Turning Strategic Context Into a Prioritised Roadmap

Overview

From unstructured business context to reviewable roadmap data

I developed this completed strategic alignment tool for founders and product decision-makers who need to connect company priorities with roadmap execution. The AI agent gathers a structured strategic baseline, accepts document-assisted input, and lets users review answers before submission.

Its most important verified capability is a controlled path from unstructured business context to reviewable assessment data and a sortable, strategy-scored roadmap—without treating AI output as a final decision.

The challenge

Product planning rarely starts with clean, comparable context

Company goals, market priorities, resource constraints, success measures, and roadmap items may be expressed in conversation or spread across documents. That makes it difficult to maintain a consistent link between strategic intent and the work being considered.

The application needed to collect that context without forcing every user into manual data entry while preserving human judgement. Users still needed to see what had been captured, correct it, and decide when the assessment was ready to submit.

The solution

A stateful agent connected to a roadmap workspace

The assessment agent guides users through 22 questions covering the company, market priorities, resources, and measures of success. Users can answer conversationally, paste a structured response set, or provide a supported document for extraction.

The agent tracks completed and outstanding required questions. Extracted information feeds a reviewable assessment, and users can amend answers before explicit submission. The same application provides manual and AI-assisted roadmap intake, external scoring automation, and focused decision-support views.

How it works

A controlled path from assessment to prioritisation

1. 01

   Establish the strategic baseline

   After signing in, the user starts a guided assessment covering company context, customers, priorities, constraints, and success measures.

2. 02

   Bring in existing information

   The user answers in chat, pastes structured responses, or uploads a supported document. The agent extracts relevant answers and identifies what is still missing.

3. 03

   Validate with a person

   The application shows captured answers for review. Users can request corrections, while bulk replacement requires explicit confirmation.

4. 04

   Submit deliberately

   Submission is available only when required questions are answered. Once submitted, the assessment is locked against further chat edits.

5. 05

   Structure the roadmap

   Users create roadmap items manually or import a file. AI-assisted processing creates consistent records while dates and statuses are validated or normalised.

6. 06

   Run prioritisation

   An authenticated, credit-controlled action starts the connected scoring workflow and stores scores for sorting and comparison.

7. 07

   Review decision support

   Dashboard views centralise the prioritised roadmap, alignment indicators, objectives, competition analysis, and summaries for human interpretation.

What I delivered

Assessment, roadmap, governance, and access controls

• A stateful conversational assessment agent with guided question progression and streamed responses.
• Document-assisted extraction and structured pasted-answer matching.
• A review-and-correct stage before explicit assessment submission.
• Assessment persistence and configurable, versioned prompt templates.
• An isolated admin playground for evaluating prompt versions and inspecting run records without enabling production submission.
• A roadmap workspace with manual entry, upload, editing, bulk deletion, filtering, sorting, and CSV export.
• AI-assisted roadmap extraction and connection to an external scoring automation.
• Dashboard views for roadmap and strategic decision-support outputs.
• Authentication, protected routes, plan gating, usage credits, and user-scoped data access.

Reliability and human oversight

AI prepares information; people approve it

Required questions must be completed before submission, captured answers remain visible for review, and users can correct them through the conversation. Bulk pasted answers do not silently overwrite existing responses, and submission locks the editable chat flow.

Uploads reject missing or empty inputs. Roadmap extraction checks the expected structure, normalises recognised statuses, and validates dates before saving. The interface exposes processing, success, and error states.

Authentication protects dashboard, admin, and API routes. Plan gating, user-scoped queries, and scoring credits add further controls. Published prompt versions govern production while an isolated admin playground records runtime settings, traces, duration, and errors.

These are implementation safeguards, not an independent security audit.

Results and operational impact

Delivered operational capabilities

Technology choices

A connected full-stack AI workflow

• Next.js and TypeScript combine the interface, server actions, and authenticated API routes.
• OpenAI with LangChain powers conversational interpretation, streamed responses, and document-assisted extraction with zero-temperature assessment configuration.
• Clerk supplies identity and route protection.
• Supabase persists assessment state, usage information, prompt versions, and playground records.
• Airtable stores roadmap records and strategic output fields.
• Make receives authenticated scoring requests and connects the external prioritisation workflow.