I'm a business analyst and software developer based in Trinidad & Tobago 🇹🇹. I work on the operational side of business — procurement, inventory, freight, and the field processes that keep a company moving — and on where AI genuinely helps versus where it just adds a dashboard nobody opens. Most of what I learn ends up here, as writing and long-form video.
Denell Jonas · Trinidad & Tobago
Most of what gets written about supply chain assumes a context that does not exist here. It assumes predictable lead times, deep supplier benchmarks, several viable freight routes, and a team big enough to have a dedicated planner. Caribbean operations run on none of that. A single delayed vessel moves your whole month. One supplier going quiet can stop a line. The buffer that absorbs all of it is usually somebody's memory and a spreadsheet they maintain by hand.
That gap is what I write about. My background blends business analysis with hands-on software development, which means I tend to start with the workflow, the people, and the actual bottleneck rather than the tooling. The same instinct applies to AI: the interesting question is never can a model do this, it's whether the process around it is stable enough for the answer to be worth anything. A forecast built on data nobody trusts is just a more confident guess.
So each article takes one scenario — a stockout, a customs hold, a supplier that stopped answering, a count that never reconciles — and works it through honestly, including the parts where AI is the wrong tool. Every piece has a long-form video covering the same ground, and the templates and playbooks I build along the way end up in resources. I'm based in Trinidad & Tobago and work with teams across the Caribbean and further afield.
Writing and video come first; the builds are what the writing is drawn from.
Mapping how goods, information and approvals actually move — then finding the constraint that everything else is queued behind.
Stock accuracy, reorder points, and demand signals — the unglamorous groundwork that any forecasting model depends on.
Applying AI where the process can actually support it — document handling, exception triage, forecasting — and saying plainly when it cannot.
Finding suppliers, verifying they are what they claim, and turning a shortlist into a decision you can defend.
Digital forms, permits and job-site reporting that replace the paper trail without slowing the crew down.
One scenario per piece, worked through end to end — published as an article and a matching video.
Quick answers to the questions people ask most.
A supply chain that keeps surprising you, a process worth automating, or a question about where AI genuinely helps — I'd like to hear it.