Table of Contents
Overview
In today’s fast-paced work environment, understanding your productivity patterns and progress without adding another manual task to your to-do list has become essential. DoneThat addresses this challenge as an AI-powered productivity tracking tool designed to automatically monitor your work, establish realistic goals, and deliver actionable insights without requiring manual effort. Founded by an Effective Altruism community member and launched through the AIM Founding to Give program, DoneThat features robust privacy safeguards including no raw data storage and a quick 2-minute setup, transforming how individuals and teams understand and optimize their workdays.
As of October 2025, DoneThat operates with a 14-day free trial and subscription pricing starting at 5 dollars per month for individual users, positioning itself in the growing market of automated time tracking and AI productivity coaching tools that eliminate the burden of manual logging.
Key Features
DoneThat delivers comprehensive productivity insights through intelligent automation designed to require zero ongoing effort after initial setup.
- Automated calendar reconstruction from activities: DoneThat intelligently rebuilds your daily and weekly calendar by monitoring your actual computer activities including applications used, websites visited, and documents accessed, providing an accurate picture of how time is actually spent rather than relying on memory or estimates.
- Semantic task grouping and categorization: Leveraging AI natural language processing, the tool automatically analyzes your activities and groups them into meaningful work categories, making sense of diverse work patterns and eliminating the need for manual project assignment or timesheet categorization.
- Pattern detection and AI coaching for insights: Beyond passive tracking, DoneThat’s AI coach detects recurring patterns in your work habits, identifies potential time sinks, recognizes signs of burnout through workload analysis and optional mood tracking, and offers personalized suggestions for workflow optimization and better work-life balance.
- Goal tracking with input and output metrics: Set weekly goals and track progress with both input-focused metrics measuring time spent in specific categories and output-focused metrics tracking completion of specific objectives, helping maintain alignment between daily activities and strategic priorities.
- Comprehensive privacy safeguards: Your data security remains paramount with multiple protective layers including immediate processing of raw data without server storage, AI providers contractually prohibited from using data for model training, option to use your own OpenAI API key for processing, ability to pause tracking anytime or set specific work periods, AI prompted to ignore non-work activities flagging them as “something private,” manual review option through “Finish Day” button before finalization, post-hoc editing capabilities to remove or correct entries, and individual entry deletion from calendar view.
- Social sharing and team collaboration features: For users who opt in, DoneThat facilitates sharing of work summaries via email or Slack, provides public and private activity feeds enabling “building in public” workflows, offers team dashboards showing collaborative work patterns with privacy controls, and includes benchmark data comparing your patterns against anonymized aggregate statistics from other users.
How It Works
DoneThat streamlines productivity tracking through maximum automation combined with user control, designed for busy professionals who want insights without administrative overhead.
The process begins with a quick 2-minute installation of the desktop application, available for Windows, Mac, and Linux operating systems. Once installed, the lightweight background application runs quietly without impacting system performance, using AI to capture your computer activities including application usage, website visits, and document interactions.
From captured data, DoneThat’s AI automatically generates daily and weekly summaries categorizing time spent across different work types, detects patterns indicating focus periods, meeting-heavy days, or potential overwork, and suggests optimizations to improve workflow efficiency. The AI processing happens immediately with raw activity data never stored on DoneThat’s servers or those of AI processing partners, addressing privacy concerns common with employee monitoring tools.
Users retain complete control throughout with options to pause tracking for confidential work or personal browsing, edit generated summaries to correct miscategorizations, set specific work periods limiting tracking to designated hours, manually trigger daily summary generation through the “Finish Day” button for pre-finalization review, delete individual entries from the calendar view if sensitive information appears, and configure custom work categories aligned with personal or team taxonomy.
For teams, optional sharing features enable automated updates to colleagues via Slack or email, team dashboards providing visibility into collaborative work patterns without exposing individual activity details, and aggregate analytics helping identify team-wide patterns like excessive meeting time or uneven workload distribution.
