I build the product
behind the product.
B2B SaaS companies do not just ship a product. They ship a support, knowledge, AI, and escalation system around it. I design that system so technical teams can increase pre-escalation resolution, reduce avoidable escalation, and scale customer experience without creating operational drift.
I'm a CX Engineer and Systems Architect. I design post-sales infrastructure for technical B2B SaaS teams that need stronger support automation, knowledge systems, AI-assisted workflows, and customer signal loops.
Your customers experience your systems,
not your org chart.
To your company, support, success, product, community, documentation, AI, and operations may be separate functions.
To your customers, they are one experience.
When those systems are disconnected, customers repeat context, get different answers in different places, wait for escalation, and lose trust in AI because the underlying content and data are unreliable.
That is not a support problem.
It is an architecture problem.
When CX is not engineered,
Shadow CX takes over.
Shadow CX is what happens when customer experience depends on hidden spreadsheets, tribal knowledge, Slack favors, one-off automations, outdated help content, disconnected CRM fields, and escalation paths only three people understand.
It works — until it does not.
Then support gets noisy, AI gets unreliable, customers lose trust, and teams spend more time routing problems than solving them.
CX Engineering replaces Shadow CX with observable, intentional, governed systems that improve pre-escalation resolution and reduce avoidable escalation.
Better self-service moves the system
closer to intent.
Self-service is not about making customers do more work.
Better self-service moves the system closer to the customer’s intent.
That means the right answer, next step, Academy path, escalation route, or feedback loop appears before the customer has to translate their need into your internal process.
See how the method works →The product behind the product.
I design and ship the systems that improve pre-escalation resolution and reduce avoidable escalation, including:
Support workflows
That reduce avoidable escalation.
Knowledge systems
That stay aligned with product reality.
Community experiences
That capture signal, not just engagement.
AI support patterns
Grounded in trusted content and clean data.
CRM and customer data structures
That make context usable.
Escalation paths
That preserve trust under pressure.
Feedback loops
That turn customer friction into product and operational insight.
Governance models
That keep systems from drifting after launch.
Product engineering for the full
customer experience.
Product engineers build the core product experience.
CX Engineers build the systems that help customers adopt it, learn it, trust it, request changes to it, recover when they get stuck, and keep moving.
The best CX work often shapes in-product journeys too, because it is informed by the places customers struggle after launch: support cases, search failures, community questions, Academy engagement, documentation gaps, escalation patterns, feature requests, and customer feedback.
Sometimes the work is connecting what already exists. Often, it means building the missing CX features companies should have had all along: feature request systems, closed-loop feedback, Academy/LMS pathways, self-service journeys, support intake, escalation visibility, AI answer flows, and customer signal loops.
| Product Engineer | CX Engineer |
|---|---|
| Builds the core product customers use | Builds the adoption, resolution, learning, and feedback layer customers rely on to succeed |
| Designs in-product workflows and features | Designs customer journeys across product, support, docs, community, Academy, AI, and escalation |
| Ships product features | Ships CX features like feature request systems, closed-loop feedback, Academy/LMS paths, self-service flows, support intake, escalation visibility, AI answer patterns, and knowledge capture |
| Owns user friction in the product | Owns customer friction wherever it appears across product, support, success, education, community, content, AI, or operations |
| Uses product analytics and user feedback | Uses product analytics plus support data, search behavior, community signals, Academy engagement, CRM data, case trends, feedback, and escalation patterns |
| Improves activation, adoption, retention, and usage | Improves adoption, resolution, trust, self-service, feedback quality, escalation quality, and post-sales scalability |
| Turns user feedback into product improvements | Builds closed-loop systems that turn customer signals into product, content, education, support, and operational improvements |
| Connects engineering, design, and product | Connects product, design, engineering, support, success, education, community, content, RevOps, data, and AI |
Selected systems outcomes.
These outcomes came from treating support, knowledge, community, and AI as one operating system instead of separate surfaces.
