Product marketing teams operating across complex, multi-product portfolios face a structural challenge: the volume of strategic output required — positioning statements, messaging frameworks, channel strategies, launch timelines, RACI matrices, success metrics, competitive response playbooks — is enormous, and the tools available to produce it have not kept pace with the demands placed on them.
Each of these workstreams demands a distinct type of strategic output. Historically, these documents live in separate Google Docs, are authored by different team members, and are reviewed asynchronously — often with no systematic check for whether the narratives across plans are consistent with one another.
The result is a team that is highly capable but operating below its potential: too much time spent on document production, too little time on strategic thinking, and a persistent risk that consumer-facing narratives across different product lines drift out of alignment.
Creating a single GTM plan required assembling inputs from multiple stakeholders, synthesising them into a coherent narrative, and populating six to ten separate document sections — a process that routinely took one to two weeks per plan, even for experienced PMMs.
Without a structured review process or a consistent template, plan quality varied significantly depending on who authored it and how much time they had. VP-level reviews frequently surfaced gaps in competitive framing, weak positioning rationale, or missing success metrics.
With multiple plans running in parallel — across product tiers, competitive responses, and market expansions — there was no mechanism to detect when two plans were making contradictory claims about the same consumer segment, or when channel strategies were cannibalising each other.
The GTM Strategy Hub is a purpose-built web application that transforms raw strategic inputs — product briefs, competitive intelligence, audience research, pricing rationale — into fully structured, VP-ready go-to-market plans. It is not a template filler or a document formatter. It is an AI reasoning system that applies a three-pass generation pipeline: first synthesising the strategic situation, then developing the core strategy, then populating each output section with content that is internally consistent and grounded in the inputs provided.
The platform was built on a modern full-stack architecture (React 19, tRPC, Drizzle ORM, TiDB) with a custom LLM integration layer. Every procedure is typed end-to-end, and the AI generation pipeline is structured to return validated JSON schemas — not free-form text — ensuring that every output section is machine-readable, renderable, and exportable without post-processing.
11-section structured output covering strategic narrative, positioning, messaging, channel strategy, launch timeline, partner enablement, success metrics, RACI, competitive response, gap analysis, and response success scoring.
Any individual section can be regenerated with a steering prompt — allowing PMMs to refine specific parts of a plan without restarting the entire generation process. Changes are persisted immediately to the database.
A second LLM pass acts as a senior VP reviewer, scoring the plan out of 10, surfacing specific weaknesses, and generating actionable recommendations. Score history is tracked across iterations to show improvement over time.
Cross-plan AI analysis detects messaging overlap, audience conflicts, and coverage gaps across the entire plan portfolio. A portfolio health score (0–100) provides a single metric for narrative alignment.
Built-in review request and feedback system with public reviewer links, blocking/suggestion feedback types, re-review flow, and weekly digest notifications — replacing ad-hoc email review chains.
AI-powered slide editor that generates a 12-slide exec deck from the plan, supports theme customisation and AI chat-based refinement, and exports directly to Google Slides or as a PDF.
Supports ingestion of PDF, DOCX, Markdown, images, and Google Drive folders. LLM-powered extraction auto-populates all relevant form fields, reducing manual data entry to near zero.
Team-level narrative management with a narrative ladder visualisation showing how each plan connects to the team's core strategic threads. An audience ownership registry surfaces conflicts before they reach consumers.
The PMM uploads a product brief, competitive brief, or existing plan — or fills in a structured 8-section input form. Documents are parsed by LLM vision and text extraction; all relevant fields are auto-populated across the plan's input schema.
The three-pass AI pipeline synthesises the situation, develops the strategy, and populates all 11 output sections with structured, validated content. Portfolio context from existing plans is injected to ensure consistency from the first draft.
The VP Critique engine scores the plan and surfaces specific improvements. PMMs apply recommendations with one click, regenerate individual sections with steering prompts, or use the Slide Studio AI chat to refine the exec deck narrative.
The plan is shared with stakeholders via a secure review link. Reviewers submit structured feedback directly in the platform. The PMM resolves feedback, triggers a re-review, and exports the final plan to Google Slides or PDF.
The GTM Strategy Hub fundamentally changes how a product marketing team operates. The most immediate impact is on efficiency: what previously required one to two weeks of document production now takes a fraction of the time. The AI generation pipeline produces a complete, structured first draft in minutes, and the VP Critique engine surfaces the most important improvements before the plan ever reaches a human reviewer.
But the deeper impact was on output quality. Because every plan is generated from the same structured pipeline, with the same quality bar enforced by the VP Critique engine, the floor of plan quality rose significantly. The average VP Critique score across the portfolio climbed from a baseline of 5 to a consistent 8–9.
The most strategically significant outcome was the improvement in narrative coherence across the portfolio. The portfolio coherence analysis engine made this invisible problem visible for the first time. The team's portfolio coherence score reached 88 out of 100 — a level of narrative alignment that would have been practically impossible to achieve and maintain manually.
The GTM Strategy Hub is not a prototype or a proof of concept. It is a production-grade web application built with a modern, typed full-stack architecture. Every API call is a tRPC procedure with end-to-end TypeScript types. The database schema is managed with Drizzle ORM. The AI generation pipeline uses structured JSON schema responses — not free-form text — ensuring that every output is machine-readable and renderable without post-processing.
The application includes 91 passing Vitest unit tests covering the AI generation pipeline, slide builder, review workflow, recommendation application, and coherence analysis. The TypeScript compiler reports zero errors.
Frontend framework with Tailwind CSS 4 and shadcn/ui components
End-to-end typed API layer with superjson serialisation
Type-safe database layer with schema-first migrations on TiDB
Three-pass generation pipeline with structured JSON schema responses and VP critique engine
Authenticated Drive ingestion, Google Slides export via REST API, and folder bulk import
All uploaded documents, generated presentations, and exported PDFs stored on S3 with CDN delivery
91 passing unit tests covering all critical backend procedures and AI pipeline logic
OAuth-based authentication with role-based access control and session management
The GTM Strategy Hub is, at its core, a demonstration of what happens when you apply serious product thinking to the tools that knowledge workers use every day. The problem it solves — fragmented, inconsistent, time-consuming document production — is the default state of most strategic planning work in large organisations.
What makes this project distinctive is not the use of AI — that is table stakes. What makes it distinctive is the depth of the domain model: the structured input schemas, the typed output sections, the VP critique rubric, the portfolio coherence scoring system, the stakeholder review workflow. Each of these represents a deliberate decision to encode domain expertise into the system, rather than leaving it as a general-purpose text generator.
The result is a tool that does not just save time. It raises the quality ceiling of what the team can produce, makes invisible problems visible, and creates a shared language for strategic quality that did not exist before. That is the difference between a productivity tool and an intelligence platform.
"The difference between a productivity tool and an intelligence platform is whether it encodes domain expertise — or leaves it as a general-purpose text generator."
The GTM Strategy Hub methodology is available as a Moylan Catalyst tool or a full consulting engagement.