liqiongyu

managing-timelines

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# Install this skill:
npx skills add liqiongyu/lenny_skills_plus --skill "managing-timelines"

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# Description

Turn a deadline, launch date, or delivery target into an executable Timeline Management Pack (deadline type + commitments, phase plan, milestone tracker, RAG cadence, scope/change control, stakeholder comms). Use for timeline/deadline/schedule/milestones.

# SKILL.md


name: "managing-timelines"
description: "Turn a deadline, launch date, or delivery target into an executable Timeline Management Pack (deadline type + commitments, phase plan, milestone tracker, RAG cadence, scope/change control, stakeholder comms). Use for timeline/deadline/schedule/milestones."


Managing Timelines

Scope

Covers
- Turning a deadline or target date into a clear commitment model (commit vs forecast vs target)
- Building a phase-based plan (Discovery → Solutioning → Build → Launch) with decision gates
- Creating a milestone tracker with simple RAG (red/amber/green) status and escalation triggers
- Protecting the team when a deadline is real (treat it like P0, reduce distractions, control scope)
- Setting a governance + comms cadence so stakeholders get early risk signals, not surprises
- Handling “fast demo, slow production” cadence (especially for AI/ML features) via explicit outer-loop work

When to use
- “We need to ship by . Create a timeline/milestone plan and status cadence.”
- “We have a launch date; convert this into phases, milestones, and a comms plan.”
- “Stakeholders keep asking for dates; define what we can actually commit to and when.”
- “The project feels off-track; set up RAG status + weekly exec review and escalation.”
- “We can demo quickly, but production will take longer—help set expectations and plan the outer loop.”

When NOT to use
- You haven’t defined the problem/outcome yet (use problem-definition)
- You need to pick which initiatives matter most (use prioritizing-roadmap)
- You primarily need to cut scope to fit an appetite/timebox (use scoping-cutting)
- You need a decision-ready PRD or build-ready spec/design doc (use writing-prds / writing-specs-designs)

Inputs

Minimum required
- The deliverable and success bar (“done means…”) + key users/stakeholders
- The date type: fixed deadline (external) vs target (internal) vs window (e.g., “late March”)
- Constraints and non-negotiables (quality, compliance, privacy/security, platform, budget)
- Team shape + capacity assumptions (who’s building; availability; parallel work)
- Known dependencies and risks (other teams, vendors, data availability, approvals)

Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If answers aren’t available, proceed with explicit assumptions and list Open questions that could change the date or scope.

Outputs (deliverables)

Produce a Timeline Management Pack in Markdown (in-chat; or as files if the user requests):

1) Deadline & commitment model (what’s fixed, what’s variable; commit vs forecast vs target language)
2) Phase plan (Discovery/Solutioning/Build/Launch) with outputs + decision gates + next commitment date
3) Milestone tracker (owners, dependencies, dates, confidence, RAG) + RAG definitions
4) Governance cadence (weekly review agenda, escalation triggers, decision log)
5) Scope & change-control plan (cut list, non-goals, “trade don’t add” rule, freeze points)
6) Stakeholder comms pack (weekly update template + escalation note)
7) Risks / Open questions / Next steps (always included)

Templates: references/TEMPLATES.md
Expanded guidance: references/WORKFLOW.md

Workflow (8 steps)

1) Intake + deadline classification

  • Inputs: User request; references/INTAKE.md.
  • Actions: Identify the deadline type (fixed vs target vs window), the “why now”, and what variable can move (scope, resources, quality, or date).
  • Outputs: Deadline classification + constraints snapshot.
  • Checks: You can state: “The date is because . The variable we will trade is .”

2) Define the commitment model (“commit vs forecast vs target”)

  • Inputs: Deadline classification; current knowledge of scope/unknowns.
  • Actions: Define what you will commit to now (usually a phase output), what you will forecast, and what remains a target. Set confidence levels and language rules for stakeholders.
  • Outputs: Commitment model section + communication rules.
  • Checks: Stakeholders can tell which dates are promises vs estimates.

3) Build a phase plan with decision gates

  • Inputs: Deliverable; known unknowns; constraints.
  • Actions: Break the work into Discovery → Solutioning → Build → Launch. Define the output of each phase and the decision gate (what must be true to move forward). Only commit to dates that are within control (near-term).
  • Outputs: Phase plan with dates, outputs, and gates; “next commitment date” (when you’ll re-forecast).
  • Checks: Every phase ends with a tangible artifact and a go/no-go decision.

4) Create the milestone tracker (+ “demo vs production” outer loop when relevant)

  • Inputs: Phase plan; dependencies; team capacity.
  • Actions: Translate phases into milestones with owners, dependencies, dates, confidence, and RAG. If AI/ML is involved, separate “first demo” from “production-ready” and explicitly add evaluation, data, safety, and reliability work.
  • Outputs: Milestone tracker table + RAG definitions.
  • Checks: Milestones are outcome-based (deliverables), not just activities; critical dependencies are explicit.

5) Set governance: RAG + weekly reviews + escalation

  • Inputs: Milestone tracker; stakeholder map.
  • Actions: Define update cadence (weekly by default), who reviews, and escalation triggers (what turns yellow/red). Use a simple RAG system and a short weekly review agenda to unblock work.
  • Outputs: Governance cadence + weekly review agenda + escalation triggers.
  • Checks: A “red” status produces a concrete ask/decision, not just a warning.

6) Protect the deadline: scope control + distraction shield

  • Inputs: Deadline type; milestone risks; incoming requests.
  • Actions: If the deadline is real, treat it like P0: define what gets deprioritized, reduce WIP, and implement change control (“trade, don’t add”). Create a cut list and freeze points (e.g., scope freeze, QA freeze).
  • Outputs: Scope/change-control plan + cut list + freeze points.
  • Checks: New scope cannot enter without an explicit trade-off and decision owner approval.

7) Stakeholder comms + expectation management

  • Inputs: Commitment model; tracker; risks.
  • Actions: Write a weekly update template and an escalation note. Pre-wire stakeholders about uncertainty (especially the demo→production gap). Ensure comms use correct language (commit/forecast/target) and highlight asks/decisions.
  • Outputs: Comms pack (templates + initial draft update).
  • Checks: Updates include “what changed since last week” and “what decision is needed by when”.

8) Quality gate + finalize

  • Inputs: Full draft pack.
  • Actions: Run references/CHECKLISTS.md and score with references/RUBRIC.md. Ensure Risks / Open questions / Next steps exist with owners and dates.
  • Outputs: Final Timeline Management Pack.
  • Checks: A stakeholder can approve the plan async and the team can execute without re-litigating dates every week.

Quality gate (required)

Examples

Example 1 (fixed external date): “We’re launching at an industry event on May 15. Create a milestone plan, RAG cadence, and a comms template for Sales/Marketing/Execs.”
Expected: a fixed-deadline plan that treats the date as P0, with change control and clear escalation triggers.

Example 2 (AI uneven cadence): “We can demo an AI support agent in 2 weeks, but production will be risky. Build a plan that separates first demo vs production-ready and sets expectations.”
Expected: milestones that include evaluation, safety/reliability, and rollout steps; explicit commit vs forecast language.

Boundary example: “Decide what we should build this quarter and set dates for everything.”
Response: use prioritizing-roadmap first; then apply this skill to the chosen initiative(s).

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.