Operational Symptoms
- Agent drift, inconsistent workflows
- Outdated SOPs and unclear rules
- Contradictory decisions across teams
Unified Context Layer · Segment Validation
SaaS UK/EU: Context Engineering Profile (Strawman)
We're validating the first target segment for the Unified Context Layer (UCL). Does this describe your team?
1. Who This Profile Represents
- SaaS companies in the UK or Europe
- Ideal size: 30–80 employees (range 15–150)
- Engineering team: 5–25
- ARR: £1M–£20M
- Hybrid/remote; high iteration pressure
- Product complexity increasing faster than documentation
- Consultants working with SaaS teams (see Partners page)
2. Common Patterns & Symptoms
Product & Engineering Symptoms
- Coding agents generate incorrect business logic
- Unclear or conflicting requirements
- Context loss slows iteration
Leadership Symptoms
- Too many AI pilots; too few reliable outcomes
- Hard to see ROI or ensure governance
3. Principal AI Use Cases
- Coding Agents as Senior Engineers — reliable, context-aligned code.
- Automation Recommendation — what to automate, in what order, safely.
- Decision Intelligence — AI recommendations that respect constraints.
4. Additional High-Value Use Cases
Fast Data • Personalisation at Scale • Reliable Support Agents • Workflow Routing • Impact Simulation
5. Why This Segment Is Our Current Focus
Strong engineering culture, high iteration pressure, operational complexity, readiness for agent adoption, and clear value from reliable AI systems.
6. What We Want to Validate
- Does this profile describe your company?
- Are these the right primary use cases?
- Would a Unified Context Layer create real ROI?
Talk to us about your SaaS context challenges
We'll walk through your symptoms, AI use cases, and whether the UCL could materially improve reliability, iteration speed, and alignment.