The Metrics That Actually Predict Developer Output
AI token burn rate. Context switching cost. Deep focus windows. Language velocity. Go beyond hours tracked — understand how you build.
Intelligence preview
AI output and human effort on the same screen.
Leverage score, token load, agent hours, and human hands-on time sit together as operational metrics instead of vague AI magic.
The problem
"Hours worked" is the worst proxy for developer productivity.
An 8-hour day with 47 context switches and 3 hours in Slack is not the same as 4 hours of uninterrupted deep work. And now that AI assistants consume real tokens (real money), no one is tracking the cost of AI-assisted development. The metrics we use to understand developer work haven't evolved with how developers actually work.
AI token intelligence
How much is your AI pair programmer costing?
Claude, Copilot, and ChatGPT consume real tokens. DevClocked tracks token usage per session so you can understand the ROI of AI-assisted development.
Est. Monthly AI Cost
Based on 22 working days
Context switching cost
Every interruption costs 23 minutes of recovery.
Research from UC Irvine shows it takes an average of 23 minutes to return to a task after an interruption. DevClocked detects context switches and quantifies their cost.
Daily Productivity Lost
1.5 hours of recovery time
Code intelligence
Understand what you're building, not just how long.
Language breakdown, framework usage, file type distribution, and complexity trends — automatically derived from your coding sessions.
LANGUAGE_BREAKDOWN
FOCUS_METRICS
Avg. Focus Window
47m
Deep Work Ratio
62%
Context Switches/Day
18
Peak Flow Hour
10 AM
AI_USAGE
AI-Assisted Time
38%
of coding sessions
Token Burn This Week
284K
$12.40 estimated
Most Used AI Tool
Claude Code
72% of AI sessions
Flow state analysis
See your day as a flow timeline.
Deep work blocks, shallow work, and interruptions — visualized across your day. Identify your peak hours and protect them.
Frequently Asked Questions
Everything you need to know about DevClocked
Focus windows (deep work duration), context switch frequency, AI tool token usage, language and framework breakdown, peak productivity hours, and flow state patterns. All derived automatically from your tracked sessions.
DevClocked integrates with AI coding tools (Claude Code, Copilot, etc.) to track token consumption per session. You can see which projects consume the most AI tokens and calculate the ROI of AI-assisted development.
A context switch is when you move between unrelated tasks — switching repos, changing projects, or moving from code to a meeting. DevClocked detects these by monitoring project/repo changes and idle gaps within sessions.
Team intelligence features are on the roadmap. Individual intelligence is available now. Team views will show aggregate patterns (not individual surveillance) — team focus windows, project allocation, and AI adoption metrics.
Beyond time tracking
Understand how you build.
Hours tracked is just the start. DevClocked gives you the intelligence layer to optimize your workflow, quantify AI ROI, and protect your deep work.
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