Skip to content

M4 v1.0 Launch

Due Aug 31, 2026

Planned1 / 33 (3%)
Exit criteria (0/4)
  • ☐ v1.0 release published for Cloud + OSS with clear version contract.
  • ☐ Migration/versioning workflow built-in and documented.
  • ☐ Onboarding repeatable without founder-only support.
  • ☐ Reliability + support metrics sustain target levels for 30 days.
KPI targets (0/3)
  • ☐ Activation and conversion improve vs M3 baseline.
  • ☐ Core reliability SLOs met over rolling 30 days.
  • ☐ Early retention/expansion signals trending positive.

Tasks by Workstream

dft core (Sr Engineer Architect)

Post-launch stabilization is complete for the YAML contract, compiler/normalizer, execution adapters, and release/versioning: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

cloud suite (UI Design and Frontend Dev)

Post-launch stabilization is complete for hosted user experience for onboarding, sharing, collaboration, and account/project flows: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

inspect profiler (Sr Engineer Architect)

Post-launch stabilization is complete for warehouse profiling, semantic inference, and analyst-facing data context surfaces: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

mcp analyst agent (Data AI Engineer Architect)

Post-launch stabilization is complete for AI agent tool interfaces, execution workflows, and eval-driven behavior tuning: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

ft dash packs (Data Analysis Evangelist and AI Training)

Post-launch stabilization is complete for connector-specific dashboard packs and KPI narratives for Fivetran sources: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

ide extension (Head of Engineering)

Post-launch stabilization is complete for analyst authoring workflow in VS Code/Cursor with preview, diagnostics, and assist: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

graph library (Data Visualization Designer and Engineer)

Post-launch stabilization is complete for visual language, chart defaults, interaction behavior, and differentiated styling: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

  • ☐ Regression prevention and quality gates — Add or enforce regression gates around chart default behavior so release quality is sustained automatically.
  • ☐ Sustainable operating model — Document and adopt sustainable operating model for interaction/accessibility polish across support, triage, and release…
  • ☐ v1.0 stability and defect burn-down — Run stability program for visual language system with recurring defect burn-down and reliability trend tracking.
  • ☐ Conditional Formatting — Implement conditional formatting primitives for the graph library to encode thresholds, exceptions, and trend states vi…

context catalog nimble (Data AI Engineer Architect)

Post-launch stabilization is complete for context schema/catalog contracts and Nimble enrichment flows across product surfaces: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

dashboard factory (Data Analysis Evangelist and AI Training)

Post-launch stabilization is complete for repeatable process for producing, reviewing, and publishing quickstarts/examples: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.

integrations platform (Head of Engineering)

Post-launch stabilization is complete for deployment, billing, 5T connectivity, and operational reliability/launch integration: recurring incidents are reduced, support burden is lower, and quality gates are enforced consistently before release. The team has a repeatable operating model for maintenance, regression prevention, and measured reliability improvements.