercises and improvisation activities, with free resources alongside paid materials. Website: https://www.dramanotebook.com/

Try this at home: Ask the child to tell a story about an imaginary animal, act out a favourite story or create a puppet show using paper and household materials.

Children who are comfortable doing so can also give a short presentation about a favourite toy, animal or book to family members.

9. Explore Dance, Yoga and Physical Activities

Not every extracurricular activity needs to involve sitting in front of a screen. Movement-based activities help children develop coordination, balance, body awareness and an appreciation for physical activity.

Free Online Resources

• GoNoodle: Movement breaks, dance activities and mindfulness exercises for children. Website: https://www.gonoodle.com/
• Cosmic Kids Yoga: Story-based yoga and mindfulness sessions for children. Website: https://www.cosmickids.com/

Try this at home: Follow a short dance routine, practise simple balance poses or create an indoor movement challenge with safe, open space.

Choose activities appropriate to the child's abilities and avoid movements that cause pain or discomfort.

10. Learn Practical Life Skills and Cooking

Extracurricular learning can also involve everyday skills. Children can learn to follow instructions, organise their belongings, measure quantities, care for plants and participate in age-appropriate household tasks.

Cooking is an especially useful activity because it combines mathematics, observation, sequencing and practical problem-solving.

Try this at home: Let the child wash fruit, assemble a sandwich, measure ingredients for a simple recipe or prepare a fruit salad with adult assistance.

Adults should handle knives, hot surfaces, appliances and other hazards. Check for food allergies and supervise the entire activity.

11. Explore Astronomy, Geography and General Knowledge

Children can travel through their imagination and explore the wider world without leaving home. They can learn about planets, countries, animals, historical places and different cultures through educational websites and virtual experiences.

Free Online Resources

• NASA Kids' Club: Space-themed educational activities and games. Website: https://www.nasa.gov/learning-resources/nasa-kids-club/
• National Geographic Kids: Information about animals, nature, geography and the environment, along with quizzes and activities. Website: https://www.natgeokids.com/
• Google Arts & Culture: Explore art, museums, cultural heritage and historical collections through digital experiences. Website: https://artsandculture.google.com/

Try this at home: Choose one country, planet or animal each week. Find out three interesting facts, draw a picture and explain what was learned to another family member.

12. A Three-Month Exploration Challenge

Parents can make exploration a simple family activity rather than another source of pressure. One approach is to introduce one new activity each week for three months.

• Month 1 – Create and express: Try drawing, paper crafts, music, dance and storytelling.
• Month 2 – Investigate and solve: Try chess, puzzles, coding, gardening and simple science experiments.
• Month 3 – Build and discover: Try model-making, cooking, astronomy, geography and a creative project of the child's choice.

This is only a suggested sequence. Children can choose activities in any order, repeat favourites or skip activities that do not interest them.

At the end of each week, ask three simple questions:

• What did you enjoy most?
• What would you like to try again?
• Is there something new you would like to explore next?

Parents can maintain a small activity journal with the child's drawings, photographs of completed projects or a few sentences about what was learned. This creates a record of the child's exploration without turning it into a competition.

13. Choosing the Right Activity for Your Child

Different children may enjoy different activities, and their interests can change as they grow. The following table provides possible starting points rather than strict age limits.

Age group	Activities to explore
3–5 years	Drawing, singing, dancing, simple puzzles, storytelling and gardening with adult help
6–8 years	Origami, chess basics, beginner coding, simple science experiments and cooking with supervision
9–10 years	Scratch projects, music practice, model-making, astronomy, nature journaling and more complex strategy games

Children can start earlier or later depending on their interests, abilities and developmental stage. There is no need to rush them into activities intended for older children.

14. Free Resources Do Not Always Mean Zero Cost

The websites listed in this article provide free learning materials, tools or activities, but their entire offerings may not always be free. Some have paid memberships, premium lessons or optional products.

Parents should check the current terms of each resource before using it. A free online lesson may also require materials such as paper, pencils, cardboard or craft supplies.

Fortunately, many activities can be started using everyday household items. Children do not need expensive kits or specialised equipment to begin exploring their interests.

Parents should also supervise internet use, review age suitability and check privacy settings before allowing children to use websites or apps independently. Where possible, prioritise activities that lead to hands-on learning away from the screen.

Conclusion: Let Children Discover What They Love

The purpose of extracurricular activities before the age of 11 is not necessarily to produce a chess champion, a coding expert, a musician or an artist. It is to give children opportunities to discover what interests them and learn how to practise something they enjoy.

A child might explore ten activities and continue with just two. That is a successful outcome. The other eight experiences may still have taught the child something valuable about the world or about personal preferences.

Parents do not have to identify a child's talent in advance. They can provide opportunities, encourage curiosity, offer guidance and allow interests to develop naturally.

Online resources make this process more accessible by providing free tutorials, activities and ideas. Families can start small, use what they already have at home and gradually discover which activities are worth pursuing further.

Let children explore several activities. Give them the freedom to experiment, the time to practise and the confidence to choose their own interests.

Sometimes, the most valuable thing a child learns is not a particular skill, but the joy of discovering something new.

Free Online Learning Resources for Kindergarten Kids: A Parent's Guide

Every child deserves the opportunity to learn, explore and discover the world without parents having to spend a fortune on educational apps, subscriptions and workbooks.

Fortunately, the internet offers a wealth of free educational resources for young children. From learning to count and recognise shapes to discovering the alphabet, reading stories, solving puzzles and exploring science, parents can create a rich learning environment at home using these resources.

This guide brings together useful websites, apps and digital libraries for children in preschool, nursery, kindergarten and the early primary years. The focus is on resources that parents can access for free, with notes wherever some features require payment or registration.

1. Mathematics and Number Skills

MathEasily – Simple Mathematics Practice

Website: https://www.matheasily.com/

MathEasily is a useful starting point for parents looking for straightforward mathematics practice. It can complement a child's schoolwork and provide additional opportunities to practise mathematical concepts.

Best for: Supplementary mathematics practice and reinforcing concepts introduced at school.

Khan Academy Kids – Mathematics and Much More

Website: https://learn.khanacademy.org/khan-academy-kids/

Khan Academy Kids is a comprehensive early-learning resource designed for children aged 2–8. It includes mathematics, reading, language, stories, creative activities and social-emotional learning. Its family app is free, without advertisements or subscriptions.

Best for: Counting, number recognition, shapes, early addition, reading and general school readiness.

Topmarks – Early Years Mathematics

Website: https://www.topmarks.co.uk/

Topmarks offers interactive educational games, including activities for children aged 3–5. Children can practise counting, recognising shapes, identifying patterns and developing early number skills.

Best for: Interactive mathematics games and short practice sessions.

K5 Learning – Printable Worksheets

Website: https://www.k5learning.com/Free-preschool-kindergarten-worksheets

K5 Learning provides free worksheets covering letters, sounds, numbers, counting, shapes, colours, early writing and introductory science. Some additional content and membership features are paid.

Best for: Parents who prefer printable worksheets and paper-based learning activities.

2. Reading, Alphabet and Phonics

Starfall – Learning to Read

Website: https://www.starfall.com/

Starfall introduces children to letters, letter sounds, phonics and early reading through interactive activities, stories and songs. Its core Learn-to-Read material is free, while an expanded collection requires membership.

Best for: Children learning the English alphabet and beginning to read simple words.

British Council LearnEnglish Kids

Website: https://learnenglishkids.britishcouncil.org/

This website offers free English-language games, songs, stories, videos, printable worksheets and craft activities. It is particularly useful for children developing their English-language skills.

Best for: Listening, vocabulary, pronunciation, early reading and learning through songs.

