Blog
Insights and tips on productivity, time tracking, and building better work habits.
jonathan wu · May 26, 2026
AI Waste: How to Find and Eliminate Wasted AI Spend
Companies waste 30-50% of AI spend on shadow AI, idle licenses, and rework. Here is how to quantify AI waste per employee and redirect spend to where it works.
jonathan wu · May 25, 2026
AI Overuse: When AI Tools Hurt Productivity
40% of AI output gets reworked. Here is how to identify AI overuse, measure net productivity impact, and redirect spend to high-yield tasks.
jonathan wu · May 22, 2026
AI Efficiency Metrics: Which Numbers Actually Matter
Most AI efficiency metrics measure cost, not outcome. The metrics that matter: hours saved per AI dollar, yield per employee, and adoption depth.
jonathan wu · May 21, 2026
AI FinOps: Bridging Cloud Cost Management to AI Spending
AI FinOps extends cloud FinOps to cover LLM tokens, AI subscriptions, and per-employee compute. 98% of orgs have FinOps, but most miss the human cost layer.
jonathan wu · May 20, 2026
AI Tool Sprawl: When More Tools Mean Less Productivity
AI tool sprawl costs $412K/year in shadow AI when teams adopt overlapping tools without governance. ATT reveals duplication per employee.
jonathan wu · May 19, 2026
LLM Cost Management: Tokens, Models, and the Human Layer
LLM cost management goes beyond token pricing. Model routing, prompt caching, and per-employee attribution with ATT cut waste without degrading output.
jonathan wu · May 16, 2026
AI Usage Tracking for Teams: ATT vs Manual Surveys
Manual AI usage surveys miss 78% of actual tool usage. ATT captures every AI tool per employee automatically. Here is how the three approaches compare.
jonathan wu · May 15, 2026
GitHub Copilot ROI: What the Data Actually Shows
Microsoft says Copilot saves 3 hours per week. But 40% of AI time savings are lost to rework. Here is the real Copilot ROI math and how to measure yours.
jonathan wu · May 14, 2026
How to Measure AI ROI Without Guessing
67% of enterprises estimate AI ROI instead of measuring it. Here is the actual formula, per employee and per project, using ATT data instead of vendor dashboards.
jonathan wu · May 13, 2026
AI Adoption by Industry in 2026
AI adoption varies up to 3x by industry. Agencies lead on creative AI, tech dominates coding tools, and professional services spend the most per employee. See where your sector stands.
jonathan wu · May 13, 2026
AI Adoption Trends: 2024-2026 Data
AI adoption statistics from 2024 to 2026 show three phases: experimentation, adoption, and infrastructure. GitHub star data, enterprise spending, and Rize tracking data reveal what is actually accelerating.
jonathan wu · May 13, 2026
AI Tool Pairings: What 30K Workers Use Together
We tracked AI tool usage across 30,000 knowledge workers. Here are the most common tool pairings, hours per tool, and which stacks are gaining fastest in 2026.
macgill davis · May 13, 2026
Best Alternatives to Employee Monitoring Software (No Screenshots)
7 employee monitoring alternatives without screenshots. Compare Rize, Timely, Memtime, DeskTime, TimeCamp, Toggl, and Clockify for privacy-first tracking.
jonathan wu · May 13, 2026
Pre-IPO Work Patterns: What the Data Shows
How do pre-IPO startup teams actually work? Aggregate data from 30,000 Rize users shows they work longer but differently -- more focus time, more AI tools, and more weekend hours than public company peers.
jonathan wu · May 13, 2026
How to Detect Shadow AI With Automatic Tracking
78% of workers use unapproved AI tools costing $412K/year. ATT detects shadow AI automatically. No surveys, no browser extensions. 3-step playbook.
jonathan wu · May 12, 2026
AI Governance Starts With Visibility
You cannot govern AI tools you cannot see. 78% of employees use unapproved AI. ATT gives compliance teams automatic visibility into every AI tool in use. No surveys required.
macgill davis · May 12, 2026
Best Automatic Time Tracking for Windows
Compare the best automatic time tracking apps for Windows 10 and Windows 11. Rize, Timely, TimeCamp, and Toggl tested for background capture, accuracy, and team reporting.
jonathan wu · May 9, 2026
How to Measure ROI After AI Agent Deployment
AI agent deployment without measurement is guesswork. Learn how to measure ROI per employee using Agent Token Tracking (ATT) and AI Yield Optimization (AYO) — the framework that connects deployment spend to productivity outcomes.
jonathan wu · May 7, 2026
AI Budget Planning for Teams: How to Set, Track, and Defend Your AI Spend
A practical guide to AI budget planning for teams. Per-employee benchmarks, shadow AI discovery, the ACO→ATT→AYO framework, and how to build a budget your CFO will approve.
jonathan wu · May 7, 2026
AI Cost Management Is Broken — Here Is What Comes Next
AI cost management tracks tokens but not people. ATT (Agent Token Tracking) and AYO (AI Yield Optimization) close the gap between what you spend on AI and what you get back per employee.
jonathan wu · May 7, 2026
AI Cost Optimization: From Token Tracking to Productivity ROI
AI cost optimization starts with token-level tracking but stops short of measuring productivity. Learn how to move from LLM cost control to per-employee AI yield — the metric that turns spend data into ROI.