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CV Coach vs WDDNG vs Pairly

The problem, what was built, the stack and the outcome, next to each other.

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In common

  • Shared stack: Next.js
  • Both kinds of work: AI, Web
  • Order: CV Coach (2025 – present) → WDDNG (Jan 2026 – present) → Pairly (Jul 2026 – present)

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CV Coach ›

AI CV analysis, job matching and tailored applications

WDDNG ›

South Africa's wedding marketplace, with two apps on Google Play

Pairly ›

An AI-native operating system for founder-led teams

At a glance

Role
Founder / Lead Engineer
When
2025 – present
Length
1 yr 9 mo so far
Status
MVP
Type
AI, Web
Role
Founder / Full-stack & Mobile Engineer
When
Jan 2026 – present
Length
10 mo so far
Status
Live
Type
AI, Mobile, Web
Role
Founder / Lead Engineer
When
Jul 2026 – present
Length
4 mo so far
Status
In progress
Type
AI, Web, Platform

The problem

A Chrome extension captures job ads; a LangGraph workflow parses the CV and the ad, scores the match and drafts tailored cover letters and CV revisions.
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.
Small teams stitch together disconnected tools for websites, customer communication, content, analytics and operations, while generic AI assistants lack safe access to business context and actions.

What was built

A Chrome extension captures advertisements, stores them in PostgreSQL and queues analysis. The platform compares a CV with a job description, produces a structured match score and generates tailored cover letters and CV revisions.
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.
Pairly gives each business one governed platform where specialised agents can work across those functions. It combines tenant-scoped AI agents, websites and CMS, CRM and communications, newsletters, analytics, integrations and a skills marketplace.

Stack

  • FastAPI
  • Next.js
  • Supabase
  • LangGraph
  • LangChain
  • Celery
  • Next.js
  • Supabase
  • PostgreSQL
  • Kotlin
  • Jetpack Compose
  • LangGraph
  • Zod
  • Paystack
  • Azure
  • LangSmith
  • Python
  • FastAPI
  • PostgreSQL
  • Redis
  • Next.js
  • React
  • Azure
  • LangChain
  • Docker

Highlights

  • LangGraph workflow with custom tools to parse, compare evidence and score the match
  • Asynchronous analysis pipeline
  • 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
  • Tenant-scoped agent runtime with durable memory, model routing, typed tools and permission ceilings
  • Streaming agent UX with human approval gates, audit events and token budgets
  • Installable skills marketplace with automated validation and human publication review
  • End-to-end features spanning API, CMS, renderer, email and PDF output

Infrastructure choices

—
  • Supabase with PostgreSQL RLS
  • PostgreSQL

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.
A broad working platform with multi-tenant permissions, real-time agent execution, publishing and revision workflows, provider integrations and installable skills, with approval gates, audit events and human review for consequential AI actions.