Waypoint™ Adaptive Execution and Continuous Replanning

1. Purpose

Waypoint™ must maintain the plan while it executes it.

An approved Execution Plan is the authorized baseline, but execution inevitably reveals information that was unavailable or uncertain during Design and Planning. Waypoint™ should convert those discoveries into governed work, update the operational plan, and continue autonomously when policy permits.

The objective is:

Learn during execution without silently changing approved scope, architecture, risk, or delivery commitments.

2. Core principle

Waypoint™ maintains two related views:

• Approved Baseline Plan — the approved version against which scope, estimate, schedule, and outcomes are measured.
• Current Execution Plan — the operational plan including authorized discoveries, defects, replanning, actuals, and forecast changes.

The baseline is preserved. The current plan evolves.

3. Discovery sources

New information may originate from:

• AI workers;
• humans;
• automated tests;
• CI/CD;
• external systems;
• monitoring;
• Jira comments;
• source-control review;
• delivery validation;
• reconciliation;
• security checks;
• data-quality checks;
• provider failures.

4. Discovery classification

Waypoint™ should classify discovered information before acting.

Suggested classes:

• implementation task;
• defect in current work;
• pre-existing defect;
• required test;
• documentation work;
• dependency;
• technical prerequisite;
• estimate variance;
• schedule variance;
• capacity issue;
• design deficiency;
• new requirement;
• scope change;
• security/compliance concern;
• cost/budget impact;
• delivery risk;
• external blocker.

Classification should retain confidence and provenance.

5. Proposed Change / Discovery entity

A structured Discovery or ProposedChange record should contain:

• discovery_id;
• project_id;
• source;
• source work/run;
• classification;
• description;
• rationale;
• affected requirements/work;
• estimated impact;
• risk;
• proposed disposition;
• confidence;
• policy decision;
• gate requirement;
• resulting work/change references;
• status;
• timestamps.

Free-text worker comments alone are insufficient.

6. Disposition engine

Waypoint™ should evaluate each discovery against policy and choose a disposition.

Potential dispositions:

• ignore/no action;
• record for later;
• create work automatically;
• create defect automatically;
• update dependency;
• adjust estimate/forecast;
• reassign/reschedule;
• request human review;
• reopen Planning;
• reopen Design;
• block affected execution;
• raise security/compliance escalation;
• raise Delivery Gate condition.

The disposition itself must be auditable.

7. Default autonomy model

A practical default policy:

All thresholds are configurable.

8. Automatic Jira maintenance

When Jira is enabled as the operational work ledger, Waypoint™ should continuously maintain it.

Waypoint™ may:

• create Task/Bug work items;
• populate descriptions and acceptance criteria;
• attach provenance;
• estimate work;
• establish parent hierarchy;
• add dependencies/links;
• assign stream;
• assign sprint/timebox;
• assign or label worker/team;
• update status;
• add relevant execution comments;
• link source-control/delivery artifacts;
• reconcile external changes.

Every executable discovered item should satisfy the same work-quality rules as originally planned work.

9. Sprint and stream placement

New work should not simply be placed into the current sprint by default.

Placement should consider:

• urgency;
• blocking impact;
• sprint objective;
• available capacity;
• dependencies;
• stream;
• required capability;
• delivery/release impact;
• policy.

Waypoint™ may automatically place work when policy permits or propose placement at a gate.

10. Immediate execution

Newly created work may become executable immediately when:

• it remains within approved scope;
• policy permits automatic disposition;
• dependencies are satisfied;
• capability/capacity exists;
• execution authorization covers it;
• no new gate is required.

The scheduler then treats it like any other executable work.

11. Plan maintenance

Adaptive execution may update:

• work hierarchy;
• dependencies;
• estimates;
• forecasts;
• sprint membership;
• streams;
• capability demand;
• delivery-unit composition;
• risk;
• acceptance/testing work.

Material changes create a new Execution Plan version or controlled amendment.

12. Baseline protection

Waypoint™ must never erase the original approved plan.

Reporting should distinguish:

• baseline work;
• discovered work;
• removed/superseded work;
• defect/rework;
• approved scope growth;
• estimate change;
• schedule change.

This is essential for understanding why delivery differed from the original plan.

13. Design feedback

Some discoveries indicate that the design itself is incomplete or incorrect.

Examples:

• architectural assumption invalid;
• integration behaves differently than expected;
• security constraint conflicts with design;
• requirement is ambiguous;
• target environment cannot support proposed solution.

Waypoint™ should:

1. stop only the affected execution path where practical;
2. record the discovery;
3. identify impacted requirements/decisions/work;
4. raise the appropriate Design Gate;
5. produce proposed design changes;
6. version the Project Design Package if approved;
7. invoke Planning to update affected work;
8. resume from the updated authorization boundary.

14. Planning feedback

Planning changes that do not alter design may be handled within Plan.

Examples:

• task split;
• new dependency;
• estimate change;
• resource/capacity shift;
• additional validation;
• changed sprint sequencing.

Waypoint™ should minimize unnecessary return to Design.

15. Learning across projects

Execution history should improve future planning.

Potential reusable learning signals:

• recurring omitted work;
• estimate accuracy;
• capability performance;
• common dependencies;
• failure patterns;
• test requirements;
• delivery prerequisites;
• project-template improvements.

Learning should initially be evidence-driven and explainable.

Waypoint™ should not silently modify organizational planning rules from opaque model inference.

16. Pattern suggestions

Waypoint™ may identify patterns such as:

Projects using technology X commonly require task Y.

A learned suggestion may be:

• informational;
• proposed for project template;
• automatically applied under policy;
• submitted for human approval.

Reusable organizational changes should be versioned and governed.

17. Continuous reconciliation

Adaptive execution requires continuous reconciliation among:

• canonical Waypoint™ plan;
• Jira;
• source control;
• execution providers;
• delivery systems.

Drift may be caused by humans changing external systems directly.

Waypoint™ should classify drift and either:

• accept/import;
• correct external projection;
• request review;
• raise conflict.

18. Reporting

Reporting should expose:

• baseline versus current plan;
• discovered work count/effort;
• discovered defects;
• rework;
• scope growth;
• estimate variance;
• forecast variance;
• disposition decisions;
• automatic versus gated changes;
• design reopenings;
• planning amendments;
• recurring discovery patterns.

19. Audit

For every autonomous plan mutation, retain:

• discovery source;
• classification;
• policy evaluated;
• disposition;
• work created/changed;
• estimate/schedule impact;
• gate decision if any;
• actor/worker;
• timestamp;
• baseline/current-plan references.

20. MVP requirements

Initial Waypoint™ should support:

1. structured discoveries;
2. automatic creation of in-scope Tasks/Bugs;
3. estimates and dependencies;
4. Jira hierarchy/sprint/stream placement;
5. automatic execution when authorized;
6. configurable thresholds for gates;
7. baseline/current-plan distinction;
8. reforecasting;
9. Design/Plan escalation;
10. reporting and audit of discovered work.

Advanced cross-project learning may follow after sufficient execution history exists.