Use Cases
DoneThat’s automated tracking and AI coaching capabilities serve diverse productivity scenarios where manual logging proves burdensome or where understanding work patterns drives improvement.
- Individual productivity optimization and goal alignment: Professionals seeking to understand work habits, eliminate time sinks draining hours without commensurate value, and align daily efforts with personal and professional goals benefit from DoneThat’s automated accountability and pattern recognition without investing time in manual tracking that itself reduces productivity.
- Team collaboration with transparency and burnout prevention: Distributed teams leverage DoneThat to foster transparency regarding work progress through opt-in activity sharing, identify potential overload before burnout occurs by tracking workload distribution and working hours, and proactively rebalance assignments when patterns reveal unsustainable workloads, building trust through objective activity data.
- Remote work trust-building via automated updates: In remote settings where visibility into daily work can feel opaque, DoneThat provides automated, objective updates on work activity that build trust and ensure alignment without constant check-ins or manual status reports, eliminating micromanagement while maintaining accountability.
- ADHD support through pattern recognition and accountability: Individuals with ADHD benefit from DoneThat’s automated pattern recognition identifying focus periods and common distractions, external accountability through activity tracking reducing procrastination, and concrete data revealing actual time allocation versus perceived time use, supporting better time awareness and task initiation.
- Freelancer and contractor time analysis for billing and efficiency: Independent professionals accurately track time spent on different client projects for precise billing without manual timer management, analyze efficiency patterns to identify profitable work types, optimize work schedules based on productivity data, and provide clients with detailed activity summaries building confidence in billing accuracy.
Pros \& Cons
Advantages
DoneThat delivers compelling benefits particularly valuable for users prioritizing automation and privacy in productivity tracking.
- Zero effort post-setup automation: Once installed, DoneThat runs automatically without requiring users to remember starting timers, manually categorizing activities, or filling timesheets, eliminating the productivity paradox where tracking time itself consumes valuable working hours.
- Strong privacy focus with user control: Multiple privacy protection layers including no raw data storage, AI providers prohibited from training on user data, pause functionality, work period limits, manual editing capabilities, and individual entry deletion put users firmly in control of their information, distinguishing DoneThat from invasive employee monitoring tools.
- Actionable AI insights beyond passive tracking: The tool transcends simple activity logging by offering intelligent pattern detection, personalized coaching suggestions, burnout risk identification through workload analysis, and contextual recommendations for workflow optimization, transforming raw data into actionable intelligence.
- Team features supporting asynchronous collaboration: Optional sharing capabilities, team dashboards with privacy controls, and aggregate benchmarking enable distributed teams to maintain alignment and identify collaboration patterns without sacrificing individual privacy or requiring synchronous check-ins.
- Affordable pricing structure: Starting at 5 dollars monthly for core features, 10 dollars for team capabilities, and 20 dollars for enterprise functionality with 14-day free trials, DoneThat provides budget-friendly access to automated tracking and AI coaching compared to enterprise time tracking solutions.
Disadvantages
As with any AI-powered productivity tool, DoneThat presents certain limitations and considerations users should evaluate against their specific requirements.
- Reliance on AI accuracy for categorization: The effectiveness of automated task grouping and insights depends on the AI’s ability to accurately interpret activities, which may require initial calibration, occasional manual corrections, and ongoing refinement as work patterns evolve, particularly for highly specialized or unconventional workflows.
- Limited to desktop environments: Current implementation operates exclusively as a desktop application for Windows, Mac, and Linux, creating blind spots for professionals whose work involves significant mobile device usage, tablet work, or frequent switching between devices not running the desktop agent.
- Potential over-reliance on automation for nuanced work: For highly creative, strategic, or knowledge work where time spent doesn’t directly correlate with productivity, automated categorization may miss important context about work quality, creative breakthroughs, or strategic thinking that occurs away from the computer, potentially leading to incomplete productivity assessment.
- Desktop-only activity visibility limitations: DoneThat captures only computer-based activities, missing time spent in physical meetings, phone calls, whiteboard sessions, paper-based work, or mobile device usage, requiring users to understand these blind spots when interpreting productivity data and potentially manually adding offline work entries.
