Most AI Programmes Fail Because Nobody Bridges the Gap Between Tech and People
13 years in people analytics. Now building the tools and programmes that close the gap between AI potential and everyday adoption.
13 years in people analytics. Now building the tools and programmes that close the gap between AI potential and everyday adoption.
Working with organizations to integrate AI agents into their workforce, not just their tech stack.
My technical background: building multi-agent workflows with n8n, Claude, Gemini, and Cursor. I work with both local and cloud solutions, testing what actually delivers efficiency versus what just sounds good in vendor pitches.
My HR focus: workforce transformation. How do you introduce AI agents to teams? Where does adoption break down? What training works? How do you measure productivity when half your "team" is automated?
The real skill isn't coding—it's understanding where AI fits in a team's workflow and how to get people comfortable working alongside it.
I'm interested in projects that treat AI integration as an organizational challenge, not just a technical one. Systems that combine multiple agents, automate complex workflows, and actually improve how teams operate—not just replace headcount.
Transformation isn't about the tools you deploy. It's about the teams you build when AI becomes part of the workforce.
RAG-powered chatbot that answers MOM compliance questions with cited legislation — section number, clause, and source URL.
HR teams waste hours digging through the Employment Act and scattered MOM guidelines to answer routine compliance questions. This chatbot grounds every answer in actual legislation and adapts its response by role — penalty clauses and employer obligations for HR, plain-English rights and complaint pathways for employees.
Evaluates Singapore neighbourhoods in 3D so buyers can make faster, better-informed purchase decisions.
Property decisions involve scattered data — URA records, school proximity, amenities, transport links. This app consolidates it into a single AI-guided view with 3D neighbourhood visualisation, built end-to-end in 6 hours at the Gemini API Hackathon.
Turns YouTube videos and web articles into structured LinkedIn posts and blog drafts in minutes.
Content research is the bottleneck in professional writing — sourcing, watching, summarising, and structuring takes hours. This AI agent automates the pipeline from URL input to publication-ready draft, so the work is editing, not starting from scratch.
The past four weeks, I've been shared the basics of AI, prompting techniques, the 5 Pro Tips framework, how to treat AI like a fresh hire you need to give clear instructions to. It was all theory.
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AI chatbots like Claude aren't just for answering questions, they're surprisingly effective learning partners. The key is knowing how to prompt them.
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Think about the last time you onboarded someone fresh out of school. Eager, capable, fast, but completely lost without direction. That's your AI. The people who complain that AI "doesn't work" are usually the same ones who'd hand a new employee a vague task and get frustrated when the result misses the mark. The problem isn't the tool. It's the management.
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