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This is the live call log from NowNow AI's production system — an AI client coordinator I built for South African medical and dental practices. When a patient calls, an AI voice agent answers in under 2 seconds, handles the enquiry, books the appointment, captures medical aid details, and logs everything into a structured database in real time. Every row you see here represents a call that would otherwise have gone to voicemail or been lost entirely — after-hours, lunch breaks, double-bookings on reception. The stack runs on Retell AI for voice, Make.com for orchestration, and Google Sheets as the live data layer, with WhatsApp follow-up firing automatically post-call so patients never get ghosted. Built end-to-end as a solo developer: voice agent prompting, automation pipeline, data architecture, and the client-facing dashboard.
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I kept seeing the same pattern over and over—good ideas getting lost in vague execution. A founder would describe something powerful in their head, but by the time it reached design or strategy, it had already been diluted into fragments.
It felt like there was a missing layer between thinking and building.
DKRAFT started as an attempt to close that gap—to turn scattered intent into structured clarity, and clarity into something real enough to build from.
“I built DKRAFT — an autonomous brand system that turns any vague business idea into a full creative agency output: strategy, identity, campaigns, and case studies.”
Instead of manually designing brands piece by piece, DKRAFT acts as an autonomous creative operating system that:
understands business context
classifies brand type
extracts strategic variables
defines emotional positioning via archetypes
generates brand storytelling
determines full deliverable scope
My Process
Identified real-world problem: fragmented branding workflows
Brainstormed with ChatGPT to refine the idea
After that i wrote a prompt that broke down the idea phase by phase, to Design DKRAFT as a multi-agent creative system, leveraging the Melius Agent to design the first phase of the system
This enabled me add more nodes manually for more depth in the system, I broke down branding into structured intelligence layers:
intake
strategy
identity
storytelling
execution mapping
Built modular prompts for each phase and nodes, instead of a single monolithic system, this Ensured system adapts based on:
business type
industry
audience
emotional archetype
the result is a full end-to-end flow from vague idea → complete brand system
VYBE STUDIOS
In this presentation i was able to use the system to come up with a brand called VYBE STUDIOS .. a media company, who's mission is to democratize elite-level creative production, giving every story teller the tools to capture attention and define culture at the speed of thought.
Key Innovation
The system allows the user to trigger node groups of their choice as it is required from their deliverable, which is also generated within Melius. They also have the ability to rewrite their brief with the Brief rewriter node. The system uses archetype-based emotional reasoning for storytelling, it also dynamically determines deliverables based on business type (not fixed templates).
Builds scalable “creative reasoning layers” instead of static outputs
TOOLS USED
Chatgpt - Refining Idea
Melius - Building the system
Feedback on Melius
I must say this was my first time using Melius, but been familiar with system thinking and writing executive layer prompts, I was able to navigate through ..
One thing i like about Melius, is the clear separation of agents,
structured workflow design, iterative prompt chaining and fast experimentation of system logic
The biggest opportunity is in improving real-time visual debugging of node flows and output dependencies for multi-agent systems.
Walkthrough video link
Project Link
this is such a cool use case!
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