Read Along by Google

Website: https://readalong.google/

Read Along is a reading-practice tool designed to help children develop their reading skills with assistance from a digital reading companion. Availability and supported languages may vary by device and region.

Best for: Children who are beginning to read aloud and practise independently, with parental supervision.

3. Free Children's Storybooks

StoryWeaver by Pratham Books

Website: https://storyweaver.org.in/

StoryWeaver is a particularly valuable resource for Indian families. It provides access to illustrated children's stories in multiple languages. Stories can be read online and, where supported, downloaded for offline reading.

The collection includes stories in English, Hindi and other Indian languages, making it useful for families who want their children to develop reading skills in more than one language.

Best for: Building a daily reading habit and introducing children to stories in their preferred Indian language.

Pratham Open School

Website: https://www.prathamopenschool.org/

Pratham Open School offers learning resources, including videos, games, stories and activities in multiple languages. Its materials cover early learning and extend to older age groups.

Best for: Families looking for educational material with an Indian context.

Oxford Owl – Free eBook Library

Website: https://www.oxfordowl.co.uk/for-home/

Oxford Owl offers children's eBooks and reading resources. Access to its free eBook library requires registration, and availability may depend on the resource and region.

Best for: Shared reading with parents and helping children progress towards independent reading.

4. Science, Discovery and Creative Learning

PBS KIDS

Website: https://pbskids.org/

PBS KIDS provides educational games and videos covering mathematics, literacy, science, problem-solving and social skills. Many activities are built around familiar children's characters. Some videos and services may be restricted outside the United States.

Best for: Learning through play, exploration and simple problem-solving.

Sesame Workshop

Website: https://sesameworkshop.org/

Sesame Workshop provides educational resources, including videos, activities and materials addressing early learning, feelings, relationships, healthy habits and school readiness.

Best for: Combining academic learning with emotional development and everyday life skills.

ScratchJr – Introduction to Coding

Website: https://www.scratchjr.org/

ScratchJr is a free introductory programming app designed for children aged approximately 5–7. Children can create interactive stories and simple animations using visual programming blocks rather than typing code.

Best for: Creativity, sequencing, logical thinking and learning to create with technology.

5. A Simple Way to Use These Resources

Parents do not need to use every website or turn home learning into another school timetable. A small, consistent routine is often more practical.

• Mathematics: Practise counting, shapes or simple addition using MathEasily, Topmarks or Khan Academy Kids.
• Reading: Explore Starfall or a suitable early-reading activity.
• Storytime: Read a StoryWeaver book together in English or the child's preferred Indian language.
• Creative learning: Use drawing, building blocks, puzzles or a ScratchJr activity when the child is ready.
• Real-world learning: Count household objects, sort toys by colour, identify shapes around the home or help measure ingredients while cooking.

A short activity followed by hands-on play can be more useful than spending a long time moving from one educational app to another.

6. Things Parents Should Remember

Free Does Not Always Mean Completely Free

Some websites provide a useful free collection but charge for premium lessons, additional worksheets or memberships. Check the terms before committing to a service.

Check Advertisements and Privacy

Review websites and apps before allowing a child to use them independently. Prefer resources that minimise advertising, unnecessary data collection and distracting features.

Choose Activities Appropriate to the Child's Age

Kindergarten children develop at different speeds. The aim should be to build confidence and curiosity rather than force every child to complete the same activities.

Do Not Neglect Offline Learning

Storybooks, drawing, pretend play, building blocks, outdoor exploration and conversations with adults remain essential parts of early childhood learning. Online resources should complement these experiences, not replace them.

Use the Child's School Curriculum as a Guide

Websites designed around American or British curricula may use different terminology, sequences or expectations from Indian schools. Parents can select activities that best match their child's current learning needs.

Conclusion

Free educational resources can help parents provide children with additional learning opportunities without committing to expensive subscriptions or purchasing a large collection of workbooks.

For an Indian family, a practical starting combination is Khan Academy Kids for general learning, MathEasily or Topmarks for mathematics practice, Starfall for English phonics, and StoryWeaver for illustrated stories in Indian languages.

The real value, however, does not lie in collecting the largest number of websites. It lies in finding a few useful resources, using them consistently and allowing children to learn at their own pace.

Learning should be an adventure, not an expense.

India Must Transfer Technology — and Grow the People Who Can Advance It

India's entry into semiconductor manufacturing presents an opportunity that goes far beyond building fabrication plants, importing machinery or obtaining technology licences. The real opportunity is to develop a generation of Indians who can understand, operate, maintain, adapt and eventually advance the technologies that underpin modern computing.

A technology transfer can give India access to a manufacturing process. It cannot automatically transfer decades of accumulated engineering experience, the ability to solve unfamiliar problems, or the institutional knowledge required to develop the next generation of technology.

India must therefore pursue two objectives together: acquire technology from wherever possible, and grow the people capable of using that technology independently.

The technology is only half the equation

India's semiconductor ambitions naturally focus on fabrication plants, process nodes, investment and manufacturing capacity. These are essential, but a fab is only one component of a much larger technological ecosystem.

A functioning semiconductor industry requires chip designers, computer architects, verification engineers, electrical engineers, materials scientists, chemical engineers, equipment specialists, manufacturing technicians, software developers and technical programme managers.

It also requires people who can connect these disciplines. A chip design must be translated into a physical layout, manufactured using carefully controlled processes, tested, packaged and integrated with firmware, drivers, operating systems and applications. Every transition introduces problems that must be understood and solved.

A country may import advanced equipment and license a manufacturing process, yet remain dependent on foreign specialists if it has not developed enough people who understand how the entire system works.

The objective should not be to avoid foreign technology. It should be to ensure that every technology partnership increases India's ability to understand, maintain and improve what it acquires.

Use the global open-technology movement as a training ground

India does not need to recreate every technological foundation independently. Europe and the United States already support extensive ecosystems of open-source software, open hardware, research collaborations and reusable engineering tools.

European initiatives provide particularly relevant examples.

TRISTAN is working to mature and industrialise an open RISC-V ecosystem, including processor building blocks, verification, electronic design automation and supporting software. ISOLDE and RIGOLETTO contribute to the wider European open-hardware landscape, including work on automotive computing platforms. These initiatives create opportunities to study real engineering practices and contribute to reusable technical foundations.

The European Unified RISC-V IP Access Platform also brings together hardware components from multiple projects, making it easier for researchers and companies to discover and reuse existing designs rather than repeatedly starting from scratch.

India should actively encourage its students, researchers and companies to participate in these international projects, alongside established American open-source software and hardware initiatives.

The principle is straightforward: do not build from zero when the world already offers a foundation that can be studied, tested, improved and reused.

Participation must, of course, respect each project's eligibility requirements, intellectual-property rights, export controls and licensing conditions. Not every project is fully open, and not every component is available for unrestricted commercial use. These constraints should be understood before students or institutions commit to a project.

Give practical technical contributions academic value

One way to make this participation widespread would be to introduce an Open Technology Experience Credit within Indian technical education.

Universities, engineering colleges, polytechnics and technical institutes could recognise verified contributions to approved international open-source and open-hardware projects as part of internships, laboratory work, research credits and final-year projects.

A student should not receive credit merely for creating an account, attending a workshop or collecting a certificate. The credit should reflect demonstrable work.

Examples include:

• Developing or improving a compiler, driver, firmware component or software library.
• Writing verification tests for a processor core or hardware interface.
• Improving the documentation and reproducibility of an electronic design automation tool.
• Building and testing an FPGA prototype.
• Contributing to an open processor design or a reusable hardware IP block.
• Investigating materials, manufacturing processes, equipment reliability or testing methods through supervised research.
• Developing automated testing systems, measurement tools or manufacturing data pipelines.
• Coordinating a multidisciplinary project and demonstrating that its technical components work together.

