Technical Support · Operations · Automation
Building systems, automations and knowledge platforms for the next generation of technical operations.
I combine technical support expertise, operational thinking, automation, and AI-powered workflows to solve complex problems and improve how teams work.
An evolution shaped by curiosity — each stage building the next.
Mapping how services, data and people connect — the foundation for everything that follows.
Fast, empathetic resolution of complex, mission-critical issues across services and databases.
SLA ownership, incident management, RCA and operational KPIs — reliability as a craft.
Scripts, SQL, dashboards and workflow design that eliminate repetitive toil.
n8n, AI agents and prompt engineering — orchestrating intelligent operations.
I work at the intersection of technical support, operations and automation — combining disciplined incident management and SQL diagnostics with active exploration of AI-powered workflows, n8n and modern knowledge systems.
End-to-end ownership of incidents — triage, mitigation and clear communication across engineering and customers in mission-critical systems.
Disciplined RCA with SQL, PostgreSQL, log analysis and structured hypotheses — turning noisy symptoms into durable fixes.
SLA ownership, KPI design, runbooks and knowledge management — building systems that stay reliable as teams scale.
Removing manual toil with Python scripts, n8n automations and AI agents — practical, measurable improvements to how teams work.
I specialize in technical support, incident management, root cause analysis and operational reliability — and I'm channeling that operational rigor into Python automation, n8n workflows and AI-powered systems that compound team productivity.
Each skill is a working capability — click any node to see how it's used in real operations and automation work.
Daily driver for production diagnostics, analytics and reporting. Complex joins, window functions, query plans.
Active research and hands-on practice — AI automation, agentic workflows and the next generation of operational tooling.
Designing production-ready AI flows with structured outputs, evaluation and guardrails.
Visual orchestration of triggers, integrations, LLM calls and conditional logic.
Patterns for classification, extraction and reliable tool-use across models.
Searchable, structured knowledge — runbooks, SOPs and a personal second brain.
From manual SOPs to deterministic automations with clear handoffs and metrics.
Multi-step agents with tools and memory — focused on safe, measurable outcomes.
A mix of shipped tools, active experiments and AI-powered workflows in progress.
Self-serve demo: paste your FAQ and get a working AI support assistant in 10 seconds. Answers only from your data, escalates payment disputes to humans. Self-hosted API with hard cost caps (Docker, nginx, DeepSeek).
A research-focused agent that searches, summarizes and cites sources with structured outputs.
Pipeline that turns runbooks, tickets and docs into a searchable, versioned knowledge graph.
A sandbox of small AI workflows for triage, classification and reply drafting.
Reusable n8n flows for ops: alert routing, incident summaries, customer follow-ups.
A personal Telegram bot with tool access — notes, reminders and AI-powered queries.
Dashboards translating support and ops data into clear, actionable signals.
A track record of keeping mission-critical systems healthy, improving processes, and lifting the teams around me.
Owned operational reliability for production systems with strict SLAs, supporting global users across time zones with high availability and recovery targets.
Drove RCA processes from triage to permanent fix — translating complex production issues into clear post-mortems and preventive actions.
Built scripts, queries, dashboards and workflow automations that eliminated repetitive operational work and accelerated resolution time.
Diagnosed live issues across services, databases, APIs and logs — using SQL, Kibana, Grafana, Elasticsearch and Postman to isolate root causes fast.
Partnered with engineering, QA, product and customer-facing teams — turning ambiguous reports into reproducible bugs and actionable specs.
Built onboarding flows, SOPs, runbooks and internal documentation that scaled team capacity and reduced single points of failure.
A deliberate growth path: combining proven support and operations expertise with hands-on AI, automation, and agentic systems.
Shipping faster with Lovable, Cursor and AI coding agents.
Building real apps through natural-language collaboration with AI.
Orchestrating APIs, data and AI across systems without glue code.
Designing autonomous agents that handle support, ops and research tasks.
Crafting reliable, structured prompts and evaluations for production use.
Combining LLMs, no-code, vector DBs and APIs into production solutions.
"The best support engineers of the next decade will be part operator, part automator, part AI orchestrator."
A curated, growing resource hub — guides, runbooks, learning notes and experiments. CMS-ready for future content.
EXPLAIN ANALYZE, indexes, statistics and the questions to ask before adding hardware.
From webhook to LLM call to Slack notification — a hands-on starter for support automation.
A reusable runbook for the first 15 minutes of any production incident.
Query patterns, filters and visualizations that surface root causes faster.
Patterns for structured outputs, classification and safe automation in customer-facing flows.
Information architecture and writing patterns proven in support teams.
Notes from building production apps through natural language and AI agents.
Small wins compound — a starter pack of scripts that save hours every week.
LinkedIn recommendations and testimonials from teammates and customers.
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Testimonials about collaboration, technical depth, ownership and impact will appear here.
Customer-facing feedback highlighting empathy, communication and resolution quality.