Productivity Route

A Team Capacity Planning Update With AI

Show leadership who's over-allocated, who has bandwidth, and what needs to change before the sprint starts.

8 steps ~30min For all professionals Free

A team capacity planning update shows current workload allocation across team members, flags over-allocation risks, and recommends adjustments for the next sprint or month. Most managers produce this by hand in a spreadsheet that takes 45 minutes to update and another 20 to format into a readable summary. At aidowith.me, the Weekly Status Update route covers this in 8 steps over about 30 minutes. You'll feed raw capacity data (hours, projects, deadlines) to AI, which generates a structured update with a capacity table, risk flags for anyone above 90% allocation, and 2-3 rebalancing options for leadership to approve. The route includes a prompt that turns plain-text task lists from Asana, Linear, or Jira into a formatted capacity table without manual reformatting. The output is ready to paste into a Slack message, email, or slide deck immediately after generating it.

Last updated: April 2026

The Problem and the Fix

Without a route

  • Building the capacity table takes 45 minutes every other week: pulling data from Asana, formatting in Excel, summarizing in a doc
  • You flag over-allocation verbally in standups but nothing gets documented, so the same problems repeat next sprint
  • Leadership asks 'how's the team doing on capacity?' and you have to say 'I'll get back to you' instead of answering on the spot

With aidowith.me

  • Generate a formatted capacity table with risk flags from raw task data in under 10 minutes using AI
  • Document over-allocation issues with rebalancing options so leadership can make decisions in the meeting
  • Answer capacity questions on the spot because the update is ready before the weekly review, not during it

Who Builds This With AI

Managers & Leads

Reports, presentations, and team comms handled faster.

Ops & Analysts

Summaries, process docs, and structured output from messy inputs.

Marketers

Content, campaigns, and briefs done in hours instead of days.

How It Works

1

Collect raw capacity data

Export task lists from your project tool or paste them as plain text. Include each person's name, active projects, estimated hours, and upcoming deadlines. Even rough estimates work for the AI input.

2

Generate the capacity table and risk flags with AI

AI converts the raw input into a formatted capacity table with columns for name, allocated hours, available hours, and utilization percentage. It flags anyone above 85% with a risk label.

3

Write the executive summary with rebalancing options

AI generates a 3-paragraph update: current state, key risks, and 2-3 options for rebalancing the over-allocated work. You review and adjust before sending.

Build Your Capacity Update in 30 Minutes

Follow the 8-step Weekly Status Update route at aidowith.me and ship a team capacity planning update with risk flags and options.

Start This Route →

What You Walk Away With

Collect raw capacity data

Generate the capacity table and risk flags with AI

Write the executive summary with rebalancing options

Answer capacity questions on the spot because the update is ready before the weekly review, not during it

"I used to spend Monday morning building the capacity deck. Now I paste in the task list and have a ready-to-send update in 12 minutes. My manager actually reads it now."
- Engineering manager, product-led startup

Questions

Collect each team member's current tasks and estimated hours, then paste the data into an AI with a structured prompt that requests a capacity table and risk summary. The aidowith.me Weekly Status Update route covers this in 8 steps, including how to handle incomplete data and how to frame rebalancing options for leadership.

Each team member's current tasks, estimated hours remaining, and due dates. You don't need exact hours: ranges work well (e.g., 4-6 hours). If your team tracks time in Asana, Jira, or Linear, the route shows you how to export and paste the data for AI to parse into a capacity table automatically.

Every sprint (1-2 weeks) is the standard for most product and engineering teams. Monthly works for teams with longer planning cycles. The route helps you build a template you can reuse in under 30 minutes each cycle, so the frequency is limited by how fast you can collect the data, not how long the update takes to write.