Signal 1
Think in systems
Find the process, constraints, owners, and failure points before choosing tools.
www.jansandiego.com
Jan Eiriel San Diego
Intelligent Systems BuilderAI Automation SpecialistGoHighLevel CRM Builder
Engineering mindset | Business systems | GoHighLevel CRM | Workflow automation | Remote operations support
I engineer practical systems that help people and organizations solve messy operational problems with clearer processes, smarter handoffs, useful automation, and AI where it genuinely helps.
Proof, not promisesReviewable workflow artifactsHuman-gated automationSystems teams can maintain
Licensed Mechanical Engineer applying systems thinking to business workflows, AI automation, CRM operations, and technical support for remote teams.
Jan's System Method
Diagnose. Map. Build. Stabilize.
Systems
Engineering mindset
Operations
Clearer handoffs
AI
Workflow intelligence
1
Diagnose
ProcessFind the real bottleneck, owner, data source, and failure point
2
Map
DataTranslate messy work into triggers, records, stages, and decisions
3
Build
WorkflowConnect CRM, AI, apps, webhooks, notifications, and handoffs
4
Stabilize
HandoffTest edge cases, document behavior, and prepare the handoff
Signal 2
Build for use
Create workflows, interfaces, and handoffs that people can understand after delivery.
Signal 3
Prove, do not promise
Show workflow screens, certificates, documentation, and deploy-ready work that can be reviewed.
Signal 4
Improve over time
Leave room for reporting, QA, recovery paths, and the next version of the system.
Capabilities
I start with the problem behind the workflow
Slow follow-ups, messy records, repeated admin work, and disconnected tools are usually symptoms. The real work is finding the operating pattern underneath, then making it easier to run.
System design
Design customer systems that scale
Turn scattered inquiries, forms, records, and follow-ups into a customer operating system people can actually maintain.
Clear ownership
Cleaner records
Repeatable follow-up
Workflow logic
Free teams from repetitive work
Move recurring admin, routing, reminders, status updates, and task handoffs into reliable workflow logic.
Less manual checking
Cleaner handoffs
Reliable timing
AI judgment
Use AI where judgment is useful
Apply AI for drafting, intake review, summarization, qualification, and structured outputs where rules alone are too rigid.
Drafted responses
Qualified context
Structured decisions
Integration
Connect disconnected technology
Bridge CRMs, inboxes, sheets, calendars, forms, APIs, and webhooks into one connected operating flow.
API workflows
Webhook routing
Cleaner data movement
Operations
Make systems easier to trust
Support the practical work that makes automation usable: QA, cleanup, documentation, testing, and handoff.
QA checks
Clear documentation
Operational handoff
Web systems
Turn ideas into usable interfaces
Use AI-assisted development to translate rough ideas into clean websites, landing pages, and deploy-ready interfaces.
Clear messaging
Responsive UI
Vercel-ready delivery
Website Builds
The same systems thinking applies to websites.
A useful website is not just a nice page. It is a clear explanation of who you are, what problem you solve, what proof you have, and what someone should do next.
Clarify the message
Turn raw notes into audience, positioning, page sections, copy hierarchy, and calls to action.
GrokOpenRouterLLM Tools
Build the interface
Use AI-assisted coding to create responsive pages with reusable components and clean frontend structure.
Next.jsTypeScriptTailwind CSS
Prepare for launch
Check the build, polish details, connect domains, and deploy through Vercel with a clear handoff path.
VercelGitHubLovable
Trust Layer
Why I notice structure inside messy work
Engineering training taught me to look for constraints, failure points, load paths, and repeatable systems. I bring that same habit into digital operations.
Engineering lens
Systems before tools
I start with the business process, failure points, owners, and handoffs before choosing GoHighLevel, n8n, Zapier, Make.com, or AI.
Reliable workflow
Automation with accountability
Good workflows are traceable. They should show what happened, who owns the next step, and where the process can recover.
Usable delivery
Practical over impressive
The best automation is the one the team can understand, maintain, and trust after the first exciting demo is over.
Licensed Mechanical EngineerSystems-first automation builderAI automation training credentialsRemote-team friendly documentation
Decision Fit
Useful when the issue is not another app, but the way work moves.
I am most useful where the process already exists, but the ownership, timing, data, and handoffs are not yet clear enough for the team to trust.
Map the process before choosing the tool
Keep workflows readable after handoff
Separate deterministic logic from AI judgment
Design for ownership, recovery, and documentation
Teams with too many manual handoffs
Good fit when work is moving through inboxes, spreadsheets, forms, and memory instead of a visible operating flow.
Founders who need operational clarity
Good fit when the business is growing but the process is still too dependent on manual checking and undocumented steps.
Remote teams that need cleaner systems
Good fit when people need shared context, follow-up visibility, and workflows that can be reviewed without guesswork.
Project
A customer workflow translated into an operating flow
This build shows the method in practice: take scattered intake, follow-ups, stage movement, and onboarding, then give each step a clearer role in the system.
Starting Point
The work was happening, but the path was not clear enough.
Small teams often rely on memory, inbox checks, and manual status updates. That can make it harder to see which leads need a quote, follow-up, onboarding, or reactivation.
System design
The build gives each part of the customer journey a role: capture the lead, record the context, move the opportunity, trigger the next step, and hand off after the outcome.
1
Intake
2
Qualification
3
Follow-up
4
Onboarding
Case study map
From loose steps to a visible system
GHL workflow example
Problem
Lead activity, quote status, follow-ups, and onboarding steps were easy to lose when the process depended on memory and manual checking.
Approach
Map the customer journey first, then convert the steps into forms, pipeline stages, tags, wait conditions, and task handoffs.
