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4.4 — Agentic Project Management

Traditional project management assumes humans do the work. Agentic project management assumes AI does much of the execution while humans provide judgment and direction. The tools are similar; the assumptions are completely different.

Traditional PMAgentic PM
Estimate hours for each taskTasks complete in minutes, but verification takes time
Assign work to team membersAssign work to agents, review output
Daily standups for statusAgent logs and dashboards for status
Sprint planning by capacitySprint planning by complexity and risk
Risk = “will this person finish on time?”Risk = “will the AI get this right?” and “is this safe to automate?”
  1. Spec first — write a clear specification before any agent touches code. The spec is your contract with the AI. Ambiguous specs produce ambiguous results.
  2. Decompose aggressively — smaller tasks = higher accuracy. Large tasks drift. Break work into units an agent can complete and you can verify in one review.
  3. Verify each step — don’t chain 10 agent tasks without checking intermediate results. A bad output at step 3 corrupts everything downstream.
  4. Version everythingGit every change. Agent output is not inherently trustworthy — you need a record and the ability to roll back.
  5. Human judgment at decision points — automate execution, not decisions about what to execute. You decide the direction; agents execute the direction.
TermDefinition
Spec (Specification)A document describing exactly what needs to be built, how it should work, and what “done” looks like
SprintA fixed time period (usually 1–2 weeks) during which a set of tasks is completed
BacklogA prioritized list of work that hasn’t been started yet
BlockerSomething preventing progress on a task
StandupA brief status update meeting (or report)
Acceptance criteriaSpecific conditions that must be true for a task to be considered complete
IterationLooking back at what was built, what worked, what didn’t — then adjusting

Next: 4.5 — Speaking Engineer | Phase overview: Phase 4