Babies Are Awesome Coders | Neuroscience, Play + Early Childhood

Most people see a baby stacking blocks, knocking them down, and rebuilding.

I see a child writing their first algorithm — proof that babies are awesome coders.

For over 35 years, I’ve worked in early childhood education — designing curricula, building businesses, and watching children learn. Over time, I’ve discovered something powerful: babies are some of the best coders you’ll ever meet.

Not coders in the narrow sense of typing commands into a computer. Instead, coders in the truest sense: pattern-spotters, problem solvers, and relentless experimenters. They debug, repeat, and refine their “programs” every single day.

If we learn to see it, then we can prepare children for the future in a way our education systems have not yet dared to imagine.


Babies as Natural Coders

Science confirms what educators observe every day.

  • Pattern detection from birth. A 2025 study in eLife showed that newborns, even while asleep, can detect regularities in speech streams (Fló et al.). In other words, babies already recognise patterns in noisy data.
  • Statistical learning. Classic work by Saffran et al. revealed that infants use probability to break down continuous speech. As a result, they can spot where one word ends and another begins.
  • Sequence learning. The hippocampus, active even in young infants, tracks temporal regularities (Ellis et al., 2021, Current Biology). Therefore, babies are, quite literally, wiring algorithms in their brains.

Most adults hear babble. However, I see loops, syntax, and error-correction routines running quietly in the background. In addition, these routines demonstrate how babies are awesome coders in ways we rarely acknowledge.


Play: The First Coding Language

Play is not a “break” from learning. In fact, it is the operating system.

  • A toddler builds a tower of blocks, watches it fall, and rebuilds differently. For example, that is iteration in its purest form.
  • A child lines up cars by colour or sorts Lego by size. In this case, the child is practising pattern recognition.
  • A group of children test different ways to balance a seesaw. As a result, they discover the value of debugging.

Research supports this view. For instance, a 2022 study comparing preschoolers’ block play with robot programming found both developed computational thinking, but block play was often stronger for sequencing and problem-solving. Consequently, wooden blocks may be a child’s first coding tool.

Here’s the dot most people miss: in many ways, children learn like AI.

They don’t stop. Instead, they keep training on new data, refining their models of how the world works. Furthermore, they approach every challenge with curiosity, creativity, and persistence. The only limits are the ones adults put around them. This is why babies are awesome coders from the very beginning.


📖 Recommended Reading

If you’d like to explore this idea of children as natural coders more deeply, one book I often recommend is:

👉 My First Coding Book

It’s a playful, interactive introduction that helps young children grasp loops, logic, and sequencing through simple activities. Books like this remind us that coding isn’t just about screens and syntax — it’s about nurturing curiosity, creativity, and resilience from the very start.


Misconceptions That Hold Us Back

Three assumptions get in the way of unleashing children’s coding potential:

  1. Coding requires literacy. In reality, the principles — sequencing, iteration, abstraction — are visible in babies long before they can read. This alone shows why babies are awesome coders before they ever touch a keyboard.
  2. Children are blank slates. In fact, neuroscience shows babies arrive primed to detect patterns and build meaning.
  3. Play is extra. On the contrary, play is where the real algorithms are written.

Therefore, the mistake we make is treating coding as something that begins with screens and syntax. Instead, it begins with curiosity and wooden blocks.


What EdTech and Curriculum Leaders Can Do

If you design products, curricula, or policies in education, the message is clear: coding is not just a subject, it’s a mindset — and babies are awesome coders already fluent in it.

  • Design for exploration, not completion. Create tools that extend children’s natural experimentation, rather than box them into rigid tasks.
  • Celebrate error. Great coders debug. Great children do too. As a result, curricula must legitimise trial and error as real learning.
  • Bridge science and design. EdTech has a unique opportunity to align brain science, pedagogy, and product development to mirror how babies’ brains actually work. In addition, such tools can prepare learners for an uncertain future.

The companies that do this will not just prepare children for the future — they will lead it.


What Governments and Education Systems Must Do

Preparing children for tomorrow’s world is not optional. Instead, it requires structural change today.

  1. Recognise play as foundational. Play must be built into early curricula as a core learning method — not treated as a luxury. It is the first coding language.
  2. Invest in computational thinking early. For example, fund programmes that embed sequencing, iteration, and problem-solving from preschool onwards, with both unplugged and tech-based tools.
  3. Empower educators as designers. Teachers should be trained to see coding principles in everyday play and scaffold exploration, not just deliver scripted lessons.
  4. Foster cross-sector partnerships. Moreover, governments should incentivise collaborations between EdTech firms, neuroscientists, and early years experts to create developmentally intelligent tools.
  5. Guarantee equity. In addition, every child must have access to stimulating environments, whether that means blocks and construction kits or coding robots.
  6. Shift assessments. Stop measuring only what children know. Instead, start valuing creativity, persistence, and resilience as core competencies. Moreover, these qualities are exactly what the future workforce will need most.

This is not about children “catching up” to technology. Rather, it is about education catching up to children.


The Future: Learning From Children — Why Babies Are Awesome Coders

I have spent decades watching babies solve problems that adults miss. I have seen toddlers invent solutions, test hypotheses, and challenge their own thinking — without any adult needing to show them how.

Here is the big picture: babies are awesome coders.

They debug. Iteration comes naturally. Writing algorithms through blocks, songs, and experiments is second nature. Like AI, they never stop learning — unless we stop them.

Therefore, the challenge is not whether babies can code. Instead, the challenge is whether adults are ready to learn from them.


👉 Work With Me
If you’re building EdTech, designing curricula, or shaping the future of learning, this is the lens I bring: connecting neuroscience, pedagogy, and technology to unlock children’s limitless potential. You can connect with me on LinkedIn — or visit consultancy.sharonkamel.com to learn more about my consulting work.


Disclaimer: Some links in this article are affiliate links. If you choose to purchase through them, I may earn a small commission at no extra cost to you. Thank you for supporting my work.


References

Yang, C., et al. (2022). Robot programming versus block play in early childhood. British Journal of Educational Technology.

Fló, A., et al. (2025). Statistical learning beyond words in human neonates. eLife. Link

Saffran, J., et al. (1996). Statistical learning by 8-month-old infants. Link

Ellis, C. T., et al. (2021). Hippocampus and learning temporal regularities in infancy. Current Biology. Link

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