- Early-stage platform considerations: As a relatively new tool launched through an accelerator program with ongoing development, users should anticipate feature evolution, potential bugs or edge cases, and possible changes to pricing or functionality as the product matures and finds product-market fit.
How Does It Compare?
The time tracking and productivity monitoring landscape in October 2025 offers diverse approaches from manual timers to fully automated monitoring. Understanding DoneThat’s positioning clarifies its distinct value proposition.
Automated Time Tracking Tools
Timely represents the leading fully automated time tracking solution focusing on eliminating manual logging for professionals and agencies. Timely’s Memory Tracker automatically captures work activities across applications, websites, and documents, then uses AI to categorize time entries into projects and clients based on learned patterns. The platform emphasizes private-by-default tracking where automatic capture data remains visible only to individual users until they approve entries for timesheets, addressing privacy concerns while enabling effortless time tracking.
Timely targets approximately 80% categorization accuracy through machine learning that adapts to individual work patterns over time. Pricing starts around 8 dollars per user monthly with emphasis on billable hour tracking, project profitability analysis, and team scheduling. While Timely excels at automated time capture for billing purposes, it focuses primarily on time allocation rather than the AI coaching and productivity pattern insights that distinguish DoneThat.
Memtime emerged in 2024-2025 as a simplified automated tracking alternative emphasizing minimalist interface design. Like Timely, Memtime runs in the background capturing activity data, but strips away complex project management and team features in favor of straightforward individual productivity tracking. Pricing remains competitive with lightweight plans, appealing to freelancers and solo professionals seeking automation without enterprise complexity.
DoneThat differentiates from these automated trackers through its AI coaching layer that goes beyond time categorization to offer pattern detection, burnout risk identification, goal tracking integration, and personalized optimization suggestions. While Timely and Memtime answer “how did I spend my time,” DoneThat addresses “how should I optimize my work patterns.”
Manual Timer-Based Tools
Toggl Track dominates the manual time tracking category with intuitive start/stop timer functionality favored by freelancers, agencies, and small businesses for billing and payroll purposes. Toggl combines manual timer control with optional automatic tracking triggered by specific applications or keywords, idle time detection, Pomodoro timer integration, favorite shortcuts for frequently-logged activities, and comprehensive reporting.
Toggl’s strength lies in precise control over what gets tracked and how it’s categorized, with users explicitly starting timers for specific projects and tasks rather than relying on AI interpretation. Pricing offers a generous free tier for up to 5 users with paid plans at 10 dollars and 20 dollars per user monthly, making it accessible for budget-conscious teams. However, Toggl’s reliance on manual initiation means users must remember to track time, creating friction that automated solutions like DoneThat eliminate.
Clockify provides similar manual tracking functionality entirely free for unlimited users, monetizing through premium features like custom reporting, time off management, and advanced team permissions. Clockify’s generous free tier makes it popular among startups and nonprofits prioritizing cost containment, though its manual approach creates the same activation energy challenge as Toggl.
DoneThat trades Toggl and Clockify’s granular manual control for comprehensive automation, appealing to users who find manual timer management disruptive to workflow or simply forget to track time consistently. The trade-off means less precise project-level billing data but broader insight into overall work patterns and productivity dynamics.
Productivity Monitoring Tools
RescueTime pioneered automatic productivity monitoring with different philosophy than time trackers—rather than measuring billable hours, RescueTime focuses on where attention goes and whether it aligns with productivity goals. RescueTime automatically tracks all computer activities, categorizes them into productivity levels from “very productive” to “very distracting” based on user-defined goals, provides focus mode blocking distracting websites during designated work sessions, and generates productivity reports showing time distribution across categories.
RescueTime Lite offers free basic tracking with premium plans at approximately 12 dollars monthly for enhanced features including detailed reports, goal tracking, and unlimited focus sessions. RescueTime excels at identifying distraction patterns and encouraging focused work but doesn’t provide team collaboration features or the AI coaching emphasis of DoneThat.