Contributions should be reviewed by experienced maintainers, researchers or industry engineers. Assessment should reward correctness, documentation, testing, collaboration and learning rather than simply counting lines of code or commits.

This would create a bridge between classroom education and the engineering practices used in actual industrial projects.

Grow the entire technical workforce, not just IT engineers

The semiconductor industry is often discussed as if it were primarily an extension of software engineering. Software is important, but the physical manufacturing process depends on many other disciplines.

Computer science students can work on operating systems, compilers, development tools, simulation and firmware. Electronics students can explore circuit design, digital logic, verification, signal integrity and FPGA implementation.

Materials and chemical engineering students can investigate substrates, photoresists, deposition, etching, cleaning, contamination control and process reliability. Electrical and mechanical engineers can work on power delivery, thermal management, precision equipment, sensors and automation.

Manufacturing technicians and diploma holders can develop expertise in equipment operation, maintenance, process monitoring, inspection and quality control. Technical managers can learn how to coordinate design teams, research institutions, equipment suppliers and fabrication facilities.

These are not separate talent pipelines that should remain isolated. They must learn to work together.

A semiconductor product succeeds when the design, manufacturing process, software and physical system function as a whole. India's education system should create more opportunities for students from different disciplines to work on shared projects, using common technical objectives and measurable outcomes.

Move from software to physical silicon

An open-source contribution is valuable, but the larger opportunity emerges when people can follow their work into physical products.

Students who develop processor designs should be able to progress towards simulation, verification, FPGA prototypes, physical implementation, fabrication, packaging and post-silicon testing.

India already has a foundation on which to build. The government's Chips to Startup programme has supported chip-design education, access to design tools, shared fabrication services and student-designed chips. A January 2026 government update reported that more than one lakh individuals had enrolled in chip-design training, approximately 67,000 had been trained, and 56 student-designed chips had been fabricated, packaged and delivered through the programme's reported activities.

These are meaningful foundations. The next step is to connect such initiatives more systematically with international open-hardware projects, industrial internships, research collaborations and actual manufacturing programmes.

A student who begins by writing a verification test for an open processor should have a route towards working on the processor's physical implementation. A materials engineering student should have a route from laboratory research into process engineering. A firmware developer should be able to work with the hardware team to diagnose problems discovered after fabrication.

The aim is to create a continuous learning pathway from foundational knowledge to practical engineering and, ultimately, independent innovation.

Acquire technology while building the capacity to improve it

International technology partnerships remain essential. India should pursue licensing, joint research, training and technology access from willing partners across Europe, Japan, South Korea, the United States and elsewhere.

But every agreement should be evaluated against a broader question: what will Indian engineers be able to do after the agreement that they could not do before it?

A successful partnership should include opportunities for Indian specialists to participate in design, process integration, testing, reliability engineering, equipment support and manufacturing improvement. Where commercially and legally feasible, it should also create pathways for local research and progressively greater domestic capability.

The same principle applies to mature and advanced semiconductor processes. India can begin with technologies that are commercially accessible today while investing in the people and institutions needed to advance towards more sophisticated manufacturing.

It does not need to wait for the most advanced process node before developing world-class engineering expertise.

Keep the technological commons alive

Open-source software and hardware can accelerate this process because shared foundations allow many teams to learn from one another. However, these foundations require continued maintenance.

A project may produce an excellent processor design, firmware library or development tool and still lose momentum when its principal maintainers move on. Without documentation, testing, funding and a succession of contributors, valuable engineering work can become difficult to use.

India should therefore support not only the creation of new projects but also the long-term stewardship of existing ones. This includes funding maintainers, supporting documentation, improving verification, providing test infrastructure and helping promising projects mature into reliable engineering resources.

Commercial companies can then build differentiated products on top of these shared foundations. Their proprietary innovations need not all be open, provided that the underlying licences and interfaces permit the intended forms of reuse.

The objective is to create a sustainable relationship between the commons and commercial innovation: shared foundations enable more participants to innovate, commercial products create economic value, and continued stewardship ensures that the foundations remain useful.

A million opportunities for hands-on experience

India should consider a long-term ambition of giving at least one million people meaningful opportunities to participate in real technical projects across open software, hardware design, semiconductor research, manufacturing and systems integration.

This should not mean one million people completing the same semiconductor course. It should mean a broad network of practical learning opportunities, appropriate to different educational backgrounds and levels of expertise.

Some participants will become chip architects. Others will specialise in materials, chemicals, process engineering, equipment maintenance, verification, firmware, operating systems or technical programme management. Many will contribute to the software and hardware infrastructure that makes semiconductor development more efficient.

The programme should be judged by what participants can actually do, the quality of their contributions, their progression into more demanding work, and the ability of Indian organisations to retain and develop their expertise.

A million certificates would prove little. A million genuine opportunities to learn through practical work could help transform the country's technical workforce.

The real measure of semiconductor success

India should not measure its semiconductor future only by the number of fabrication plants it builds, the amount of investment it attracts or the smallest process node it can manufacture.

It should also measure how many people can design, verify, manufacture, test, maintain and improve the technology inside those facilities.

A fab can be built with sufficient capital, equipment and external expertise. The accumulated engineering judgement required to operate it efficiently and develop the next generation of processes takes sustained effort to cultivate.

India's opportunity is to combine international technology access with grassroots technical enablement. The global open-software and open-hardware movement can provide a practical learning ground, while domestic research institutions, manufacturers and industrial partnerships can connect that experience to physical products.

The objective is not to make India independent of every foreign supplier. It is to ensure that India becomes increasingly capable of understanding, adapting and advancing the technologies on which it depends.

Technology transfer gives India access to today's capabilities. People give India the ability to use those capabilities. A sustained culture of learning, research and engineering gives India the chance to create tomorrow's capabilities itself.

That is the investment that can outlast any single fab, technology licence or semiconductor generation.

The Same Package: Hair, Headgear, Faith, Family and the Moral Life Across Civilizations

Across the history of Eurasia, we repeatedly encounter people who look surprisingly similar: long or uncut hair, substantial facial hair, hair tied into a knot or covered with cloth, turbans, caps, robes, beards and other forms of distinctive dress.

It is tempting to conclude that these similarities must come from a common ancient tradition. Sometimes there may indeed have been historical contact or transmission. But often the similarity may have another explanation: different civilizations encountered similar human bodies, similar environmental conditions and similar social problems, and independently developed ways of giving those things meaning.

The more interesting question, therefore, is not simply:

“Who had long hair, beards and head coverings?”

It is:

“What was the complete package of ideas in which long hair, facial hair, clothing, ritual, family, learning, gender, spirituality and social responsibility belonged?”

This distinction is important. Two people may both have long hair, a beard and a head covering while holding radically different ideas about God, family, society and justice.

At the same time, two traditions that look very different on the surface may share remarkably similar underlying principles.

1. The “same package” principle

A human practice rarely exists in isolation.

Uncut hair may be connected to a belief about the body. A head covering may be connected to dignity or ritual. A beard may signify maturity or religious discipline. A particular garment may distinguish a community. A daily prayer may reinforce an ethical code. A martial tradition may emerge from a particular understanding of justice.

So instead of comparing hairstyles, we can compare complete packages:

• The body: hair, beard, clothing, cleanliness and physical discipline.
• The mind: learning, meditation, prayer, self-control and emotional discipline.
• The family: marriage, children, parents, ancestors and obligations.
• Gender: expected roles, equality, complementarity and historical practice.
• The divine: God, gods, Heaven, Dao, ultimate reality or another conception of transcendence.
• Learning: scripture, Guru, teacher, philosophy, ancestors or lived example.
• Ritual: prayer, meditation, initiation, pilgrimage, worship and daily discipline.
• Community: equality, hierarchy, caste, status, fraternity and service.
• Authority: scripture, Guru, priesthood, ruler, family or moral law.
• Justice: what constitutes a good society.
• Tyranny: what a person should do when authority becomes unjust.
• Martial tradition: whether fighting is forbidden, permitted, obligatory or part of religious identity.
• Ultimate purpose: salvation, liberation, enlightenment, harmony, service or realization of the Divine.

