SS-1

Intelligence layer · Built above TX-1 Terminal

Intelligence before
the screenshot.

SS-1 monitors your competitive landscape continuously and delivers a structured intelligence brief — before the LinkedIn post arrives and the reactive sprint begins.

SS-1SIGNAL SHELLMeridian Analytics
Scanning

14:28:02❯ ss1 sync

14:28:02Starting market sync for Meridian Analytics...

14:28:03[SCANNING] datavault-pro.com/changelog

14:28:04[SCANNING] datavault-pro.com/blog

14:28:05[SCANNING] insightflow.io/features

14:28:06[ANALYSING] Comparing snapshots against manifest context...

14:28:08[SCORING] DataVault Pro (changelog) → 72/100 — surfacing

14:28:08[SCORING] DataVault Pro (blog) → 29/100 — below threshold, discarded

14:28:09[SCORING] InsightFlow (features) → 18/100 — below threshold, discarded

14:28:10[PROPOSING] Generating intelligence brief for 1 significant signal...

[SIGNAL DETECTED]— DataVault Pro
72/100 WARNING

DataVault Pro ships Collaborative Workspaces

Source: datavault-pro.com/changelog

Direct hit on Analytical PM archetype. Real-time co-editing was a top-3 pain in every user research session. Roadmap item needs to accelerate from Q3 → Q2.

− Threat level: MEDIUM

+ Threat level: HIGH

+ Shift collaboration editing Q3 → Q2

UPDATE MANIFEST ⌘↵SAVE BRIEF ⌘BDISMISS Esc

5

LangGraph agent nodes

0

manual research steps

100%

HITL approval required

git

audit trail for every brief

The problem

Product teams are reactive by default. Not because they want to be — because competitive intelligence is a manual, periodic, expensive process.

Tuesday

Competitor ships

A competitor releases a feature. No one on your team knows yet. The changelog is live.

Wednesday

LinkedIn screenshot

Someone in the industry posts about it. Your PM sees it and screenshots it in Slack.

Thursday

Reactive sprint

A feature request lands in your backlog with no strategic context, no user impact analysis, no assessment of whether responding is even the right move.

SS-1 gives you the brief before the LinkedIn screenshot. Before the reactive sprint. Market intelligence treated as a stateful system process — not a research exercise.

What SS-1 does

Six capabilities, one terminal.

Continuous manifest monitoring

Your Project Manifest is a git-backed SSOT: vision, competitors, archetypes, priorities. SS-1 monitors the external world against it — continuously.

LangGraph intelligence pipeline

Five agent nodes: Monitor → Analyst → Significance Gate → Propose → HITL. Haiku for routing and scoring. Sonnet for analysis and brief generation.

Significance scoring

Not every competitor move deserves a response. Every signal is scored 0–100. Below 40 is discarded silently. Above 40 surfaces a card for your review.

Structured intelligence briefs

Not a news summary. A structured brief: what changed, strategic implication, proposed manifest update, and three strategic response options.

HITL approval gate

No manifest update without explicit user approval. Every agent-proposed change is previewed as a diff before it touches the file.

Git-versioned audit trail

Every approved brief creates a git commit. The manifest's evolution is an auditable record of how your competitive landscape changed — and how your thinking responded.

Key design decisions

Six choices that shaped the architecture.

All decisions →

01

Why a manifest file instead of a database?

A markdown file under git gives you a diff, a commit history, and a human-readable record. A database gives you none of those. The manifest is designed to be read by a human, not just queried.

02

Why HITL approval on every manifest write?

An agent that updates your strategy without asking is not an intelligence tool. It's noise. Every proposed change must pass through a diff preview and explicit approval before it touches the file.

About the builder

Anthony Key

Product designer and builder working at the intersection of AI systems and product strategy. SS-1 is the intelligence layer above TX-1 Terminal — together they represent a complete thesis about where enterprise AI tooling is heading: systems that don't just respond to what you ask, but anticipate what you need to know.

Every architectural decision in SS-1 is documented and defensible. This is not a side project. It is a portfolio artifact demonstrating AI product architecture, agentic systems design, and the kind of senior product thinking that connects technical choices to strategic outcomes.

Stack

Tauri v2

Desktop shell

React 19

Webview UI

LangGraph

Agent orchestration

FastAPI

Python sidecar

Claude API

Haiku + Sonnet

Firecrawl

OSINT crawler

SQLite

Local persistence

GitPython

Manifest versioning

TX-1 · SS-1

The execution layer. The intelligence layer.

TX-1 acts on problems inside your systems. SS-1 monitors for problems emerging outside them. The manifest schema connects them. Together they represent a complete picture of enterprise AI tooling — reactive and proactive, unified.