The key distinction between RescueTime’s approach and DoneThat’s lies in their primary objectives—RescueTime concentrates on distraction management and focus optimization while DoneThat emphasizes work pattern analysis, goal alignment, and team collaboration. RescueTime judges activities as “productive” or “distracting,” whereas DoneThat neutrally tracks work categories without moral judgment, leaving productivity assessment to users and AI coaching suggestions.
Enterprise Time Tracking Solutions
Enterprise platforms including Time Doctor, Hubstaff, and ActivTrak target larger organizations requiring employee monitoring, compliance tracking, and detailed productivity analytics. These tools typically feature screenshot capture, application and website monitoring with detailed logs visible to administrators, productivity scoring based on predefined criteria, integration with payroll and project management systems, and comprehensive reporting for management oversight.
Enterprise solutions start around 7-15 dollars per user monthly with higher-tier plans offering advanced features. While powerful for organizational oversight, these tools raise significant privacy concerns with always-on monitoring, administrator visibility into detailed activity logs, and surveillance-oriented design that can damage trust and morale.
DoneThat explicitly positions itself against invasive monitoring through privacy-first architecture where raw data never reaches servers, team visibility operates on opt-in rather than administrator surveillance model, and focus remains on individual and team productivity improvement rather than compliance enforcement. This philosophical difference makes DoneThat unsuitable for organizations requiring detailed employee surveillance but appealing for trust-based teams prioritizing productivity insights over monitoring.
DoneThat’s Market Position
DoneThat occupies a distinct position combining Timely’s automated capture, RescueTime’s productivity focus, and unique AI coaching capabilities with strong privacy protections. Its sweet spot serves professionals and small teams seeking effortless tracking without sacrificing privacy, wanting productivity insights beyond raw time data, needing team collaboration features without invasive monitoring, and prioritizing affordability and simplicity over enterprise complexity.
The platform suits remote teams building trust through optional transparency, individuals with ADHD benefiting from automated accountability, freelancers wanting billing accuracy without manual timers, and productivity-conscious professionals seeking pattern insights and coaching. It provides less value for organizations requiring detailed employee surveillance, professionals needing mobile device tracking, or those wanting granular project-level time allocation for complex billing scenarios.
Final Thoughts
DoneThat represents a thoughtful evolution in productivity tracking tools, successfully combining automated activity capture with AI-driven coaching while maintaining strong privacy protections. By eliminating the manual effort typically required for time tracking while delivering insights that transcend simple hour counting, DoneThat addresses genuine pain points for productivity-conscious professionals and teams.
The platform’s October 2025 positioning with affordable pricing starting at 5 dollars monthly, 14-day free trial, and privacy-first architecture makes it accessible for individuals and small teams exploring automated productivity optimization without enterprise budget commitments. The founder’s connection to the Effective Altruism community and transparent “building in public” approach fosters trust and suggests values alignment for ethically-minded users.
However, potential users should maintain realistic expectations about AI categorization accuracy requiring occasional manual corrections, desktop-only coverage creating blind spots for mobile-centric work, and early-stage platform maturity meaning feature evolution and potential growing pains. DoneThat works best as a complement to personal productivity practices rather than complete replacement for intentional time management and goal setting.
For professionals frustrated by the friction of manual time tracking, remote teams seeking trust-building transparency without surveillance, individuals with ADHD benefiting from automated accountability, and freelancers wanting billing accuracy with minimal administrative overhead, DoneThat merits serious evaluation. Those requiring detailed employee monitoring, precise project-level billing for complex engagements, or mobile device tracking should consider more comprehensive or enterprise-focused alternatives.
As the productivity tool landscape continues evolving with AI capabilities in October 2025, DoneThat’s combination of automation, coaching, and privacy positions it as a compelling option for users valuing effortless insights over exhaustive control, making it worth exploring during the free trial period to assess fit with individual workflow patterns and productivity goals.