progressive-estimation

Progressive Estimation

Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops.

Overview

Progressive Estimation adapts to your team's working mode — human-only, hybrid, or agent-first — applying the right velocity model and multipliers for each. It produces statistical estimates rather than gut feelings.

When to Use This Skill

• Estimating development tasks where AI agents handle part of the work
• Sprint planning with hybrid human+agent teams
• Batch sizing a backlog (handles 5 or 500 issues)
• Staffing and capacity planning with agent multipliers
• Release date forecasting with confidence intervals

How It Works

1. Mode Detection — Determines if the team works human-only, hybrid, or agent-first
2. Task Classification — Categorizes by size (XS–XL), complexity, and risk
3. Formula Application — Applies research-backed multipliers grounded in empirical studies
4. PERT Calculation — Produces expected values using three-point estimation
5. Confidence Bands — Generates P50, P75, P90 intervals
6. Output Formatting — Formats for Linear, JIRA, ClickUp, GitHub Issues, Monday, or GitLab
7. Calibration — Feeds back actuals to improve future estimates

Examples

Single task:

"Estimate building a REST API with authentication using