Waypoint™ MVP Scope and Release Boundaries
1. Purpose
Waypoint™ is intentionally broad. This document defines a practical first end-to-end product boundary without converting the specification into implementation epics or Jira tickets.
The goal of the initial product is to prove:
A user can design a project, approve a generated plan, authorize autonomous execution, deliver a validated outcome, and understand/control the entire lifecycle from Waypoint™.
2. MVP philosophy
The MVP should be vertically complete, not horizontally exhaustive.
It is better to support one strong end-to-end development-project path than implement partial support for many providers without completing the lifecycle.
The architecture must remain project-type neutral even if the first automated adapters focus on software development.
3. MVP user journey
The initial release should support:
- create a project;
- describe an objective conversationally;
- develop requirements/design documentation;
- assess design readiness;
- approve a Project Design Package;
- generate an Execution Plan;
- review phases/releases, epics, work, estimates, dependencies, streams, and worker forecast;
- approve the plan;
- materialize/synchronize work in Jira;
- authorize execution;
- dispatch work to at least one AI-agent runtime plus human work;
- execute parallel work safely;
- create source-control changes/PRs for a development project;
- run required tests/validation;
- capture evidence;
- identify delivery readiness;
- deliver through at least one automated provider path;
- validate delivery;
- record acceptance;
- report the complete lifecycle in Waypoint™.
4. MVP Design Engine
Include:
- project creation;
- conversational discovery;
- durable structured design state;
- requirements;
- scope/non-goals;
- decisions;
- risks/assumptions/open questions;
- generated Markdown artifacts;
- document revision;
- readiness assessment;
- Design Gate;
- versioned Project Design Package;
- planning handoff.
Defer/limit initially:
- many specialized design-agent personas;
- broad automatic cloud/repository inventory;
- advanced multimodal diagram understanding;
- large organizational template marketplace.
5. MVP Planning Engine
Include:
- decomposition;
- phases/releases;
- epics/work items;
- estimates;
- dependencies;
- streams;
- sprint/timebox support;
- capability requirements;
- human/AI eligibility;
- allocation forecast;
- plan validation;
- Plan Gate;
- Jira materialization/reconciliation;
- requirement traceability.
Defer/limit initially:
- sophisticated ML estimate prediction;
- portfolio-wide resource optimization;
- complex multi-project dependency scheduling.
6. MVP Execute Engine
Include:
- readiness service;
- executable queue;
- capability-based matching;
- reservations;
- durable execution runs;
- at least one AI-agent integration;
- human assignments;
- parallel streams;
- source-control workflow for development projects;
- testing/validation;
- evidence;
- failure retry/reconciliation;
- stall detection;
- pause/stop;
- actuals;
- discovered bugs/work.
Defer/limit initially:
- large heterogeneous agent marketplace;
- advanced agent-team optimization;
- autonomous cross-project worker balancing;
- many infrastructure/data execution providers.
7. MVP Delivery Engine
Include:
- delivery units;
- Delivery Gate;
- at least one automated delivery provider;
- manual delivery steps;
- post-delivery validation;
- rollback model;
- acceptance;
- handoff evidence;
- delivery reporting.
A strong initial development path could support Git-based promotion plus one deployment provider.
Defer/limit initially:
- many cloud providers;
- complex global rollout strategies;
- advanced canary/traffic management unless needed by the first target.
8. MVP Worker model
Include:
- human workers;
- AI agents;
- reusable agent profiles;
- capabilities;
- tools/environments;
- capacity/concurrency;
- assignment/reservation;
- autonomy/permissions;
- health;
- basic cost telemetry.
Model agent teams, automations, and external-system workers in the domain, but advanced orchestration may follow after the first release.
9. MVP Governance
Include:
- Design Gate;
- Plan Gate;
- execution authorization;
- quality/review gates;
- Delivery Gate;
- Acceptance Gate;
- roles/approvers;
- approval version binding;
- basic policy checks;
- exceptions;
- audit;
- evidence;
- pause/stop;
- basic budget threshold.
