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miki-reynolds/README.md

class AboutMi:
    def __init__(self):
        self.name = "Mi | Miki"
        self.role = "SWE @ Adobe"
        self.team = "DX – AEM Assets (Digital Asset Management)"
        self.education = "MS in Computer Science ‘28 (AI/ML) @ Georgia Tech"
        self.fun_facts = """
        My name is pronounced as /me/, hence the `AboutMi`! 
        My nickname growing up is Miki - a combo of my first & middle name @^▽^@ 
        Hobbies are reading and building softwares that _help_ myself and my loved ones.
        I love nerdy jokes! Also, I'm trilingual!
        """
        self.tmi_facts = "It's weird - I get easily startled (-̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥᷄_-̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥̥᷅ ) Something is not 200..."

        
        self.focus_areas = [
            "Autonomous AI agents & ML/AI systems",
            "Distributed systems & event-driven architectures",
            "Scalable cloud infrastructure (AWS, Kafka, dBT, Snowflake, Iceberg)"
        ]

        # plz tell me u get my pun TT.TT
        self.ci_cd = {
            "distributed_system": [
                """Designed and implemented end-to-end scalable ingestion & AI-powered enrichment 
                pipelines on AWS using distributed semaphores & optimistic locking 
                to orchestrate multi-cloud asset flows for partners, e.g. Warner Bros, 
                enabling cross-cloud asset discovery without costly data duplication.""",
            
                """Redesigned AEM Assets event ingestion from at-least-once-guaranteed delivery HTTP to Kafka-based
                pipelines with exactly-once semantics, eliminating dedup logic & reliably processing billions+ of events a day"""
            ],
            
            "data_analytics": [
                """Built incremental, version-controlled data models in dbt & Snowflake 
                for attrition risk prediction, enabling data-driven decisions and proactive churn mitigation"""
            ],
            
            "pocs_mvps": [
                """Designed C2PA multi-agent provenance system POC & co-developed Brand-Aware-Tagging 
                POC that eventually got shipped to GA in 2025"""
            ]
        }
        
        self.core_tech_stack = [
            "Java", "Python", "Node.js", "Spring Boot",
            "AWS", "Kafka", "Snowflake", "dBT", "LangChain",
            "n8n", "Docker", "Kubernetes", "ArgoCD"
        ]

        self.pet_projects = {
            "miki-kb": {
                "about" : """AI-powered knowledge base syncing Notion to custom RAG API & NotebookLM
      via automated n8n workflows with LangChain & pluggable providers""",
                "status": "designing"
            },
            "something medical": {
                "about" : """Exploring on expanding my prev. healthcare project that I developed for my parents
                  & prev. patients using GCP...""",
                "status": "ideating"
            }
        }
    
    
    def introduce(self):
        print(f"\ʕ •ᴥ•ʔ/ Hi | こんにちは | Xin chào - I'm {self.name}!")
        print(f"Passionate about natural + technical languages, continuous learning & exploring emerging technologies!")

if __name__ == "__main__":
    mi = AboutMi()
    mi.introduce()

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