The same eight stages on every project, from the first conversation to years of running. Each one lists the practices I use and a project where you can see them.
Start with the problem, not the code.
I talk to the people who will use it and write down the one job it has to do. Then I cut the first release down to what proves the idea.
Settle the hard parts on paper first.
Data model, system architecture, API contracts and screen flows, before the first line of code. Multi-tenancy and payments get designed early, because they are expensive to change later.
Code the next engineer can pick up and own.
I use the stack that fits the job. Laravel or plain PHP for business systems, Node and TypeScript for real-time and media, Django for data-heavy work, React and Flutter for the front end.
Money, permissions and data get tested first.
Automated tests cover the rules that cost the most when they break: payroll, payments, who can see what, and one client's data staying out of another's.
$ php artisan test PASS Tests\Feature\BusinessRoleScopingTest PASS Tests\Feature\EmployeePortalScopingTest PASS Tests\Feature\EntitlementUnifiedFormulaTest PASS Tests\Feature\LeaveApplicationLifecycleTest PASS Tests\Feature\BiometricDeviceAttendanceTest PASS Tests\Feature\ClientImpersonationTest PASS Tests\Feature\CustomRoleBuilderTest … # 100 feature test files · HR & Payroll platform
Releases should be boring, on purpose.
Every change goes through the same automated path to production. Servers, workers and scheduled jobs are set up the same way each time and written down.
name: CI & Deploy # water vending frontend on: push: { branches: [main] } jobs: build-and-deploy: runs-on: ubuntu-latest steps: ✓ checkout ✓ setup node 20 npm ci ✓ build npm run build ✓ deploy rsync → AWS EC2 ✓ restart apache
Designed in from the start, then checked.
Access rules, login protection and payment safety are part of the design. They aren't a patch before launch. Where the law applies, like Kenya's Data Protection Act, the system is built to meet it.
$ curl -I https://pos.tafity.com strict-transport-security: max-age=31536000; includeSubDomains content-security-policy: default-src 'self'; … x-frame-options: SAMEORIGIN x-content-type-options: nosniff referrer-policy: strict-origin-when-cross-origin permissions-policy: geolocation=(), microphone=(), payment=()
Measured under load, then tuned.
I don't guess at capacity. I build a throwaway copy of the system, hit it with realistic traffic, break parts of it on purpose, and fix what gives way.
| Scenario | Load | Result |
|---|---|---|
| owner10k | One photographer uploads 10,000 photos | Gallery and downloads hold at 10k |
| read100k | 110,000 photos in one event | Gallery reads stay paged and fast |
| crowd | 200 guests uploading, 1,000 viewing | Guest uploads jump the queue |
| resilience | Kill API and worker, restart Redis, freeze Postgres | Recovers with no lost photos |
| bulk | 20,000-row import | ~1 min → a few seconds |
| capacity | 12-second video clips | 6 → 9.7 per minute (+62%) |
I stay after launch.
Software keeps changing after it ships. Tax rules change, clients ask for new modules, payments need reconciling. I keep systems current and keep them honest.
The practices that cut across every stage, each with a project that shows it working.
I measure first, then fix the slowest thing. Heavy work goes to background queues so pages stay quick.
Least privilege by default. Every login, change and payment leaves a trail you can check.
Built so the tenth client costs almost nothing to add. The API and workers scale separately.
Networks fail and payment callbacks arrive twice. The system expects both and recovers without anyone stepping in.
Tests guard the rules that matter, and catch slow database patterns before users feel them.
I connect software to the real world: mobile money, SMS, WhatsApp, prepaid meters, biometric clocks and receipt printers.
AI where it saves real work: reading receipts and CVs, drafting reports, answering questions over company data with a human approving any change.
When something goes wrong I want to know before the client calls. Structured logs, slow-query logs and admin health dashboards.
Tell me what you need. I'll reply within a day with questions, a rough approach, or a time to talk.