class CertifiedAIExpert:
    """
    🏆 IBM RAG & Agentic AI (8 courses)
    🎓 Harvard CS50x — Computer Science
    🐍 Harvard CS50P — Python Programming
    """

    def __init__(self):

        # ═══ IBM RAG & AGENTIC AI ═══
        self.rag = {
            "chunking":   ["semantic", "recursive", "agentic", "late chunking"],
            "embeddings": ["OpenAI ada-002", "Cohere", "BGE-M3", "Nomic"],
            "retrieval":  ["hybrid search", "HyDE", "re-ranking", "MMR", "RAPTOR"],
            "generation": ["RAG fusion", "CRAG", "self-RAG", "corrective RAG"]
        }

        self.agents = {
            "frameworks":    ["LangGraph", "CrewAI", "AutoGen/AG2", "BeeAI", "Semantic Kernel"],
            "patterns":      ["ReAct", "Plan-Execute", "Tree of Thoughts", "Reflexion"],
            "orchestration": ["multi-agent debate", "hierarchical agents", "swarm"],
            "protocols":     ["MCP (Model Context Protocol)", "function calling", "tool use"]
        }

        # ═══ HARVARD CS50x ═══
        self.cs_foundations = {
            "algorithms":      ["sorting", "searching", "graph traversal", "dynamic programming"],
            "data_structures": ["arrays", "linked lists", "trees", "hash tables", "tries"],
            "languages":       ["C", "Python", "SQL", "JavaScript", "HTML/CSS"],
            "concepts":        ["memory management", "pointers", "encryption", "TCP/IP"]
        }

        # ═══ HARVARD CS50P ═══
        self.python_mastery = {
            "core":      ["functions", "variables", "conditionals", "loops", "exceptions"],
            "advanced":  ["OOP", "inheritance", "decorators", "properties", "generators"],
            "testing":   ["unit testing", "pytest", "assert", "debugging"],
            "practical": ["regex", "file I/O", "CSV", "APIs", "third-party libraries"]
        }

        # ═══ 🧬 BIOINFORMATICS (SeqDNA 16S) ═══
        self.bioinformatics = {
            "sequencing":    ["16S rRNA metabarcoding", "FASTQ parsing", "Phred quality"],
            "assembly":      ["paired-end R1+R2", "consensus scoring", "overlap merge"],
            "identification":["NCBI BLAST+ (megablast)", "SILVA 138.2", "k-mer indexing"],
            "diversity":     ["Shannon", "Simpson", "Chao1", "Bray-Curtis", "Jaccard"],
            "statistics":    ["PERMANOVA", "ANOSIM", "PCoA ordination", "rarefaction"],
            "pipelines":     ["Biopython", "BIOM 1.0 export", "PDF reports", "Flask SaaS"]
        }

        # ═══ PRODUCTION ═══
        self.production = {
            "api":          ["FastAPI", "gRPC", "WebSockets", "streaming"],
            "infra":        ["Docker", "Kubernetes", "AWS", "GCP"],
            "monitoring":   ["LangSmith", "Langfuse", "Weights & Biases"],
            "optimization": ["caching", "batching", "quantization", "guardrails"]
        }

    def deliver(self) -> dict:
        return {
            "🎯 RAG Systems":    "Documents → Knowledge → Action",
            "🤖 AI Agents":      "Autonomous reasoning & execution",
            "🧬 Bioinformatics": "FASTQ → Species identification",
            "🎓 CS Foundations":  "Harvard-validated fundamentals",
            "🐍 Python":         "Deep mastery, tested & certified",
            "⚡ Production":     "Scalable, monitored, responsible"
        }

class DevPhilosophy:

    RULES = [
        "If you do it more than twice → automate it",
        "Clarity beats cleverness. Always.",
        "Ship fast, iterate faster, learn fastest",
        "Good code is code that can be deleted",
        "The best prompt is the one you never have to write twice"
    ]

    MOTTO = "Au nom du Prompt, du Modele et de la Sainte Iteration 🙏"

    def daily_standup(self) -> str:
        return """
        ☕ Coffee.init()
        💻 Code.write()
        🐛 Bugs.hunt()
        🚀 Features.ship()
        📚 Papers.read()
        🔄 Repeat()
        """