From 8f4716f87583519ba7718753beb85a68957e2a7d Mon Sep 17 00:00:00 2001 From: Ty Date: Wed, 8 Jul 2026 20:40:19 +0000 Subject: [PATCH] docs: add initial user stories --- docs/MVP-PRD.md | 34 ++++++++++++++++++++++++++++++---- 1 file changed, 30 insertions(+), 4 deletions(-) diff --git a/docs/MVP-PRD.md b/docs/MVP-PRD.md index a76a7a4..b2664c3 100644 --- a/docs/MVP-PRD.md +++ b/docs/MVP-PRD.md @@ -1,11 +1,11 @@ ## Chapter 1: Vision and Scope +### Elevator Pitch + +Athena is an autonomous research intelligence engine that cuts through high-volume, fragmented signals by ingesting from multiple sources, surfacing cross-source convergence, and using falsification to distinguish real momentum from noise. While the initial focus is on AI signals, the system is designed to work with any class of signals. It delivers actionable insight into emerging trends and capability gaps while remaining model-agnostic and lightweight enough to run autonomously. + ### 1.1 Vision -#### What are we building? - -Athena is an autonomous AI research intelligence engine designed to continuously ingest signals from multiple sources across the AI ecosystem, apply structured scoring, and use falsification logic to surface real practitioner momentum and cross-source convergence rather than noise. - #### Why are we building it? The AI space produces an overwhelming volume of new research, tools, discussions, and model releases every day. Individual sources only provide partial views, making it difficult to distinguish genuine, sustained trends from one-day spikes. Without a system that can detect convergence across sources and validate momentum over time, real opportunities tied to emerging capability gaps are missed. @@ -46,3 +46,29 @@ We will use the following prioritization model: - **P1**: Use cases that are fundamental to successfully implementing the product vision. - **P2**: Use cases that add strength, convenience, and quality to the product vision. - **P3**: Use cases that bring additional value but can be cut if time or resource constrained. + +## Chapter 2: User Stories (Bob) + +**As Bob, I want to…** + +**Bob-1.** Automatically receive daily updates on new AI innovations without having to manually check multiple sources. + +**Bob-5.** See emerging trends and differentiate durable signal from temporary or artificial hype. + +**Bob-10.** See when the same idea or pattern is appearing across multiple independent sources (GitHub, arXiv, Reddit, HN, HF). + +**Bob-15.** Identify emerging capability gaps or opportunities early, before they become widely obvious. + +**Bob-20.** Have research that gives me confidence it is exhaustive and vetted. + +**Bob-25.** Adjust or alter the underlying data feeds and weights so I can tune the accuracy and relevance of the output. + +**Bob-30.** Understand why a particular signal is considered strong or weak (e.g., cross-source convergence or falsification results). + +## Chapter 3: Requirements + +This chapter captures non-functional and system-level requirements that support the product vision but are not expressed as user stories. + +### 3.1 Reliability + +**REQ-REL-05:** Once setup and configured, the system will reliably operate without interaction from the user.