226%
growth in problems resolved before reaching support by moving help upstream through predictive signals, inline guidance, and community-based routing
$192K
in annual operational efficiency gains, validated by Finance, through digital support improvements that reduced avoidable support demand
4.96% → 8.8%
growth in community-assisted resolution as a share of incoming support volume after rebuilding a transactional portal into a customer community
78%
growth in quarterly community logins after improving routing, content visibility, and customer-facing support paths
10%
ticket volume reduction and 25% fewer repeat questions after unifying Zendesk, Discord, and Discourse into an intent-based help architecture
Post-sales systems
designed, built, and shipped.
A focused diagnostic if you need to see where your customer experience infrastructure breaks. A fractional engagement if you need someone to own the systems that improve pre-escalation resolution and reduce avoidable escalation.
CX Architecture Audit
A focused 1-hour diagnostic of your post-sales experience infrastructure. I map how customers currently move through support, knowledge, community, AI, escalation, and internal handoffs — then identify the places where systems, ownership, and data drift apart.
The audit is designed to answer one question: where is the system too far from the customer’s intent to resolve before escalation?
I look for the places where customers are forced to translate their own need into your internal categories, search across disconnected surfaces, repeat context, escalate without clarity, or submit feedback into a loop they cannot see.
Deliverables include:
- Customer intent path map.
- Self-service and escalation breakpoints.
- Academy/LMS and learning-path gaps.
- Feedback-loop and feature-request gaps.
- Recommendations for moving answers, actions, escalation, and learning closer to customer intent.
Fully credited toward a Fractional engagement if we continue.
Book a CX Architecture Audit →Fractional CX Engineer & Systems Architect
For teams that need senior systems leadership across support automation, knowledge, AI, and customer signal loops without hiring a full-time function. I help design, build, and operationalize the systems behind scalable customer experience: support workflows, knowledge architecture, community strategy, AI readiness, data hygiene, and cross-functional governance.
Built for companies that need someone who can move from strategy to system design to implementation before they scope a full-time role.
Explore Fractional CX Engineering →3-month minimum. Rolling monthly after. 30-day cancellation. Limited to 2 concurrent partners at a time.
The bits and the Bee.
NahamSec and I at a Bugcrowd live hacking event in Las Vegas
I'm a technical operator, systems architect, and builder focused on the infrastructure behind customer experience.
My work sits between support, success, product, community, knowledge, data, and AI. I help B2B SaaS teams turn fragmented post-sales operations into systems customers and internal teams can trust.
I believe most customer struggle is not user error. It is system failure. When customers cannot find the right answer, when support cannot see the right context, when AI gives inconsistent responses, when escalation depends on tribal knowledge, or when feedback never reaches the product team, the issue is rarely one person or one tool. It is the architecture.
Frequently asked questions
Is this support operations, customer experience, or business systems? +
Yes. I work across support operations, knowledge architecture, community, self-service, AI, and business systems because customers experience those as one path, not separate departments.
Do you only advise, or do you also own execution? +
I own execution. The advisory work is useful because it identifies where the system breaks, but the larger value is building the roadmap, governance, workflows, routing, and measurement model needed to fix it.
Is the audit useful if we don't continue? +
Yes. That's why it's a flat $1,500 and only credits forward if you choose to continue. The deliverable stands on its own.
How is this different from a UX audit? +
A UX audit usually focuses on interface and usability. My work looks at the full post-sales system: support flows, knowledge architecture, community, routing, self-service, AI surfaces, and the operational seams between them. The issue is often not one screen. It's that the experience strategy and the systems behind it are owned separately, so the customer journey breaks across the boundary.
Can I just hire you full-time? +
Possibly. The fractional model exists for companies that need this function before they're ready to scope or hire it as a full-time role.
Build the product behind your product
Tell me where
the experience breaks.
If your post-sales experience depends on hidden workarounds, disconnected tools, or heroic internal effort, it is time to engineer the system behind pre-escalation resolution.