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GenAI Strategy & Architecture
Original framework • Capability overview — not a client case study.
A practical way to move from a business objective to a buildable GenAI delivery plan. I use this structure to frame the use case, prioritize value and feasibility, define the target architecture, map data and integration boundaries, and sequence a proof of value.
Typical outputs: discovery notes, use-case prioritization, a solution blueprint, governance and evaluation checkpoints, dependencies, risks, and a phased delivery roadmap.
My role sits between business value and technical delivery: shaping the workflow, architecture, and implementation path so teams can build the right system with appropriate guardrails.
The network for creativity
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Creatives on Contra have earned over $150M and we are just getting started
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Seedance 2.5 is live!
I tested the exact same prompt twice and got two completely different results. It’s interesting to see how much the model can reinterpret the same idea depending on the generation.
Both have their strengths, but I definitely have a favorite.
Which one do you think is better, 1 or 2?
2 voted
25%
6 voted
75%
8 votes
Closed
I will go for option 2. Thank you.
Designed and built the core product experience for Beauto, an AI-powered automation tool for small businesses.
What I did:
AI Assistant — chat interface where users describe a task and the AI builds the automation, with proactive, impact-ranked suggestions
Integrations hub — searchable library of one-click connections (Calendar, Stripe, HubSpot, Slack, etc.)
Analytics dashboard — automations run, hours saved, and conversion rate at a glance
Result: A chat-first flow that felt far less intimidating than traditional automation builders in user testing, driving most new automations created.
So creative 👏
AI Digital Marketing Strategy Architect Design (Draft 1 of Project)
AI Digital Marketing Strategy Architect application. Here is a high-level overview of the project's architecture and features:
Core Functionality: The application is a comprehensive 4-phase digital marketing strategy builder that helps users plan, build, and automate their growth engines. It's designed with an elegant, editorial-style interface featuring high-contrast typography and clean layouts.
Phase 1: Foundation: A module for establishing the product's niche, generating detailed target personas using AI, and setting up the foundational tech stack (analytics, landing pages, email lists).
Phase 2: Content Engine: Focuses on organic reach. It includes an interactive SEO topic cluster generator, a visual ContentMap graph to visualize pillar links, and an AI-powered repurposing studio that transforms a single article into multiple formats (threads, LinkedIn posts, video scripts).
Phase 3: Growth & Acceleration: Built for paid and organic scale. Features a paid ad testing matrix with AI "Scale vs Kill" rules, an organic social winner analysis simulator, and an Answer Engine Optimization (AEO) readiness auditor.
Phase 4: Scale & Automation: Focuses on workflow automation. Includes a visual Zapier/n8n pipeline builder, a live lead simulator for AI-personalized email drafting, and an A/B testing loop optimizer.
Technical Architecture: A full-stack application utilizing React on the frontend and an Express server on the backend to securely manage Gemini API calls. It persists project state locally, includes preset templates (like SaaS or E-commerce), and offers a robust export engine to generate Markdown or Raw JSON blueprints.
Clean work