Once these dimensions are placed together, the apparent similarities and differences become much clearer.

2. The body: “Was this body given to me?”

One of the most remarkable comparisons is between the Sikh concept of kesh and the traditional Confucian understanding of the body.

The Classic of Filial Piety contains the famous statement that the body, hair and skin are received from one's parents and therefore should not be casually damaged. It describes this as the beginning of filial piety.

This creates a powerful philosophical proposition:

The body is not merely an object of personal fashion.

In the Confucian framework, the body connects the individual to parents, ancestors and the family.

In the Khalsa framework, kesh can be understood within a relationship to the Creator, Guru and Khalsa discipline. The Sikh Rehat Maryada explicitly includes unshorn hair among the five articles of faith for initiated Sikhs.

The similarity is therefore striking:

“I did not manufacture myself, so I should think carefully before altering the body I have received.”

But the direction is different.

Confucianism places the body primarily inside a chain of parents → ancestors → family → society.

The Khalsa places the disciplined body within a chain of Creator → Guru → individual → Khalsa → humanity.

These are not the same theology. But they demonstrate how two civilizations can arrive at a related intuition through different philosophical routes.

3. Hair is not necessarily about hair

This is perhaps the most important point in the entire comparison.

Uncut hair can mean:

• filial responsibility;
• acceptance of divine creation;
• asceticism;
• renunciation;
• social adulthood;
• community identity;
• religious discipline;
• resistance to imposed authority;
• or simply inherited custom.

And shaving can have equally different meanings.

A Buddhist monk may shave as an expression of renunciation. An ascetic tradition may preserve hair precisely because allowing it to grow represents another form of renunciation. A military institution may demand short hair for discipline and uniformity. A modern professional may cut hair because of fashion or workplace convention.

The same physical object — human hair — therefore becomes a symbol of completely different ideas.

4. Confucianism: the body as a bridge between generations

Traditional Confucian thought provides one of the clearest examples of a civilization in which bodily appearance, family and moral education were interconnected.

Filial piety was not simply “obey your parents.” It was part of a larger process of becoming a morally cultivated person. The Classic of Filial Piety describes filiality as the root of virtue and connects serving one's parents with establishing oneself through moral conduct.

The package therefore looks roughly like:

body → parents → ancestors → education → moral cultivation → social harmony.

Traditional Chinese society also developed elaborate rules concerning dress, ritual, age, rank and public conduct. The objective was not merely individual spiritual experience. It was the creation of a morally ordered society in which people knew their responsibilities to one another.

This is an important contrast with the Khalsa.

The Khalsa also imposes visible discipline, but it uses that discipline to create a community of people committed to a different theological and ethical order.

5. Khalsa: the body as public commitment

The Khalsa was formally institutionalized in 1699 under Guru Gobind Singh Ji. The Sikh community's development culminated in this transformation into an initiated community with a distinct discipline and visible identity.

The five articles of faith make the body itself part of the commitment. Kesh is accompanied by the kangha, kara, kachera and kirpan. The Sikh Coalition describes these articles as a public commitment to the values and ethics of the tradition, including service, compassion and honesty.

This is a crucial difference from merely having long hair because one's society happens to prefer long hair.

The Khalsa makes identity deliberately visible.

The person carries the commitment into the street, workplace, battlefield, family and marketplace.

The appearance therefore becomes a kind of continuous reminder:

“I belong to something, and that belonging imposes obligations upon me.”

The turban also acquires a particularly interesting social meaning. Sikh sources describe it as a visible assertion of dignity, equality and public commitment, rather than merely a device for managing long hair.

6. The crucial Sikh difference: Sant-Sipahi

The comparison becomes much deeper when martial responsibility is added.

The Khalsa is not simply a community of spiritually disciplined people. Sikh history develops the ideal of the Sant-Sipahi — the saint-soldier.

This creates a distinctive package:

spirituality + ethical discipline + service + courage + capacity to defend others.

The kirpan is therefore not adequately understood simply as a weapon. Within Sikh identity it belongs to a broader moral vocabulary concerning justice, responsibility and the defence of human dignity.

This is one of the places where comparing only external appearance becomes misleading.

A bearded, long-haired ascetic and a Khalsa Sikh may look superficially similar, but their social philosophies can be very different.

The ascetic may be withdrawing from worldly power.

The Khalsa ideal can instead require the spiritually disciplined person to remain inside society and accept responsibility for what happens within it.

7. Tyranny: when is obedience no longer enough?

This dimension makes the comparison especially interesting.

Confucian political thought developed the concept commonly known as the Mandate of Heaven. The legitimacy of political authority was connected to moral governance rather than merely possession of power.

That creates an important principle:

A ruler's authority carries moral obligations.

The Sikh tradition develops a different but similarly powerful concern with the relationship between authority and justice.

Guru Nanak's criticism of corrupt political and religious authority, the martyrdom tradition of the Sikh Gurus, the later militarization of the Sikh community and finally the Khalsa all belong to a historical development in which spiritual commitment becomes increasingly connected with resistance to oppression.

The two traditions should not be declared identical. Their political structures, metaphysics and historical experiences are different.

But they share an intriguing rejection of the proposition:

“Because someone possesses power, whatever they do must therefore be morally legitimate.”

8. Confucian resistance and Sikh resistance are not the same

This distinction is essential.

Confucianism generally places extraordinary emphasis on education, moral cultivation, proper relationships and good government. The ideal political response to disorder is heavily connected with restoring moral order.

The Sikh tradition, especially after the Mughal-era conflicts experienced by the Sikh Gurus and community, develops a much more explicit martial dimension.

Thus:

Confucian ideal: cultivate the person → cultivate the family → cultivate government → restore harmony.

Khalsa ideal: cultivate the person → remember the Divine → serve others → stand for justice → defend the vulnerable when necessary.

Both are concerned with moral society, but the mechanism and historical context differ.

9. Hindu traditions: one civilization, multiple answers

“Hinduism” cannot be treated as a single package for this comparison.

Indian traditions developed radically different approaches to the body.

Some ascetic traditions preserved and cultivated long hair, including jata. Other traditions emphasized shaving the head as part of renunciation. Household traditions had their own conventions concerning hair, dress, ritual and social status.

This produces an important lesson:

India demonstrates that the same civilization can produce opposing interpretations of the same body.

Hair can represent natural/divine creation.

Hair can represent asceticism.

Shaving can represent renunciation.

Hair can represent social status.

And in the Khalsa, uncut hair becomes a permanent community discipline.

Therefore, “India traditionally kept long hair” is too simplistic. The more accurate statement is that the Indian civilizational environment produced a remarkably large number of competing philosophies concerning what hair means.

10. Buddhism: the opposite answer

Buddhist monastic traditions provide an especially useful counterexample.

Where the Khalsa deliberately preserves hair, Buddhist monastic discipline traditionally involves shaving the head.

The important point is not that one practice is “more spiritual.” They are answering different questions.

The Khalsa asks, in part:

“How can I live visibly and continuously within a disciplined relationship with the Divine and my community?”

The Buddhist renunciant asks:

“How can I reduce attachment to worldly identity and cultivate liberation?”

The physical actions therefore move in opposite directions:

preserve the hair versus remove the hair.

Yet both can be forms of disciplined spirituality.

This is why comparing only outward practices can be so deceptive.

11. Daoism: harmony rather than social conformity

Daoist traditions introduce another philosophical possibility.

