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Picking & Packing app vs WhatsApp platforms vs WDDNG
The problem, what was built, the stack and the outcome, next to each other.
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In common
- Shared stack: none in common
- Order: WhatsApp platforms (2018 – 2022) → Picking & Packing app (2025 – 2026) → WDDNG (Jan 2026 – present)
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Picking & Packing app ›
A Kotlin warehouse app for fulfilment teams
WhatsApp platforms ›
Altur, Harambee and eButler on the WhatsApp Business API
WDDNG ›
South Africa's wedding marketplace, with two apps on Google Play
At a glance
- Role
- Lead, Smart Kitchen Co
- When
- 2025 – 2026
- Length
- 1 yr
- Status
- Delivered
- Type
- Mobile
- Role
- Lead engineer, Mmogo Media
- When
- 2018 – 2022
- Length
- 4 yr
- Status
- Delivered
- Type
- Platform, AI
- Role
- Founder / Full-stack & Mobile Engineer
- When
- Jan 2026 – present
- Length
- 10 mo so far
- Status
- Live
- Type
- AI, Mobile, Web
The problem
An Android app that drives picking and packing for warehouse and fulfilment operations.
A WhatsApp-based job platform (Altur), Harambee Youth Accelerator's move from a mobisite to WhatsApp, and eButler's WhatsApp ordering with payments through Flash.
South African couples plan across fragmented directories, WhatsApp messages and opaque “price on request” listings, while many international tools don't support local multi-ceremony wedding journeys.
What was built
—
—
A Next.js and Supabase marketplace with two Kotlin / Jetpack Compose Android apps on Google Play: one for couples, one for vendors. Thuli, the AI planner, is a LangGraph supervisor coordinating 16 specialist agents.
Stack
- Kotlin
- Android
- Python
- Django
- WhatsApp Business API
- Infobip
- Twilio
- Next.js
- Supabase
- PostgreSQL
- Kotlin
- Jetpack Compose
- LangGraph
- Zod
- Paystack
- Azure
- LangSmith
Highlights
- Led architecture and development
- Built in Kotlin for warehouse floor use
- Conversational journeys on the WhatsApp Business API
- Payments via Flash, Paystack and MTN MoMo
- Two Kotlin / Jetpack Compose Android apps published on Google Play
- Thuli: a LangGraph supervisor coordinating 16 specialist agents through Zod-typed handoff tools
- Per-agent model selection, token metering and LangSmith tracing
- SSE streaming that renders vendor cards and progress during an answer
Infrastructure choices
—
—
- Supabase with PostgreSQL RLS
Outcome
—
—
The marketplace runs across web and two production Android apps, giving couples structured planning tools and vendors better-qualified enquiries with date, budget and guest-count context.