Contributor to Google ADK · Pydantic AI · LiteLLM · llama.cpp · ag-ui
7+ years in applied AI · author of a package in the official ADK integrations catalog
I build production AI systems that reason, plan, and execute autonomously: multi-agent orchestration, agent skills and harnesses for coding agents, enterprise RAG pipelines, LoRA fine-tuning at scale, and multi-adapter inference serving.
| Focus area | Working with |
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| Multi-agent AI | Google ADK A2A Protocol MCP Agent Orchestration |
| Agent skills & harnesses | SKILL.md Claude Code Operator Skills Evidence Gates |
| Knowledge graphs & RAG | Neo4j GraphRAG Hybrid Search Reranking Guardrails |
| LLM fine-tuning & serving | LoRA / QLoRA Unsloth vLLM Multi-Adapter Inference |
| LLM observability | Langfuse MLflow OpenSearch Domain Evaluation |
| Model building | Transformers from scratch DeepSpeed SFT / DPO / RLHF |
- Building an enterprise decision-intelligence platform: multi-agent orchestration on Google ADK, NL2SQL over governed data, AG-UI streaming to a React frontend
- Production hardening: durable sessions, tenant isolation, model benchmarking, incident postmortems
| Project | What it is |
|---|---|
| rhytm | Multi-agent framework for proprietary data analysis with business intelligence |
| SLM-From-Scratch | Ongoing: alignment utilities and GGUF / ONNX export paths for small language models |
Where agentic AI is heading in 2026, and where I'm already hands-on:
| Frontier | My work there |
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Agent skills: portable SKILL.md capabilities for coding agents |
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| Harness engineering: the control plane around coding agents |
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Agent protocols: MCP A2A AG-UI AGENTS.md |
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| Context engineering: sessions, memory and state over prompts |
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| Agent reliability: evals, failure taxonomies, observability |
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- EquityOracle: self-improving equity recommender with multi-horizon predictions and paper trading
- fincept-operator-skill: agent skill operating a live trading terminal, paper-only with human-approved live actions
| Years | Era | Proof |
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| 2019–2021 | Data science and classical ML | Lead-Scoring · Telecom-Churn · Product-Recommender |
| 2021–2023 | NLP and deep learning | Deep-Learning-Projects · Spark-GPU-Sentiment |
| 2023–2025 | GenAI foundations: RAG, fine-tuning, model building | Enterprise-RAG · LLM-Finetuning-Toolkit · SLM-From-Scratch |
| 2025–now | Agentic AI: orchestration, skills, harnesses | Multi-Agent-Framework · adk-database-memory · prepostmortem-skills |
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Google ADK Python |
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ADK Community |
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ag-ui Protocol |
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Pydantic AI |
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llama.cpp |
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LiteLLM |
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adk-database-memory |
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(pre·post)mortem |
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Full tech breakdown
LLM providers OpenAI · Anthropic · Google Gemini · Llama · Mistral
Agent frameworks Google ADK · A2A Protocol · MCP · LangGraph · CrewAI
RAG stack LlamaIndex · LangChain · Neo4j · OpenSearch
Vector DBs Pinecone · Weaviate · Milvus · Qdrant · ChromaDB
Observability Langfuse · MLflow · Weights & Biases · OpenTelemetry
Inference vLLM · Multi-LoRA serving · TensorRT-LLM · ONNX Runtime
Fine-tuning LoRA · QLoRA · DoRA · Unsloth · Axolotl · DeepSpeed · RLHF / DPO
Model building PyTorch Transformers · BPE tokenizers · GGUF / ONNX export
Frontend React · Vite · Next.js · TypeScript · TailwindCSS
Backend FastAPI · Python · Node.js · GraphQL
Cloud AWS (Bedrock, SageMaker) · GCP (Vertex AI) · Azure (OpenAI, AI Search)
Data & distributed PySpark · Spark NLP · Databricks · Streamlit · scikit-learn · XGBoost
Infrastructure Docker · Kubernetes · Terraform · GitHub Actions



