I have followed Claude Code closely since Anthropic released it. I have built AI systems in Jamaica since 2011 and run several technology companies in the region, including StarApple AI, the Caribbean's first AI company, so I care about what AI coding tools do for developers who work where I work.
My view: for a Caribbean founder with one or two engineers, Claude Code changes how much software a small team can ship. It does not remove the need to know what good software looks like.
What Claude Code does
Claude Code is Anthropic's agentic coding tool. It runs in your terminal or editor, reads the files in your project, makes changes across several files at once, runs your tests and commands, and fixes the errors it finds. By default it asks your permission before it edits a file or runs a command.
Earlier assistants completed the line you were typing. Claude Code works at the level of the application. Give it a Django project and it can trace the data models, views, serialisers and authentication flow, then change one part without breaking the others. Treat it like a fast, tireless junior engineer whose work still needs review.
Why it matters for a small Caribbean team
Most Caribbean startups cannot afford four engineers. They have a founder, perhaps a co-founder, and a product they need in front of customers before the savings run out.
I have watched Caribbean founders spend months on authentication, payment integration and data pipelines. Claude Code can scaffold that kind of standard plumbing in hours, which leaves the founder's time for the parts of the product that are specific to their market. For a bootstrapped company, months saved can decide whether it launches at all.
It also gives developers a reviewer. In Kingston, Port of Spain or Bridgetown, finding a senior engineer with distributed-systems or machine learning experience to review your code is hard and expensive. Claude Code can read your code and explain what is wrong with it. It does not replace an experienced colleague, but for a developer working alone it is far better than no review.
How we use it at StarApple AI
Across StarApple AI and our labs, Claude Code handles scaffolding while engineers focus on work that needs domain judgement. When the team prototypes an AI model, it builds the data pipelines, cleans training sets and sets up evaluation code. The Section 9 AI Lab used it for rapid prototyping across different modalities, and Maestro AI Labs uses it in pre-seed product development. We have not cut engineers. The same engineers ship more.
It takes skill to use well. A developer who cannot describe the architecture they want gets code that runs and is badly structured. That is why our free weekly AI training, now in its seventh year, still starts with fundamentals: you have to understand the system to direct the tool.
The gap between users and non-users
Developers who use these tools every day get better at briefing them, and that skill compounds. Over a year, a developer who has practised directing an agent will ship noticeably more than one who has not, and late nights will not close that difference.
For the Caribbean this is an opening. A two-person team in Montego Bay can now build software that used to need a funded team in London. I cannot yet measure how large that effect is across the region, and I would distrust anyone who claims a precise multiplier.
"For the Caribbean developer, Claude Code is an equaliser, and the developers who learn to direct it this year will set the pace for the next." Adrian Dunkley
What a Caribbean developer should do this month
- Pick a real project, not a toy. Choose one feature you need to ship in the next two weeks and let Claude Code work on it with you from the first commit.
- Write a project brief file. Before the first session, create a CLAUDE.md file in the project root describing the architecture, the conventions and the commands for running tests. Claude Code reads it at the start of each session.
- Brief it like a new hire. State the constraint, the files involved and what "done" means, including the test that must pass. Vague prompts produce plausible code that does the wrong thing.
- Review every change before you commit it. Read the diff line by line for the first month. You will learn from the review, and you will catch the errors it makes with confidence.
- Keep secrets out of the session. Store API keys and customer data outside the project folder or in files the tool is told to ignore, since anything it reads is sent to Anthropic for processing.
Then tell me what you built. I want to hear from the people doing the building.
Frequently Asked Questions
What do I need to start using Claude Code?
You need a computer with a terminal, the Claude Code installer from Anthropic's documentation, and either a paid Claude subscription or an Anthropic API account billed by usage. There are also extensions for VS Code and JetBrains editors if you prefer working there. Check Anthropic's current pricing page before you choose, as plans and limits change.
Does my code stay on my computer when I use Claude Code?
No. The files stay on your machine, but any file or command output Claude Code reads is sent to Anthropic's servers, where the model runs. Review Anthropic's commercial terms and data retention settings before you use it on client code. If a contract forbids sending code to third parties, get written permission first.
Is Claude Code useful for a developer who is still learning?
Yes, if you use it to explain as well as to write. Ask it why it made each change and what the alternative would have been, then check the answer against documentation. The common mistake is accepting code you cannot explain, which leaves you unable to fix it when it breaks in production.
How do I stop Claude Code making changes I did not want?
Work on a separate Git branch for each task, so you can throw away a bad session with one command. Keep the default permission prompts on until you trust the tool on that project. Ask it to propose a plan before editing, and approve the plan first.
Can Claude Code work on older systems written in languages it sees less often?
It reads most mainstream languages, including older ones such as PHP, Java and COBOL, but its output is weaker where public code is scarce or the house conventions are unusual. Give it examples of your existing code and a written note on your conventions. Test more heavily on legacy code than on a new project.