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Public roadmap
What has shipped and what we are building next. Updated regularly. Not a promise — a best-effort snapshot.
Q1–Q3 2026
shipped- Goals as the main screen — metric and project goals with baseline → target, milestones, and live progress from recorded contributions
- Opportunity Sandbox and per-team Solution Boards — kanban and table views, drawers, stage transitions with scoring gates (soft warnings and hard blocks)
- Reusable scoring library — RICC, ICE, WSJF, and custom formula models; any gate can reference any model
- AI research import — paste or upload raw research and interviews; get structured opportunities on the board
- Multi-user workspaces — invitations, owner/admin/editor/viewer roles, per-team roles, full audit trail
- Discovery health dashboard — funnel overview, bottleneck detection, gate health, driver load per team
- MCP server — AI agents read and update goals, opportunities, and solutions through 23 tools
- Public showcase — publish a read-only snapshot of goals and solutions at a share link
- Security and compliance baseline — DPA, Privacy Policy, Sub-processors, Security page; row-level security and audit log
Q3 2026
in-progress- MCP token management in Settings — mint and revoke agent access without leaving the product
- Recording goal contributions straight from the product UI when experiments close and solutions ship
- Pipeline editor polish — rename, reorder, and tune stages and gates without leaving the canvas
Q4 2026
planned- Team load heatmap — who is drowning and who is idling, surfaced in the dashboard
- Outcome attribution — tag every solution with a target metric and expected impact; roll up to the group level
- IQS freshness decay — insights that nobody has referenced in 90 days auto-dim; weekly digest flags zombie evidence
- Quarterly discovery digest — auto-generated summary of experiments decided, solutions shipped, and outcome deltas
Q1 2027
planned- Public launch and open signups (currently early access)
- CSV import from Productboard, Aha, or Google Sheets
- Jira two-way integration — link Sorby opportunities to Jira epics; sync status both ways
- Linear native integration
- Hypothesis similarity search — find past experiments with similar hypotheses before you start