Instead of making the central problem either social hierarchy or renunciation, Daoist thought often emphasizes alignment with the Dao — the underlying Way or natural order.

Practices concerning body cultivation, simplicity, naturalness and longevity therefore belong to a different package from either Confucian filial order or Khalsa discipline.

Interestingly, Confucianism and Daoism developed within the same broad Chinese civilization while offering substantially different answers to the question of how a human being should live.

This is another warning against equating geography with philosophy.

12. Korea: when hair becomes social adulthood

Korean history provides another fascinating example because Confucianism became particularly influential in Joseon society.

Traditional men's long hair was commonly tied into a topknot after reaching adulthood, and formal headgear became part of the social presentation of the mature male.

The resulting appearance can look remarkably similar to other Eurasian traditions:

long hair → controlled hair → headgear → adult identity.

But the underlying package was strongly connected with family, status, ritual propriety and Confucian social order.

Compare that with the Khalsa:

kesh → dastar → initiated identity → discipline → responsibility.

The visual resemblance is real. The philosophical package is different.

13. Judaism, Christianity and Islam: another set of packages

Jewish, Christian and Islamic traditions add further variations to the comparison.

In Jewish traditions, hair, beard, side-locks, head coverings and dress can become expressions of religious law and communal identity, although practices vary considerably between communities and historical periods.

Christian traditions contain both hair-preserving and hair-removing models. The long-haired and bearded holy person appears in many Eastern Christian contexts, while monastic traditions have also developed distinctive forms of tonsure, shaving and head covering.

Islamic traditions contain strong traditions surrounding beard, modest dress and head coverings, but again the precise practices vary according to region, school and historical period.

These traditions therefore demonstrate another principle:

religious identity can be carried on the body without the body itself being the ultimate object of worship.

14. Gender changes the package

Any serious comparison has to include women.

It is not sufficient to compare “men with long hair and beards” because many traditions have entirely different expectations for male and female appearance.

The important questions are:

• Is hair uncut for everyone or primarily men?
• Are women expected to cover their hair?
• Is facial hair treated as a male marker?
• Does religious initiation apply equally to men and women?
• Are visible religious symbols available to both genders?
• Does the tradition distinguish spiritual equality from different social roles?
• What did the texts prescribe, and what did historical societies actually do?

The last question is particularly important.

Prescriptive tradition and historical practice are not the same thing.

A religion may teach spiritual equality while a particular historical society retains patriarchal customs. Conversely, a philosophical tradition may prescribe social hierarchy while individual societies implement it in many different ways.

15. Learning: where does truth come from?

This may be the deepest comparative question.

Different civilizations answer it differently.

Khalsa/Sikh tradition: Guru, Shabad, Gurbani, Naam, lived discipline and community.

Confucian tradition: classical learning, teachers, ancestors, moral cultivation and exemplary conduct.

Buddhist traditions: Dharma, teacher, meditation, ethical conduct and direct insight.

Hindu traditions: an enormous spectrum including Veda, Guru, scripture, philosophical reasoning, devotion, yoga and direct realization.

Daoist traditions: Dao, classical texts, teachers and practices of alignment/cultivation.

Abrahamic traditions: revelation, scripture, prophetic or apostolic traditions, religious law and interpretive communities.

The visible body is therefore only the outer layer of a much larger educational system.

16. Ritual: repetition as a technology of memory

Ritual is another place where these traditions unexpectedly converge.

A daily prayer, meditation, recitation, garment, head covering, hairstyle, dietary rule or physical discipline can serve as a memory technology.

It repeatedly answers the question:

“What kind of person am I trying to become?”

For a Sikh, the five Ks and daily prayers can continually bring the Khalsa commitment back into consciousness. The Sikh Rehat Maryada prescribes daily devotional practices alongside the articles of faith.

In Confucian society, ritual propriety similarly trained people to embody appropriate conduct rather than merely intellectually understand it.

In Buddhist practice, repeated meditation and ethical discipline train attention and conduct.

In many Hindu traditions, repeated mantra, puja or other practices connect everyday life with the sacred.

Ritual can therefore be understood not simply as “religious ceremony.”

It is a way of repeatedly training memory, attention and behaviour.

17. The visible person as a walking reminder

This leads to one of the strongest similarities between otherwise unrelated traditions.

A visible religious appearance can operate as a reminder both to the individual and to everyone around them.

A Sikh who maintains kesh and wears a dastar cannot easily forget that the Sikh identity is being carried publicly. Sikh sources explicitly describe the visible identity as a public commitment to the values and ethics of the tradition.

Something similar can happen with religious clothing, beads, robes, caps, sacred threads, markings or other visible practices in other civilizations.

The body becomes a kind of mnemonic device.

Instead of keeping religion entirely inside the mind, the tradition puts part of the commitment onto the body.

18. The martial question separates many traditions

Now introduce the question:

“What should a good person do when confronted by violence or tyranny?”

The answers become dramatically different.

Some traditions emphasize nonviolence or renunciation.

Some emphasize obedience to legitimate authority.

Some emphasize reform through moral education.

Some permit defensive violence.

The Khalsa develops an unusually explicit combination of spirituality and martial responsibility.

The ideal is not simply the warrior and not simply the monk.

It is the saint-soldier.

The desired person should have enough spiritual discipline to avoid becoming merely violent, but enough courage to avoid becoming merely passive.

This produces a particularly powerful ethical tension:

How do you possess power without becoming tyrannical?

and:

How do you remain peaceful without becoming helpless?

Those questions are central to understanding the Khalsa's distinctive historical package.

19. The deeper commonality: disciplined freedom

When these traditions are compared at this level, an unexpected common theme begins to appear.

They are all, in different ways, trying to solve the problem of the undisciplined human being.

The human being has desires, anger, fear, pride, greed, sexuality, ambition, attachment and the ability to harm others.

Different civilizations propose different solutions.

Confucianism: cultivate the person through education, relationships and ritual.

Buddhism: understand and overcome craving and ignorance.

Hindu traditions: use different paths of dharma, knowledge, devotion, action and disciplined practice.

Daoism: seek alignment with the Way rather than excessive forcing.

Khalsa/Sikh tradition: remember the Divine, live truthfully, serve humanity, cultivate courage and remain prepared to defend righteousness.

These are different answers to a broadly human problem.

20. And this brings us back to the “ancient look”

The long-haired, bearded, head-covered man therefore shouldn't automatically be categorized as “Asian.”

He appears repeatedly across Eurasia and in many religious and philosophical contexts.

Sometimes the appearance is simply the result of hair being allowed to grow naturally.

Sometimes it reflects adulthood.

Sometimes spirituality.

Sometimes social rank.

Sometimes family duty.

Sometimes military identity.

Sometimes resistance.

Sometimes fashion.

The modern short-haired, closely shaved male appearance is therefore only one historical solution among many.

What changed in modernity was not human biology. It was the meaning assigned to grooming.

21. Khalsa and Confucianism: perhaps the most revealing comparison

Of all the comparisons, the relationship between Confucianism and Khalsa may be especially valuable because the two traditions reveal both deep similarity and deep difference.

Both can say, in their own ways:

The human being is not an isolated consumer who can arbitrarily redesign himself without consequences.

Both emphasize disciplined conduct.

Both value learning.

Both care about family and social responsibility.

Both connect personal virtue with the condition of society.

Both reject the idea that power alone makes something morally right.

But they then take different routes.

Confucianism strongly emphasizes:

family → education → ritual → moral cultivation → social harmony.

Khalsa/Sikh thought emphasizes:

Divine remembrance → truthful living → discipline → equality → service → courage → justice.

The resemblance is therefore not that the two traditions are secretly the same.

The resemblance is that both recognized that character must be embodied.

22. The real object of comparison is therefore not the turban

A turban by itself tells us very little.

