Quic-Cal: AI Agent Scheduling Assistant

AI scheduling assistant designed to reduce the friction of calendar setup by letting users create meetings through natural language instead of repetitive form-based workflows.

Product Vision

Quic-Cal is a productivity tool built around the idea that scheduling should feel conversational instead of procedural. Rather than forcing users to click through multiple meeting settings, the product accepts natural language prompts and translates them into actionable meeting details.

As a Google extension, the product was positioned as a centralized scheduling layer that saves time for people who create meetings frequently and want a faster workflow.

Market View

The scheduling market is crowded with products like Calendly, Google Calendar, and Microsoft Outlook. Those tools are strong in structured workflows and graphical interfaces, but they still rely heavily on manual setup.

Competitor strengths

• Calendly: simple setup, cross-calendar integrations, timezone handling.
• Google Calendar: seamless Google Workspace integration and familiar UI.
• Outlook: deep integration into Microsoft ecosystems with strong enterprise support.

Competitor weaknesses

• Calendly requires a subscription for fuller functionality.
• Google Calendar has limited third-party integrations and still requires too many screens and settings for scheduling.
• Outlook can feel overwhelming for new users.

Differentiation

• Unstructured natural language input instead of rigid forms.
• LLM-powered interpretation of user intent.
• Cross-platform scheduling workflow.
• Reduced setup time by eliminating repetitive clicks.

Problem Statement

Meetings consume a large portion of knowledge-work time, especially in consulting and collaborative roles. Existing scheduling flows create unnecessary overhead because users still need to manually configure dates, times, attendees, and event details through graphical interfaces.

Quic-Cal explored the idea that meeting setup could instead happen in chat form, with an agent handling the translation from prompt to calendar action.

Planned Features

• Schedule a meeting.
• Check availability at a requested time.
• Find attendee emails.
• Cancel a meeting at a given time.

Technical Direction

The architecture planning focused on agent actions such as:

• at_time to look for a free slot at a specific time.
• find_attendees to retrieve attendee emails.
• find_availability to check whether attendees are free.
• cancel_at_time to find and cancel a matching meeting.

Next Steps

• Learn and integrate Google APIs more deeply.
• Tune prompts and improve action recognition.
• Improve how the agent handles uncertain or incomplete inputs.
• Productionize the system through deployment and a stronger agent framework.