Context plane
Approved behavioural, commercial, customer and repo sources become one persistent, source-backed understanding of the product and its users.
The product
One operating system for the UX function.
Sightspool joins the work that normally fragments across analytics, research repositories, design reviews, meetings and somebody’s memory. It gives the team a continuous way to understand, act and learn.
The architecture of the function
Five layers. One continuous learning loop.
“Decision OS” is the governance spine inside Sightspool. The broader product also understands context, validates signals, routes specialist work and accumulates what the team learns.
Signal layer
Sightspool turns beliefs into questions and validates the event, threshold, sample and evidence required before treating a number as a read.
Specialist studio
Focused agents across research, interaction and service design investigate from the same context instead of producing disconnected AI opinions.
Action governance
Recommendations keep their evidence, uncertainty, downside and client-owned decision attached. Consequential actions remain human-gated.
Learning memory
Product changes re-arm the right questions. Outcomes, including null and negative results, improve the next piece of work.
Live now
This is working product, not a proposed org chart.
Sightspool already runs as a multi-tenant application with connected evidence, focused agents, shared memory, governed interventions and coding-agent surfaces.
Connected evidence
PostHog, Stripe, GitHub/repo context, first-party Signals and approved customer material enter through source-specific tools with provenance.
Truthful measurement
Unknown events, measured zero and insufficient samples remain distinct. An unavailable signal cannot silently become a product verdict.
Persistent studio
Vera, Ella, Theo and Zach share sources, memories, tasks, personas and journeys across runs rather than beginning from a blank prompt.
Governed action
Findings require proof. Interventions require approval. Verdict history is append-only, and an agent can never declare an assumption verified.
Product change awareness
Repository changes can re-arm the assumptions that depend on them, so yesterday’s answer does not survive a materially different product.
Outcome continuity
The action, intended result and later observation remain one record, with digests and coding-agent write-back keeping the learning in circulation.
Clear product boundaries
Continuous UX capacity without pretending to be everything.
Sightspool operates customer-facing product uncertainty. It does not quietly expand into roadmap authority, production delivery or formal compliance work.
Sightspool owns
- Source-backed customer and experience context
- UX question routing and specialist investigation
- Evidence quality, uncertainty and downside
- Recommendation, action and outcome continuity
Your product team owns
- Goals, roadmap and priorities
- Requirements and delivery coordination
- The final product decision
- Implementation in the customer product
Human assurance owns
- Consequential or ambiguous recommendations
- Sensitive research and participant safety
- Unresolved specialist tensions
- Formal review where professional judgement is required
Start with a real question
Bring one question. See the whole operating system move.
A working demo starts with a real customer or experience question and shows which sources Sightspool would use, how the studio would route it and where human assurance would enter.