Long hair by itself tells us very little.

A beard by itself tells us very little.

Even a religious garment by itself tells us very little.

But when we place these things inside the complete package, they become extraordinarily informative.

We can ask:

What does this person believe about the body?

What does this person believe about God or ultimate reality?

What does this person owe to parents?

What does this person owe to strangers?

What should this person do with anger?

What should this person do with power?

What should this person do when a ruler becomes unjust?

What should this person teach their children?

What should this person do every day to remain the person they claim to be?

Only after answering those questions does the hair become meaningful.

23. A broader way of reading civilizations

Perhaps this is the most useful conclusion.

We often compare civilizations through their visible products:

architecture, weapons, clothing, hairstyles, scripts, food and monuments.

But beneath those visible things are packages of assumptions about human life.

The same hairstyle can arise from different assumptions.

The same head covering can represent different ideas.

The same beard can represent different virtues.

And two traditions that look completely different can sometimes share the same deeper concern: how to prevent human freedom from degenerating into selfishness, and how to turn an individual into a responsible human being.

The Khalsa is particularly interesting because it makes this philosophy unusually visible.

The body carries the commitment.

The daily discipline reinforces it.

The community recognizes it.

The martial tradition gives it a response to injustice.

And the spiritual tradition gives the power a moral direction.

That is why the Khalsa cannot be adequately understood simply as a community that “does not cut its hair.”

Kesh is one visible component of a much larger package.

And that is precisely the right level at which to compare it with Confucianism, Hindu traditions, Buddhism, Jainism, Daoism, Judaism, Christianity, Islam and the many other civilizational traditions that have asked the same fundamental question in different ways:

“What should a human being become?”

Once that question becomes the centre of the comparison, the similarities become more meaningful, the differences become clearer, and the superficial question of “who looked like whom?” becomes a much deeper investigation of how civilizations attempted to shape the human being.

Conclusion: The Package Is the Tradition

Perhaps the safest way to approach cross-cultural comparison is therefore:

Do not compare the hair. Compare the package.

Do not compare the turban. Compare what the turban means.

Do not compare the beard. Compare what the beard represents.

Do not compare the ritual. Ask what transformation the ritual is intended to produce.

Do not compare the warrior. Ask what gives the warrior legitimacy.

Do not compare the family. Ask why the family matters.

Do not compare the scripture. Ask what kind of human being the scripture is trying to create.

When we do that, the apparent similarities between distant civilizations stop being merely curious visual coincidences. They become evidence of something more interesting: human societies repeatedly encountered the same fundamental problems — mortality, desire, family, authority, injustice, violence, meaning and the search for the Divine — and developed different but sometimes surprisingly convergent packages for answering them.

The outward form is only the visible edge of the package.

The real comparison is the philosophy of the human being underneath it.

India Should Build the Foundations AI Will Need

India's next software opportunity may not be to write more applications for other people's platforms. It may be to build the open foundations that both humans and AI agents will use to create the next generation of applications.

For decades, India's software industry has demonstrated an extraordinary ability to take specifications, business requirements and existing technologies and turn them into working software at scale.

That model created an enormous industry.

But artificial intelligence is beginning to change the economics of software development.

The important question is therefore not simply whether AI will replace software engineers.

A better question is:

Which parts of software development become cheap when AI can write code, and which parts become more valuable?

The answer may be pointing toward an opportunity that India has not pursued aggressively enough: foundational software.

Instead of competing with AI to write another application, Indian engineers could increasingly build the libraries, engines, protocols, databases, media frameworks, graphics systems, APIs, developer tools and machine interfaces that AI itself will depend upon.

In other words:

Don't compete with AI at typing code. Build what AI needs underneath it.

The AI Coding Revolution Has a Hidden Limitation

The recent progress of AI coding systems is genuinely impressive.

Modern coding agents can read repositories, modify multiple files, run commands, inspect errors, write tests and iterate on implementations. AI can already produce surprisingly sophisticated applications from relatively simple instructions.

But there is an important distinction between writing software and having reliable software foundations available to build upon.

Suppose someone asks an AI:

"Create a reminder application that schedules notifications, stores reminders locally, survives a reboot and allows users to edit or delete reminders."

This is a reasonably approachable problem because modern platforms already provide many of the required building blocks.

The AI can combine a database, notification framework, scheduling system, user interface toolkit and operating-system APIs.

The result may still contain bugs. The architecture may need improvement. Dependencies may conflict. The application may require considerable debugging.

But the fundamental primitives already exist.

Now ask the AI:

"Build a reliable cross-platform video conversion engine that accepts arbitrary video files, decodes multiple codecs, handles audio and video streams, resizes frames, converts formats, encodes the result efficiently, preserves synchronization, muxes the output correctly and works across modern mobile hardware."

The problem changes completely.

The AI is no longer merely assembling mature components. It is suddenly forced to understand an enormous amount of low-level engineering.

Video processing involves codecs, containers, timestamps, buffers, hardware acceleration, pixel formats, audio pipelines, memory management, threading, synchronization and platform-specific behaviour.

Android's own MediaCodec, for example, is explicitly described by Google as a low-level interface to encoder and decoder components and is normally used together with other multimedia components such as MediaExtractor, MediaMuxer, MediaSync and Surface.

This is precisely where the difference between "AI can code" and "the ecosystem has good foundations" becomes visible.

My Own Experiments Pointed to the Same Problem

This is not merely a theoretical observation.

When I experimented with having frontier AI models build Android applications, relatively conventional applications were feasible.

A reminder application could be constructed using Android's existing scheduling, notification, database and UI infrastructure.

But when the task moved toward video conversion and media processing, things became much harder.

The problem was not necessarily that the AI could not write Kotlin or Java.

The problem was that the required abstraction was much weaker.

There was no single clean, modern, universally convenient "VideoEngine.convert(input, output, settings)" foundation that an AI could simply understand and reliably invoke.

Instead, the developer had to deal with lower-level interfaces and a large number of compatibility and implementation details.

This experience reveals something important about the future of AI-assisted programming.

AI becomes dramatically more powerful when difficult engineering problems have already been converted into reliable abstractions.

The AI can then assemble those abstractions.

This suggests that the value of software engineering will increasingly move toward the layers where those abstractions are created.

From Writing Applications to Building Digital Infrastructure

Imagine that somebody creates a mature, well-tested, open-source video foundation.

It provides:

• video decoding
• video encoding
• audio decoding and encoding
• format conversion
• resizing
• cropping
• frame extraction
• subtitle handling
• metadata handling
• hardware acceleration
• streaming
• container manipulation
• progress reporting
• error handling
• cross-platform APIs
• command-line interfaces
• language bindings
• machine-readable documentation

Suddenly, building a video application becomes much easier.

An AI agent might only need to invoke something like:

convert_video(
    input="movie.mp4",
    output="compressed.mp4",
    codec="h265",
    resolution="1080p",
    quality=75
)

The difficult engineering has not disappeared.

It has simply been moved downward into a reusable foundation.

That foundation can then support thousands of applications.

This is the economic difference between selling implementation and building infrastructure.

The New Software Stack May Have Four Layers

The software industry has traditionally been understood roughly like this:

1. hardware
2. operating systems
3. libraries and frameworks
4. applications

AI introduces another layer of interaction.

A future stack could increasingly look like:

1. Hardware — CPUs, GPUs, NPUs, storage, networking and accelerators.
2. System foundations — operating systems, drivers, compilers, databases, graphics, codecs and networking.
3. Agent-ready foundations — APIs, tools, schemas, documentation, state inspection, permissions and machine-readable interfaces.
4. Applications — products assembled increasingly by humans and AI agents.

The fourth layer may become progressively cheaper to produce.

The second and third layers could therefore become strategically more important.

