Freelance Assistant Trainer @ Iglow Pte Ltd

Freelance Assistant Trainer @ Iglow Pte Ltd

Freelance Assistant Trainer @ Iglow Pte Ltd

đź“š
TL;DR: Joined Iglow Pte Ltd as a Freelance Assistant Trainer teaching AI to adult learners aged 30–70+. Built and delivered 10+ workshops from scratch, redesigned all course materials into graphically engaging slides and printed references, and learned to bridge the gap between technical complexity and genuine human curiosity. The role was only meant to be a side income, but it became a crash course in public speaking, empathy, and the art of listening. Left after a compensation restructuring and a shift toward centralised material control, but walked away with a fundamentally different understanding of how adults actually learn.

Key lessons: preparation beats improvisation, adults learn differently than you expect, and the best trainers are the best listeners.

🛣️ The Journey

I landed the role at Iglow Pte Ltd through a referral from a relative. At the time, I was looking for something on the side - an extension of my technical background that could generate income without derailing my main trajectory. Iglow is a post-education provider that runs lectures for students in their later years, typically after the age of 30, covering topics like AI, Digital Security, and Marketing. I was brought in to assist with their AI curriculum.
My qualification came from an unconventional place. I wasn’t a career academic or a seasoned educator. I was a founder and software engineer who had spent years using AI to plan and code applications, combined with deep personal research into AI-driven productivity. I understood the tools technically and used them daily. Iglow needed someone who could translate that technical fluency into something accessible, and I fit the mould - though I didn’t yet know how much I would need to grow to actually fill it.
The arrangement was hybrid in practice: preparation happened remotely during after-hours - PowerPoints, notes, printed materials - while the actual lectures were delivered on-site. I worked with them for roughly four to five months, with a break over the December holidays. Compensation was structured per training course, which kept the stakes clear and the focus sharp.

🔥 The Classroom Reality

Walking into that first classroom was humbling. The audience wasn’t what I expected. These weren’t fresh graduates or young professionals eager to absorb jargon. My students ranged from their late 30s to their 70s, with class sizes between 15 and 35 people. And they weren’t a monolith. The room was split between two completely different mindsets:
  • The career-active learners: still working, motivated by productivity, asking “How can I use this to work faster and smarter?”
  • The curiosity-driven learners: in retirement, attending because their children or grandchildren wouldn’t stop talking about this “AI thing,” asking “What exactly is this, and why does it matter to me?”
Teaching both groups simultaneously in the same 90-minute session was the single hardest challenge of the role. I couldn’t optimise for one without alienating the other. The career-minded attendees would grow restless if I slowed down to explain what a large language model was from first principles. The retirees would glaze over if I jumped straight into prompt-engineering workflows for Excel automation.
And then there was the language barrier. I had spent my professional life operating entirely in English - writing code, reading documentation, building products. But many of the elderly students needed me to teach in my severely underdeveloped mother tongue. I was out of my depth, fumbling for words, constantly aware that my fluency in code did not translate to fluency in the language my students were most comfortable hearing. It forced me to slow down, to strip away every unnecessary layer of abstraction, and to communicate with precision and patience I had never exercised before.

🛠️ The Work

The resource situation at Iglow was sparse. The curriculum was unclear, and the existing materials were skeletal. I had to build the course content from the ground up - content that, I later learned, would become the baseline for the company’s future official education materials.
I redesigned the PowerPoint slides to be visually engaging, moving away from dense walls of text to graphics, diagrams, and visual metaphors that made abstract AI concepts tangible. I also created printed reference notes that students could take home, annotate during class, and cross-reference later when their attention wandered. These physical materials became surprisingly important; for an audience spanning multiple generations, having something tactile to hold and revisit lowered the cognitive barrier to entry.
Over my tenure, I personally led more than 10 workshops. I treated the curriculum as a living document, applying a continuous improvement model - updating slides weekly with the latest AI industry news, real-world contributions, and cautionary tales of misuse. If a new model dropped or a major AI policy was announced, it was in my next deck. This kept the material relevant and gave students a sense that they were learning something current, not static.
To keep my focus purely on the educational delivery, I partnered with someone who handled logistics and operations on a profit-sharing basis. That separation of responsibilities allowed me to obsess over the classroom experience without drowning in administrative noise.
The results spoke for themselves. Trainee satisfaction improved by 20%, and engagement levels rose by 30%. More importantly, students began recommending my lectures to their peers unprompted, quoting that the sessions were interesting and gave them new insight into the world of AI. That organic word-of-mouth meant more to me than any metric.

đź“š The Growth

This role did something my years as a software engineer and founder never did: it put me face-to-face with the end user.
In my previous roles, user feedback was abstract - analytics dashboards, support tickets, NPS scores. At Iglow, the feedback was a 65-year-old woman in the front row nodding when a concept finally clicked, or a 40-year-old manager staying back after class to ask how ChatGPT could help him draft performance reviews. I had to learn public speaking from essentially zero baseline. I had to develop empathy and patience for students who needed me to repeat a concept three times, not because they weren’t listening, but because the frame of reference was entirely foreign to them.
Teaching retirees about transformer architectures using my broken mother tongue taught me more about communication than any technical documentation ever could. You cannot hide behind jargon when your student is looking at you, confused. You have to find the metaphor, the analogy, the simple truth underneath the complexity.

🏫 The Lessons

1. đź“ť Preparation Beats Improvisation

I walked in thinking my technical depth would carry me. It didn’t. Every workshop that landed well was one I had over-prepared for - slides refined, analogies rehearsed, printed materials stacked, contingency questions anticipated. The classes where I tried to wing it based on my knowledge alone were the ones where I lost the room. Expertise without preparation is just noise. Preparation creates the structure that lets expertise shine.

2. 🎭 Adults Learn Differently Than You Expect

Adult learners are not empty vessels. They bring decades of context, skepticism, and competing priorities. The retiree learning about AI for the first time and the mid-career professional optimising their workflow need entirely different emotional contracts from a trainer. You cannot teach them the same way you would teach a uniform cohort of juniors. You have to design for the slowest and the fastest simultaneously, which means layering your content so every student leaves with at least one meaningful takeaway - regardless of where they started.

3. đź‘‚ The Best Trainers Are the Best Listeners

I used to think teaching was about transmitting knowledge. It’s not. It’s about diagnosing where the student is, what they fear, what they hope for, and what language they actually speak - literally and figuratively. Some of my best sessions weren’t the ones where I explained the most; they were the ones where I listened first, adjusted in real time, and met the room where it was. The best trainers don’t talk the most. They hear the best.

🎯 The Takeaway

My time at Iglow was never meant to be transformative. It was a side gig - a way to monetise knowledge I already had. But it became one of the most humanising professional experiences I’ve had. It forced me to translate technical complexity into empathy, to stand in front of a room and own the silence, and to understand that the real product in education isn’t the slide deck - it’s the connection between the person speaking and the people listening.
I eventually left after the company restructured compensation and shifted direction toward centralised control over materials. The freelance nature of the role meant it was always going to have a shelf life, and that centralisation closed the creative loop I had enjoyed. But the skills I built - public speaking, patience, the ability to read a room, and the discipline of preparation - are permanent.
Technical knowledge gets you in the door. The ability to make another human being feel seen, heard, and capable of understanding something new? That’s what keeps you there.