Product Decision Impact Brain

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  Demo View

Live demo requires the running Codespace; see the video for a full walkthrough. Video link: https://youtu.be/fGibetl3_es

Core workflow: When a product decision changes, my brain reconstructs why the original decision was made, traces what depends on it, and helps the Product Owner manage the consequences.

Demo scenario: Leadership decides to postpone a planned feature. The brain connects the original decision and rationale to roadmap dependencies, customer commitments, engineering work, support documentation, owners, and AI-agent instructions.

The agent then:

1. Explains what is affected and why, with evidence from connected company knowledge.
2. Identifies conflicts, risks, and people who need to be involved.
3. Produces a prioritized action plan and drafts updated instructions for affected AI agents.

Inspiration

Product decisions rarely affect just one team. A change in direction can ripple through the roadmap, customer commitments, engineering work, and AI agents—but that context is often scattered across documents and meetings. I wanted to explore how a connected Company Brain could help Product Owners understand the consequences of a decision before those consequences become problems.

What it does

Product Decision Impact Brain helps Product Owners understand what happens when a product decision changes. It connects the original decision and its rationale to affected projects, dependencies, customer commitments, responsible people, and AI-agent instructions. It explains why each item is affected and generates a prioritized action plan, helping teams act on the full context rather than just the change itself.

How I built it

I used HydraDB as the persistent knowledge layer and built an application experience for exploring decision impacts. The workflow retrieves connected context, traces downstream effects, and presents evidence-backed recommendations and updated agent instructions.

Where the data comes from

I created a fictional company, Tandem, and used AI assistance to write 12 realistic company documents, including decision records, roadmap items, a SOC 2 readiness plan, customer commitments, policies, AI-agent instructions, help-center content, and a leadership Slack thread.

I ingested the documents into HydraDB as knowledge documents and explicitly defined 28 entities and 40 relationships through graph ingest. These connections link facts across documents—for example, an audit log satisfying SOC 2 control CC7.2 and a customer renewal depending on the SOC 2 timeline. In a real deployment, I would connect knowledge from existing company tools such as document systems, chat, and roadmap platforms.

Challenges I ran into

My main challenge was connecting related information and identifying meaningful downstream consequences rather than simply matching documents.

Accomplishments I'm proud of

I focused the Company Brain concept on a concrete Product Owner problem: understanding the wider impact of a changed decision and identifying actionable next steps.

What I learned

Connected knowledge becomes more valuable when AI can reason about relationships between decisions, people, projects, and commitments—not just retrieve documents.

What's next for Product Decision Impact Brain

I would expand the knowledge sources, improve impact analysis, and enable approved actions such as updating roadmap items, drafting stakeholder communications, and revising AI-agent instructions.

Built With

• appstarter
• claude
• hydradb