AI-Controlled Software Is Different From AI-Generated Software

This distinction is particularly important.

There are at least three different things happening under the broad label of "AI coding".

1. AI-generated code

The AI writes the implementation.

This is what most people think about when they hear "AI coding".

2. AI-controlled software

The software already exists, but an AI agent can operate it through reliable commands.

For example:

create_rectangle(x, y, width, height)

create_circle(x, y, radius)

boolean_intersection(object_a, object_b)

export_image(format="png")

The AI does not need to understand how a geometric intersection algorithm works.

The graphics engine does.

The AI only needs to understand what the operation means and when to use it.

3. AI-generated content

The AI itself generates the resulting image, video, text, sound or other content.

These are very different technological models.

And the second model could become enormously important.

It means existing professional software can become agent-addressable.

The Agentic API Is Becoming a New Kind of Interface

Traditional APIs were designed primarily for programmers.

An engineer reads the documentation, understands the parameters and writes code against the interface.

AI agents introduce a new consumer for APIs.

The interface now needs to be understandable not only by humans but also by machines that reason over descriptions, schemas, examples and available operations.

This is already visible in emerging standards such as the Model Context Protocol (MCP).

MCP defines primitives including tools, resources and prompts. Tools allow models to invoke executable functions, while resources provide structured contextual information.

The significance is larger than one protocol.

It represents a shift in how software can be exposed.

A database does not necessarily have to be operated exclusively through a graphical interface.

A graphics editor does not necessarily have to be operated exclusively through menus and mouse clicks.

A spreadsheet does not necessarily have to be operated exclusively through cells.

A video editor does not necessarily have to be operated exclusively through a timeline.

The underlying capabilities can increasingly become tools that an AI agent can discover and invoke.

That makes the quality of the underlying API extremely important.

Documentation Becomes Part of the Software

This may be one of the most underestimated consequences of agentic software.

Documentation has traditionally been treated as something humans read.

In an agentic environment, documentation increasingly becomes part of the machine interface.

A good foundation should explain:

• what each operation does
• what inputs are accepted
• what outputs are returned
• what errors can occur
• what state is changed
• whether an operation is reversible
• whether an operation is destructive
• what permissions are required
• what performance characteristics exist
• what examples demonstrate correct usage
• what combinations of operations are valid
• what the agent should do when something fails

Modern MCP development is already moving in this direction. The protocol exposes tools with descriptions and schemas, while its broader ecosystem is developing ways to communicate server instructions and agent skills alongside tools and resources.

In other words:

The documentation of tomorrow may be executable knowledge.

This makes extremely detailed documentation an economic asset rather than merely a developer convenience.

What Should Indian Engineers Build?

If this thesis is correct, India should not simply ask:

"Which applications can we build using AI?"

We should also ask:

"Which difficult software capabilities could we turn into reusable foundations?"

There is an enormous list.

Tier 1: Simple Foundations

These may not sound glamorous, but they could provide excellent training grounds.

• notification engines
• scheduling engines
• document generation
• PDF creation and manipulation
• OCR
• text extraction
• speech-to-text
• text-to-speech
• file conversion
• archive management
• image resizing and transformation
• metadata extraction
• search libraries
• local indexing
• configuration management

These are not necessarily billion-dollar products individually.

That is not the point.

The point is to turn difficult recurring engineering problems into reliable reusable components.

Tier 2: Media and Data Foundations

Once engineers become comfortable with these systems, the complexity can increase.

• audio engines
• video engines
• image processing engines
• document rendering engines
• database engines
• search and indexing systems
• data transformation pipelines
• compression libraries
• streaming systems
• networking libraries
• file-system abstractions
• synchronisation engines
• local-first databases

These are much deeper engineering problems.

They require understanding memory, concurrency, algorithms, operating systems, storage, networking and hardware.

They are also exactly the kinds of foundations that thousands of applications could reuse.

Tier 3: Advanced Foundations

Then comes the genuinely difficult territory.

• graphics engines
• rendering systems
• physics engines
• simulation frameworks
• compilers
• language runtimes
• cryptographic libraries
• distributed databases
• distributed storage
• networking stacks
• virtualisation
• container infrastructure
• operating-system components
• GPU compute frameworks
• machine-learning runtimes

These are not ordinary application-development projects.

They require engineers who understand the machine underneath the abstraction.

And Then There Is Hardware

This is where the opportunity becomes particularly interesting for India.

The boundary between software and hardware is becoming increasingly important as AI workloads spread across CPUs, GPUs, NPUs and specialised accelerators.

Open hardware projects and open instruction-set architectures such as RISC-V provide another possible direction.

An engineer who understands operating systems, compilers, runtimes and hardware interfaces can eventually work much closer to the machine itself.

That could mean:

• RISC-V software stacks
• device drivers
• embedded operating systems
• accelerator runtimes
• GPU software
• NPU runtimes
• compiler backends
• hardware abstraction layers
• firmware
• verification tools
• simulation environments
• EDA tooling

This is particularly relevant to India's emerging interest in open silicon.

If India eventually wants to participate seriously in open CPUs, NPUs, GPUs and specialised accelerators, it will need software engineers who can cross the boundary between software and hardware.

The future opportunity is therefore not simply software versus hardware.

It is software deeply integrated with hardware.

The "Daily-Wage Programmer" Problem

There is an uncomfortable economic dimension to all of this.

Large parts of the global software-services economy are structured around selling engineering capacity.

A customer has a requirement.

A company assigns engineers.

The engineers implement the requirement.

The customer pays for the work.

The engineers move to the next project.

There is nothing inherently wrong with this model. It created enormous employment and helped establish India as one of the world's major technology centres.

But economically, it has a limitation.

The value is repeatedly tied to human implementation hours.

AI directly attacks the economics of repetitive implementation.

If an AI agent can produce in one hour what previously required ten engineers for a week, the market value of simply supplying those implementation hours will inevitably come under pressure.

That does not mean software engineering disappears.

It means the location of value changes.

Instead of asking:

"How many programmers can India provide?"

We should increasingly ask:

"How many foundational technologies can Indian engineers create and maintain?"

Foundational Software Is Digital Capital

A reusable software foundation behaves differently from a consulting project.

A consulting project may serve one customer.

A foundation can serve thousands.

A library written once can be integrated into hundreds of products.

A codec can be used by countless applications.

A database can support millions of users.

A graphics engine can power an entire ecosystem.

An open protocol can become infrastructure.

A compiler can support an entire hardware architecture.

This is why foundational software should be understood as digital capital.

It is not simply code.

It is accumulated engineering knowledge converted into a reusable machine.

Open Source Makes the Opportunity Even More Interesting

India does not necessarily need to own every foundation commercially.

Open source changes the equation.

An Indian engineering team could build an open-source foundation and allow companies around the world to build upon it.

Revenue could then emerge from:

• commercial support
• enterprise editions
• hosting
• integration
• certification
• hardware partnerships
• consulting
• specialised implementations
• managed services
• commercial extensions

But the underlying technical asset remains available to the ecosystem.

This creates a very different relationship between Indian engineers and global technology.

Instead of merely implementing somebody else's platform, Indian engineers can help create the platforms that others implement against.

India Already Has the Scale

The interesting thing is that India does not need to start from zero.

India already possesses an enormous technology workforce and a large software-services ecosystem.

NASSCOM's recent industry estimates put India's technology-industry workforce at millions of employees, while engineering R&D, GCCs and digital engineering have become increasingly important parts of the ecosystem. Its 2025 strategic review estimated FY2025 technology-industry revenue at more than $282 billion including hardware and projected the industry toward $300 billion in FY2026.

The question is therefore not whether India has enough engineers.

The question is what those engineers are encouraged to build.

