progressive-estimation

name	progressive-estimation
description	Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
category	project-management
risk	safe
source	community
date_added	2026-03-10
author	Enreign
tags	["estimation","project-management","pert","sprint-planning","ai-agents"]
tools	["claude"]

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 Claude Code"

Batch mode:

"Estimate these 12 JIRA tickets for our next sprint"

With context:

"We have 3 developers using AI agents for ~60% of implementation. Estimate this feature."

Best Practices

• Start with a single task to calibrate before moving to batch mode
• Feed back actual completion times to improve the calibration system
• Use "instant mode" for quick T-shirt sizing without full PERT analysis
• Be explicit about team composition and agent usage percentage

Common Pitfalls

• Problem: Overconfident estimates Solution: Use P75 or P90 for commitments, not P50

• Problem: Missing context Solution: The skill asks clarifying questions — provide team size and agent usage

• Problem: Stale calibration Solution: Re-calibrate when team composition or tooling changes significantly

Related Skills

• @sprint-planning - Sprint planning and backlog management
• @project-management - General project management workflows
• @capacity-planning - Team velocity and capacity planning

Additional Resources

• Source Repository
• Installation Guide
• Research References

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.