Defer/limit initially:
- highly expressive organization-wide policy language;
- complex compliance packs;
- advanced separation-of-duty matrices.
10. MVP Reporting
Include native dashboards and reporting APIs for:
- project lifecycle;
- pending decisions/gates;
- hierarchy progress;
- sprint/stream progress;
- estimate versus actual;
- active workers;
- blockers/failures;
- validation;
- delivery readiness/status;
- capacity/utilization;
- audit timeline.
A separate sophisticated BI experience can evolve later, but the API and reporting projections belong in the MVP architecture.
11. MVP integrations
Required categories:
- Jira;
- Git/source control;
- one AI-agent runtime;
- one automated delivery provider;
- authentication/identity;
- artifact storage.
Strong candidates for later expansion:
- additional agent runtimes;
- Azure infrastructure;
- additional cloud providers;
- CI/CD providers;
- Slack/Teams notifications;
- BI connectors.
Specific provider selection should be made during implementation architecture planning.
12. MVP Control Plane
Include:
- lifecycle state;
- artifact/version registry;
- gates/approvals;
- worker/capability registry;
- orchestration;
- durable run state;
- events;
- audit/evidence;
- reporting projections/API;
- integration configuration;
- reconciliation;
- notifications sufficient for required human decisions.
13. MVP adaptive execution
Include:
- structured execution discoveries;
- automatic disposition for low-risk in-scope discoveries;
- automatic Jira Task/Bug creation;
- estimates, dependencies, sprint/timebox, and stream placement;
- automatic execution when authorized;
- baseline versus current-plan preservation;
- reforecasting;
- configurable gates for material changes;
- reporting and audit of discovered work.
This capability is part of the MVP rather than a post-MVP optimization.
14. MVP UI
Minimum major surfaces:
- project list/dashboard;
- Design workspace;
- document/artifact review;
- Plan review;
- execution control room;
- worker/agent view;
- decision queue;
- delivery view;
- reports;
- administration/integrations.
The UI should make Waypoint™ usable without requiring constant navigation to Jira.
15. Documentation and developer quality
The Waypoint™ implementation should include:
- maintained architecture/product documentation;
- MkDocs Material site;
- strict documentation build in CI;
- PR template;
- automated PR compliance checks;
- source/work-item traceability;
- clean branch/workspace procedures;
- automated test requirements.
16. Release-boundary guidance
The planning process should derive exact releases, but a logical progression is:
Foundation
Canonical model, identity, integrations framework, project lifecycle, artifacts, events, reporting foundation.
Design
Conversational Design Engine and Project Design Package.
Plan
Planning Engine, Jira synchronization, estimates/dependencies/streams.
Execute
Worker registry, scheduler, agent integration, source-control execution, testing/evidence.
Deliver
Delivery provider, delivery gates, validation, acceptance.
Harden
Recovery, observability, security, performance, reporting depth, operational readiness.
This is guidance, not a mandated Jira release structure.
17. Post-MVP expansion
Likely expansion areas:
- infrastructure project execution;
- data-platform project execution;
- multiple AI-agent providers;
- advanced agent teams;
- project templates;
- reusable organizational skills;
- portfolio planning;
- predictive estimates;
- advanced cost optimization;
- policy packs;
- richer reporting/BI;
- additional delivery providers;
- cross-project dependency/capacity management.
18. MVP success criteria
The MVP succeeds when an owner can complete one realistic project end-to-end with:
- durable design artifacts;
- approved plan;
- Jira synchronization;
- autonomous and human execution;
- parallel work;
- evidence-based completion;
- controlled delivery;
- acceptance;
- reporting;
- audit;
- recovery from at least representative execution/provider failures.
The demonstration should prove the lifecycle, not merely individual screens or integrations.