About the Project
This project was developed following an intensive one-day workshop with Vitaly Friedman (Smashing Magazine), where we explored advanced UX processes and practical AI workflows. During the session, we learned how to structure prompts effectively, which tools to leverage throughout the design process, and actionable best practices for integrating AI into product development.
Challenges
We had to unify a fragmented ecosystem, balance simplicity with advanced control, ensure privacy and offline reliability, manage energy data efficiently, and design a solution scalable to any home size.
Timeline & milestones
✅ Discovery workshop & project scope definition
✅ Research phase: smart-home ecosystem, interoperability, user expectations
✅ Technology strategy: multi-protocol compatibility (Zigbee, Z-Wave, Wi-Fi, Matter, BLE, etc.)
✅ UX & UI concepting, flows and low-fidelity wireframes
✅ Automation engine & scenarios architecture
✅ Energy usage monitoring specification & dashboard layouts
✅ Privacy & security definition: encrypted communication, local-first mode
✅ Open API & plugin system planning
✅ Scalability & performance considerations
About the Project
This project was developed following an intensive one-day workshop with Vitaly Friedman (Smashing Magazine), where we explored advanced UX processes and practical AI workflows. During the session, we learned how to structure prompts effectively, which tools to leverage throughout the design process, and actionable best practices for integrating AI into product development.
Challenges
We had to unify a fragmented ecosystem, balance simplicity with advanced control, ensure privacy and offline reliability, manage energy data efficiently, and design a solution scalable to any home size.
Timeline & milestones
✅ Discovery workshop & project scope definition
✅ Research phase: smart-home ecosystem, interoperability, user expectations
✅ Technology strategy: multi-protocol compatibility (Zigbee, Z-Wave, Wi-Fi, Matter, BLE, etc.)
✅ UX & UI concepting, flows and low-fidelity wireframes
✅ Automation engine & scenarios architecture
✅ Energy usage monitoring specification & dashboard layouts
✅ Privacy & security definition: encrypted communication, local-first mode
✅ Open API & plugin system planning
✅ Scalability & performance considerations
About the Project
This project was developed following an intensive one-day workshop with Vitaly Friedman (Smashing Magazine), where we explored advanced UX processes and practical AI workflows. During the session, we learned how to structure prompts effectively, which tools to leverage throughout the design process, and actionable best practices for integrating AI into product development.
Challenges
We had to unify a fragmented ecosystem, balance simplicity with advanced control, ensure privacy and offline reliability, manage energy data efficiently, and design a solution scalable to any home size.
Timeline & milestones
✅ Discovery workshop & project scope definition
✅ Research phase: smart-home ecosystem, interoperability, user expectations
✅ Technology strategy: multi-protocol compatibility (Zigbee, Z-Wave, Wi-Fi, Matter, BLE, etc.)
✅ UX & UI concepting, flows and low-fidelity wireframes
✅ Automation engine & scenarios architecture
✅ Energy usage monitoring specification & dashboard layouts
✅ Privacy & security definition: encrypted communication, local-first mode
✅ Open API & plugin system planning
✅ Scalability & performance considerations
Process & Methodology
Our approach followed a user-centered design framework, enriched by insights from Vitaly Friedman’s workshop:
Search for examples, competitors, inspirations, these will be included into the prompt to give the LLM the best context to build from
Use chat GPT to generate the perfect Lovalble promp
Prompt lovable with the perfect prompt
Refine the lovable results (debug)
The workshop learnings were instrumental in shaping the project, helping us work faster and smarter while maintaining clarity of vision.
Process & Methodology
Our approach followed a user-centered design framework, enriched by insights from Vitaly Friedman’s workshop:
Search for examples, competitors, inspirations, these will be included into the prompt to give the LLM the best context to build from
Use chat GPT to generate the perfect Lovalble promp
Prompt lovable with the perfect prompt
Refine the lovable results (debug)
The workshop learnings were instrumental in shaping the project, helping us work faster and smarter while maintaining clarity of vision.
Process & Methodology
Our approach followed a user-centered design framework, enriched by insights from Vitaly Friedman’s workshop:
Search for examples, competitors, inspirations, these will be included into the prompt to give the LLM the best context to build from
Use chat GPT to generate the perfect Lovalble promp
Prompt lovable with the perfect prompt
Refine the lovable results (debug)
The workshop learnings were instrumental in shaping the project, helping us work faster and smarter while maintaining clarity of vision.
Key outcomes & impact
Unified smart-home control from a single interface
Powerful automation engine accessible to beginners and experts
Energy insights & consumption dashboards for efficient and eco-responsible usage
Local-first, privacy-centric architecture with secure connectivity
Highly scalable modular ecosystem ready for future integrations
Key outcomes & impact
Unified smart-home control from a single interface
Powerful automation engine accessible to beginners and experts
Energy insights & consumption dashboards for efficient and eco-responsible usage
Local-first, privacy-centric architecture with secure connectivity
Highly scalable modular ecosystem ready for future integrations
Key outcomes & impact
Unified smart-home control from a single interface
Powerful automation engine accessible to beginners and experts
Energy insights & consumption dashboards for efficient and eco-responsible usage
Local-first, privacy-centric architecture with secure connectivity
Highly scalable modular ecosystem ready for future integrations