There is a huge difference between having millions of people capable of writing software and having a large community capable of maintaining foundational software.

The second requires a different culture.

We Need More Engineers Who Understand the Machine

The foundational engineer of the future should probably be comfortable moving across multiple layers.

They should understand:

• algorithms
• data structures
• memory
• concurrency
• operating systems
• networking
• file formats
• compilers
• databases
• graphics
• hardware interfaces
• performance profiling
• testing
• security
• API design
• documentation

Languages such as C, C++ and Rust become particularly useful in this world, not because higher-level languages disappear, but because somebody eventually has to understand what is happening underneath them.

And AI itself becomes a powerful assistant for these engineers.

An engineer who understands a system can ask AI to generate implementations, explore alternatives, write tests, inspect code and produce documentation.

The engineer provides the architectural understanding.

The AI provides enormous amounts of implementation leverage.

This could actually make foundational engineering more productive, rather than less relevant.

The Goal Is Not to Eliminate Application Developers

This argument should not be misunderstood.

India should not suddenly tell millions of application developers to abandon their careers and become kernel developers.

That would be neither realistic nor desirable.

Application development will remain enormous.

People will always need products designed around particular businesses, industries, cultures and human needs.

What should change is the proportion of effort spent reinventing low-level capabilities.

If a mature open-source foundation already exists, developers should use it.

If it does not exist, that absence may represent an opportunity.

The application developer of the future may therefore become much more productive.

Instead of spending three months building an internal document engine, they might spend three days integrating a mature one.

Instead of writing a custom media pipeline, they might call a standard media foundation.

Instead of manually integrating dozens of APIs, an AI agent might orchestrate them.

This means foundational engineering does not destroy application development.

It makes application development cheaper and more powerful.

Universities Should Teach the Layers Below the App

This also suggests a change in engineering education.

Students should certainly learn Python, JavaScript, Java, Kotlin and modern AI tooling.

But they should also be encouraged to build things such as:

• a small database
• a file system
• a compiler
• a network protocol
• a simple operating-system component
• a graphics renderer
• a media pipeline
• a search engine
• a compression algorithm
• a small virtual machine
• a RISC-V emulator
• a hardware simulator

These projects teach something that framework-based application development often hides:

what the computer is actually doing.

Once an engineer understands that, AI becomes an accelerator rather than a replacement for understanding.

India Could Build a National Foundation Software Ecosystem

There is an even larger possibility.

India could deliberately identify a few hundred important open-source foundations and treat them as strategic digital infrastructure.

Not every project needs government ownership.

Not every project needs a giant company.

But India could create funding, fellowships, university programmes, industry partnerships and long-term maintenance programmes around strategically important open-source projects.

Consider a hypothetical Indian foundation stack:

Layer	Examples
Basic utilities	Files, scheduling, notifications, archives, conversion
Documents	PDF, office formats, rendering, OCR
Media	Audio, video, codecs, streaming
Data	Databases, indexing, search, synchronisation
Graphics	Rendering, 2D/3D, GPU compute
AI infrastructure	Inference runtimes, model formats, accelerator APIs
Systems	Compilers, runtimes, operating-system components
Networking	Protocols, distributed systems, secure communication
Hardware	Drivers, firmware, RISC-V, accelerators, simulation

Each layer would make the next layer easier.

That is how an ecosystem becomes self-reinforcing.

The First Foundations May Look Boring

There is another lesson here.

The first generation of Indian foundational software does not need to be spectacular.

A reliable notification library may be more useful than another flashy AI application.

A truly excellent PDF engine may quietly become part of thousands of applications.

A robust open-source video engine may save developers around the world enormous amounts of engineering effort.

A high-quality document renderer may become infrastructure for countless AI agents.

A well-designed database API may become invisible infrastructure used by applications nobody has imagined yet.

This is how foundational technologies often work.

Their success is measured by how many things can be built without thinking about them anymore.

AI May Actually Increase the Value of Good Foundations

This is perhaps the most important conclusion.

It is tempting to assume that AI makes software less valuable.

But another interpretation is possible.

AI makes well-abstracted software more valuable.

If an AI agent can discover a capability, understand its inputs and outputs, invoke it safely, inspect the result and recover from failure, that capability becomes a building block for automated software creation.

One foundation can therefore become part of thousands or millions of future AI-generated workflows.

The leverage becomes enormous.

This creates a positive feedback loop:

1. Engineers build a reliable foundation.
2. The foundation receives excellent documentation and APIs.
3. AI agents learn how to use it.
4. AI agents build applications using it.
5. More applications expose new requirements.
6. The foundation improves.
7. More developers and agents adopt it.

The foundation becomes more valuable precisely because AI makes it easier to build things on top of it.

Don't Build What AI Can Easily Assemble

This could become a useful rule for the next generation of Indian software engineers.

If an application can be assembled from ten mature open-source components in a few hours, building another copy of that application may not be the best long-term engineering opportunity.

Instead ask:

• Which component is missing?
• Which API is painful?
• Which format has poor support?
• Which low-level interface is unnecessarily difficult?
• Which library is abandoned?
• Which important project has poor documentation?
• Which capability is repeatedly rebuilt by thousands of developers?
• Which foundation could make an entire category of applications easier?

That is where the opportunity lies.

The Next Indian Software Story Could Be Deeper Than Services

India's first major software revolution was built around services.

The next could be built around products.

But there is potentially an even deeper stage:

infrastructure.

Not just SaaS products.

Not just mobile applications.

Not just AI wrappers.

Not just consulting.

But the underlying software that makes all of these things possible.

And as the AI era develops, the customer for this infrastructure will no longer be only a human developer.

It will increasingly be another piece of software.

An AI agent.

A coding agent.

A design agent.

A research agent.

A financial agent.

A manufacturing agent.

A scientific agent.

Millions of such agents may eventually need reliable software foundations.

From Software Services to Software Infrastructure

India should therefore think beyond the question:

"How many software engineers will AI replace?"

A much more productive question is:

"What foundations can Indian engineers build so that the next billion software systems can be created more easily?"

That is a completely different vision.

It does not require India to defeat Silicon Valley.

It does not require India to build the next giant consumer platform.

It does not require every engineer to become an AI researcher.

It requires something much more practical:

Build excellent software that other software can depend upon.

Start with the boring problems.

Make them reliable.

Document them obsessively.

Expose clean APIs.

Make them accessible from multiple languages.

Make them usable locally and offline where possible.

Make them friendly to automation.

Make them safe for agents.

Make them open where openness creates ecosystem value.

Then move deeper.

Into graphics.

Databases.

Networking.

Compilers.

Operating systems.

AI runtimes.

Hardware interfaces.

Open silicon.

This is not a retreat from the AI revolution.

It is a way of moving closer to its foundation.

The Opportunity Below the Application Layer

There will always be people who build applications.

There will always be people who design user experiences.

There will always be people who solve business problems.

But increasingly, AI will be able to perform more of the mechanical work involved in turning those requirements into software.

That makes the deeper layers more interesting.

The engineer who understands the machine, the operating system, the protocol, the file format, the compiler, the accelerator and the API can become the person who creates the abstraction that thousands of other engineers — and eventually millions of AI agents — use.

That is a fundamentally different position from selling another block of programming hours.

It is the difference between writing code for a project and building a piece of the digital infrastructure on which future projects will run.

India already has the people.

India already has the software culture.

India already has enormous experience operating at global scale.

What is needed is a stronger deliberate push downward — toward foundational software, open infrastructure, systems engineering and eventually hardware-software co-design.

The age of AI may reduce the value of writing repetitive code.

But it could dramatically increase the value of creating the foundations from which that code can be generated.

India should not merely become the world's largest consumer of AI coding agents.

It should help build the foundations those agents stand on.

That may be one of the most important software opportunities of the next decade.