Introduction

AcmeTasker now includes a Smart Scheduling feature that automatically suggests optimal times for tasks based on your calendar and priorities. This document describes the feature in detail, including configuration, usage examples, and troubleshooting tips.

Overview

Smart Scheduling analyzes existing tasks, user availability, and external calendar integrations (Google Calendar, Outlook) to recommend due dates and times. It helps teams avoid conflicts and balance workloads.

Configuration

To enable Smart Scheduling, go to Settings > Features and toggle Enable Smart Scheduling. Administrators can configure lookahead windows and maximum daily hours per user.

Calendar Integration

Link your calendar via the Integrations page. The system supports OAuth for major providers. Once linked, calendar events will block suggested times.

Using Smart Scheduling

When creating or editing a task, click the Suggest button next to the due date field. Choose a recommended slot or manually pick a time. Suggestions appear in a dropdown with confidence scores.

Examples

  1. Create a task Prepare report and click Suggest; the system may recommend next Monday at 10 AM, avoiding existing meetings.
  2. Edit a high-priority task and request a slot; the algorithm may recommend working hours tomorrow.

User Interface

Smart Scheduling appears as a sidebar panel with time slots, color-coded by availability (green = good, yellow = tentative, red = conflict). Use keyboard arrow keys to navigate suggestions.

API Support

A new endpoint POST /tasks/{id}/suggest returns JSON suggestions: json { suggestions: [ {dueDate:2026-03-10T10:00:00Z,score:0.95}, {dueDate:2026-03-11T14:00:00Z,score:0.87} ] }

Troubleshooting

  • No suggestions shown: Ensure calendar is linked and user has at least one available hour in the next 7 days.
  • Incorrect suggestions: Verify timezone settings; suggestions use the user’s profile timezone.

Rollout Notes

Smart Scheduling will be rolled out gradually. Users can opt-in via their profile, and version 1.2.1 includes performance improvements.

Future Enhancements

Plans include machine learning models that learn individual work patterns and support for team-wide scheduling.