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Edtech Firms Rethink Curriculum, Cut Coding Time in Half as AI Roles Surge

Edtech firms like Great Learning and Newton School are slashing coding fundamentals by up to 50% and shifting to AI-driven curricula as demand for Forward Deployed Engineering roles skyrockets.

India’s upskilling platforms are undergoing a significant transformation as they adapt to the rapidly evolving landscape shaped by generative AI. In a move to align with the changing job roles and expectations of employers, these platforms are revising their curricula to reduce the emphasis on coding fundamentals while incorporating AI tools into core learning pathways.

The urgency of this shift is underscored by the rapid advancements in AI models, which can now execute tasks that previously required extensive training. As a result, edtech firms are prioritizing applied skills, system design, and real-world deployment over traditional syntax-heavy learning methods. “At a structural level, what used to take six weeks of coding fundamentals can now be done in two weeks with AI-assisted coding,” said Arjun Nair, co-founder and COO at Great Learning. He noted that this reallocation of time allows for a greater focus on higher-order skills such as problem framing, data quality, business context, and outcome interpretation.

Great Learning has also expanded its offerings to include no-code pathways across various programs, effectively broadening its market reach. Nair highlighted that in some of these programs, as much as 80 percent of learners are choosing the no-code track, with individuals from non-technical backgrounds accounting for 58 percent of its user base in FY26, a considerable increase from 36 percent in FY24.

Other platforms are adopting a more measured approach. Newton School, for instance, retains core fundamentals while integrating AI throughout its curriculum. Krishna Choudhury, head of growth at Newton School, mentioned, “Roughly 20–30 percent of time has been reallocated toward AI-first workflows, but always layered on top of strong fundamentals.” This balance aims to ensure that learners are well-equipped with foundational knowledge while also adapting to the demands of new technologies.

The curriculum revisions have coincided with the emergence of new AI-native roles, particularly in areas that bridge engineering, product management, and deployment. One notable position gaining traction is Forward Deployed Engineering (FDE), which is increasingly sought after as businesses look for talent capable of operationalizing AI systems at scale. Raghav Gupta, CEO and founder of Futurense, stated, “Forward Deployed Engineering has emerged as the hottest role in AI globally, yet there was no structured pathway anywhere in the world to prepare engineers for it.” To address this gap, Futurense has launched the FDE Academy, aiming to connect Indian engineering talent with global AI deployment opportunities, highlighting the future of AI work as engineers who can take systems from prototype to production and scale.

In tandem with these developments, the duration of educational programs is also being condensed. Great Learning reports that most new courses are now designed to last three to five months, with an emphasis on hands-on learning experiences. “Roughly 70 percent of learning is now practical application, with the rest focused on conceptual understanding,” Nair noted, pointing to a significant shift in educational focus.

Newton School corroborated this trend, indicating that 70–80 percent of its programs are now project-led, allowing learners to execute ideas swiftly and iterate without obstacles. This shift caters to the increasing demand from enterprises for AI-fluent talent across various functions, not limited to engineering. Upskilling firms are betting that the next wave of growth will come from professionals eager to integrate AI into their existing roles rather than transitioning to entirely new career paths.

As generative AI continues to reshape labor markets and skill requirements, these educational adaptations reflect a broader trend towards agility and practicality in learning, aiming to produce a workforce ready to tackle the challenges posed by emerging technologies. The focus on applied skills and real-world applications signals a pivotal shift in how future talent will be prepared to meet the demands of an AI-driven economy.

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David Park
Written By

At AIPressa, my work focuses on discovering how artificial intelligence is transforming the way we learn and teach. I've covered everything from adaptive learning platforms to the debate over ethical AI use in classrooms and universities. My approach: balancing enthusiasm for educational innovation with legitimate concerns about equity and access. When I'm not writing about EdTech, I'm probably exploring new AI tools for educators or reflecting on how technology can truly democratize knowledge without leaving anyone behind.

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