Architecture
Lead capture feeds the CRM record, decisions segment the contact, stage changes trigger follow-up logic, and won/lost outcomes start the next path.
Technology
GoHighLevel forms, opportunities, tags, workflows, email follow-ups, smart lists, and onboarding tasks.
Business impact
The team gets a clearer operating path for response, follow-up, sales tracking, and post-sale handoff.
Future improvements
Add reporting, source attribution, response-time tracking, and AI-assisted message drafting once the core workflow is stable.
Design goals
Earlier visibility on new inquiries
Clearer follow-up ownership
Cleaner pipeline movement
Less manual status checking
A more consistent onboarding path
GHL Build Scope
Customer operating flow
This project shows the architecture behind a customer workflow: intake creates the record, stages describe progress, tags add context, and automation keeps the next action visible.
- 01Intake
System stage
Form
Capture clean intake
- 02Record
System stage
Opportunity
Create the sales record
- 03Stage
System stage
Pipeline
Move work by stage
- 04Action
System stage
Workflow
Trigger the next action
Architecture Notes
The useful part is not the canvas. It is the operating logic.
The build translates a business process into triggers, conditions, ownership, follow-up timing, and handoffs. That is the difference between a tool setup and a system people can run.
Lead capture forms and funnel entry points
Opportunity pipeline setup for quote and sales stages
Lead qualification and interest-based tagging
Automated quote follow-ups and lost-lead reactivation
Won-customer onboarding with email and task handoffs
Workflow proof
GoHighLevel
CRM workflow system
GoHighLevel workflows shown as reviewable system evidence: intake, segmentation, quote follow-up, onboarding, and reactivation.
Good fit for customer journeys that need clearer stages, cleaner records, and follow-up logic the team can review.
Lead intakePipeline movementFollow-up paths
GoHighLevel, project 1 of 5, New Lead Intake
01 / 05
1 of 5
Proof Library
Workflow proof, organized for quick evaluation
The platforms change, but the pattern stays the same: understand the process, design the flow, connect the tools, and leave behind work that can be reviewed, maintained, and improved.
Proof, not promises
Each build is a different surface of the same skill.
The screenshots are not decoration. They are artifacts of how a system was reasoned through: what starts the work, where data moves, what decisions happen, and how the next action becomes visible.
Portfolio screenshots are selected or recreated to be safe to review while still showing the operating logic behind the work.
CRM cleanupWorkflow automationAI agentsLead follow-upTechnical VA systems
3
Platforms
14
Workflow builds
5
Credentials
Reviewable artifact
AI Call Appointment Setter
Reduces manual scheduling work by letting an AI voice agent handle appointment requests while n8n manages availability, records, confirmations, and error paths.
Workflow artifacts
Grouped so the work is easy to evaluate
Each platform is grouped by the operating problem it helps solve, so the work can be reviewed without opening a gallery or hunting through hidden popups.
Selected platform
n8n
AI agents and workflow logic
Deeper workflow architecture for AI agents, scheduled operations, RAG, voice flows, and APIs.
Good fit for deeper logic, AI agents, API workflows, scheduling, and reusable systems with recovery paths.
AI agentsAPI workflowsRecovery logic
n8n, project 1 of 9, ASMR Video Generator
01 / 09
1 of 9
Credential Layer
Training that supports the practice
Certificates are not the main story. They simply show that the tools behind the systems were studied deliberately, not used casually.
Verified credential
Certificate 1 of 5
Zapier Automation Training
Training credential for building app-to-app automations and Zapier workflows.
Why this matters
This credential supports the systems work shown in the portfolio: practical automation, clearer workflows, tool fluency, and better handoff quality.
Verify credentialPauses while reviewing
Process
The method behind the work
I try to make every workflow answer the same questions: what starts it, what data matters, what decision happens, what action follows, and how the team recovers when something changes.
4-stage design plan
A simple path from unclear work to a system people can use, review, and improve.
01
Diagnose
Find the real friction
02
Design
Shape the operating path
03
Build
Connect the moving parts
04
Stabilize
Prepare it for handoff
Diagnose the real problem
Identify the trigger, owner, data source, follow-up timing, failure points, and business outcome before touching the tools.
Output
Problem map
Design the operating flow
Turn the process into a readable structure: stages, records, decisions, data handoffs, timing rules, and recovery paths.
Output
Workflow blueprint
Build the system
Connect the CRM, apps, AI prompts, webhooks, branches, notifications, and interface pieces needed to make the flow work.
Output
Working system
Stabilize the system
Check edge cases, data formatting, duplicate prevention, notifications, and documentation so the workflow can be reused.
Output
Team-ready system
Tools
Tools come after the system is clear
I do not lead with software. I choose tools based on the workflow, data, handoff, maintenance, and budget reality of the problem.
GoHighLeveln8nZapierMake.comOpenAIChatGPTGrokOpenRouterLLM ToolsCodexClaude CodeAnthropicLovableNext.jsTypeScriptTailwind CSSVercelGoogle SheetsAirtableSlackAPIsWebhooksDockerGitHub
Closing thought
The real work is making the system easier to understand.
I moved from mechanical engineering into automation because the same pattern kept appearing: capable people were doing important work inside fragile manual processes. My role is to find the friction, simplify the operating path, and build systems real teams can trust.
Find friction
Clarify flow
Build trust
Contact
If you are trying to make work clearer, I can help.
Send a short note about the process, workflow, or operation you want to improve. I will help clarify the next practical step.
Email for inquiries
hello@jansandiego.comBest for job opportunities, project scopes, collaboration details, and formal remote work inquiries.
Quick message
Best for quick introductions, follow-ups, and direct conversation about automation support.
Best fit: business process improvement, AI automation, workflow systems, CRM operations, and technical support for remote teams.