I started in L&D the way most people do — building slides, recording voiceovers, packaging SCORM files. But I kept running into the same ceiling: the tools stopped where the problems didn't.
So I learned to write JavaScript inside Storyline. Then to connect courses to live APIs. Then to automate workflows that used to eat entire project weeks. Not because I wanted to be a developer — but because the learner experience I wanted to create required it.
Today I sit at a specific intersection: I think like an instructional designer and build like an engineer. That combination is rare, and it's where I do my best work.
I started with the fundamentals — storyboarding, scripting, building in early-era authoring tools. The gap between "what I want to build" and "what the tools allow" was the most interesting problem in the field, so I learned to close it.
That meant writing JavaScript inside Storyline. Then wiring courses to live APIs. Then building FFmpeg pipelines that reduced per-language video localisation from a full day's work to under 90 seconds across 8 languages.
Most L&D professionals start with content. I start with behaviour — what the learner needs to do differently, and what's currently stopping them. The technical work always follows from that question, never the other way around.
I use complex tech when it solves a real problem, and simple tech when that's what the problem needs. xAPI isn't impressive for its own sake — it's impressive when the data changes what you do next. I build once and document well enough that someone else can maintain it. And if something is being done manually and repeatedly, there's almost certainly a systems fix waiting to be written.
Based in Pune, India. Open to remote-first roles globally. I work best where L&D is seen as a craft — where you're expected to have a point of view and the latitude to act on it.
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I started in L&D the way most people do. I kept running into the same ceiling: the tools stopped where the problems didn't. So I learned to close that gap.
Building learning experiences grounded in learning science and pedagogical theory.
Technology infrastructure for modern L&D teams at scale.
Engineering workflows that eliminate repetitive work.