Dashboard Automator Strategist Logic

Source Summary

Document Metadata

• title: Strategist Logic
• description: What the AI strategist layer is trying to achieve and how to interpret its outputs
• status: evolving
• lastUpdated: "2026-02-13 07:22 ET (America/New_York)"
• owner: Product/Engineering # Strategist Logic This document explains the "strategist" layer in Dashboard Automator: the logic that turns messy project signals (G

Imported Context

Document Metadata

• title: Strategist Logic
• description: What the AI strategist layer is trying to achieve and how to interpret its outputs
• status: evolving
• lastUpdated: "2026-02-13 07:22 ET (America/New_York)"
• owner: Product/Engineering

Strategist Logic

This document explains the "strategist" layer in Dashboard Automator: the logic that turns messy project signals (GitHub activity + manual notes) into goals, health signals, risks, and recommendations for an owner-operator portfolio.

If you want the implementation/architecture map, see DOCS/how-it-works.md.

Problem This Project Solves

Portfolio status for a solo developer is usually scattered:

• GitHub activity shows movement, but not intent, priorities, or whether work is "on track".
• Manual notes exist, but they do not aggregate across projects and are hard to keep consistent.
• Producing a portfolio-level update becomes a recurring tax: time spent collecting signals instead of shipping.

Dashboard Automator aims to reduce that tax by continuously ingesting activity, synthesizing likely goals, and publishing a snapshot you can use as a command center and export artifact.

High-Level Goals (Strategist Outcomes)

The strategist is optimized for a single authenticated owner-operator workflow (current MVP reality). Its outcomes are:

• Convert activity into intent: infer 2-4 plausible goals per repository (not a full roadmap).
• Create portfolio-level focus visibility: summarize overall focus/health and surface cross-repo risks.
• Make health legible at a glance: compute KPIs and per-project health labels for fast scanning.
• Support auditing and iteration: persist agent runs and allow explicit user evaluations of AI outputs.
• Generate a stable artifact: create a JSON snapshot suitable for export and downstream workflows.

Inputs (What The Strategist Uses)

The strategist primarily works from:

• GitHub ingested events per included repo (commits, PRs, issues, releases).
• Manual logs you add inside the app (notes/tasks/conversations), optionally attached to a repo.
• Repo metadata (language, stars, open issues, description).

Outputs (What The Strategist Produces)

Repository goals

For each included repository, the strategist synthesizes 2-4 goals with:

• title
• description
• status: active | completed | at_risk | stalled
• confidence: 0.0-1.0 (model-provided)
• evidence: short textual citation of the activity/notes that motivated the goal

Portfolio analysis

For the whole included portfolio:

• focusScore: 0.0-1.0 (model-provided)
• risks: { repo, risk, severity } with severity high | medium | low
• recommendations: 3-5 actionable next-step suggestions
• summary: 2-3 sentence health narrative

Snapshot (portfolio artifact)

The strategist emits a single JSON snapshot containing:

• KPIs (repo count, activity totals, goal totals, open-issue totals, etc.)
• portfolio analysis (above)
• per-project summaries including a computed healthScore and healthLabel
• a 30-day activity timeline
• a "recent activities" feed

Strategist Mechanics (Current Logic)

The strategist loop (conceptual)

1. Ingest: fetch recent GitHub activity into the database.
2. Synthesize: generate repo goals from the latest activity + manual logs.
3. Analyze: generate portfolio-level focus, risks, and recommendations.
4. Snapshot: assemble a portfolio snapshot (KPIs + health + timeline) and store/export it.

Time windows and truncation

Current implementation intentionally bounds input size:

• Goal synthesis uses up to 30 most recent activities per repo.
• Portfolio snapshot uses a rolling 30-day activity window and keeps a top 50 "recent activities" list.

Scoring and labels (non-AI)

Some outputs are deterministic heuristics (not model-generated):

• activityScore = min(1, recentRepoActivities / 20)
• goalScore = average(goal.confidence) for the repo (fallback 0.3 when there are no goals)
• healthScore = activityScore * 0.5 + goalScore * 0.3 + (openIssues > 0 ? 0.2 : 0)
• healthLabel derived from healthScore:
  • >= 0.7 => healthy
  • >= 0.4 => warning
  • else => critical

Note: the current openIssues term increases score when open issues exist. If you intend open issues to reduce health, this term should be inverted in a future checkpoint.

Trust Model (Confidence, Gating, and Review)

The strategist stores a numeric confidence per goal (model-provided) and exposes it in the UI.

Product docs define a stricter UX target (only show outputs >= 0.85 in primary views, with lower-confidence content accessible in a closed drawer), but that gating behavior is not currently implemented in the UI. Today, the system records and displays confidence rather than suppressing low-confidence outputs.

The system does support:

• Agent run logging (inputs, outputs, latency, token usage).
• Human evaluation of runs (rating + verdict + feedback) to drive iteration.

Constraints and Non-Goals (Strategist Scope)

Constraints:

• JSON-only snapshot export.
• Single-user, session-authenticated usage (current MVP scope).
• No external "source of truth" beyond GitHub + manual logs in the app database.

Non-goals (currently):

• Fully automated project management or deterministic roadmaps.
• Multi-tenant team workflows and role-based access control.

Provenance

• Source file: Dashboard-Automator/DOCS/strategist-logic.md
• Source URL: https://github.com/maggielerman/Dashboard-Automator/blob/main/DOCS/strategist-logic.md