Progressive Estimation

Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops

Published by @sickn33 and contributors·0 agent reads / 30d·0 saves·

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.

Bundled with this artifact

2 files

Reference files that ship alongside this artifact. Agents pull these in only when the task needs them.

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