Skip to main content
9 specialized agents covering the full AI/ML lifecycle from data engineering to production deployment.

​
Agents

AI Engineer

End-to-end AI systems from model selection to production deployment
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: ai, machine-learning, model-training, deployment, mlops
npx github:dmicheneau/opencode-template-agent install ai-engineer

Data Scientist

Data analysis, predictive modeling, and statistical insights
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: data-science, statistics, machine-learning, analytics, modeling
npx github:dmicheneau/opencode-template-agent install data-scientist

ML Engineer

Production ML pipelines, model serving, and automated retraining
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: machine-learning, mlops, model-serving, pipelines, training
npx github:dmicheneau/opencode-template-agent install ml-engineer

MLOps Engineer

Model deployment, serving infrastructure, monitoring, and ML lifecycle
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: mlops, model-serving, monitoring, deployment, ml-lifecycle
npx github:dmicheneau/opencode-template-agent install mlops-engineer

LLM Architect

LLM system design, fine-tuning, RAG, and inference optimization
  • Mode: subagent
  • Quality: 4.88/5 (Excellent)
  • Tags: llm, rag, fine-tuning, inference, nlp, ai
npx github:dmicheneau/opencode-template-agent install llm-architect

Prompt Engineer

Prompt analysis, optimization, and improvement for LLM interactions
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: prompts, llm, optimization, ai, prompt-engineering
npx github:dmicheneau/opencode-template-agent install prompt-engineer

Data Engineer

ETL pipelines, data warehousing, Spark, Airflow, and data infrastructure
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: data-engineering, etl, spark, airflow, data-warehouse, pipelines
npx github:dmicheneau/opencode-template-agent install data-engineer

Data Analyst

SQL analytics, BI dashboards, reporting, and data storytelling
  • Mode: subagent
  • Quality: 4.75/5 (Excellent)
  • Tags: data-analysis, sql, bi, dashboards, reporting, visualization
npx github:dmicheneau/opencode-template-agent install data-analyst

Search Specialist

Advanced web research, search techniques, and multi-source synthesis
  • Mode: subagent
  • Quality: 4.62/5 (Excellent)
  • Tags: search, research, web, information-retrieval, synthesis
npx github:dmicheneau/opencode-template-agent install search-specialist

​
Usage Examples

@ai/llm-architect Design a RAG system for customer support

​
Quality Stats

  • Average score: 4.75/5
  • All agents: Excellent rating
  • Total tokens: ~11,000 (avg ~1,220 per agent)
  • Coverage: Full ML lifecycle + data stack

​
Common Workflows

  1. Data Scientist — Exploratory analysis and model training
  2. ML Engineer — Production pipeline implementation
  3. MLOps Engineer — Deployment and monitoring setup
Or use the ml-to-production pack:
npx github:dmicheneau/opencode-template-agent install --pack ml-to-production
  1. Data Engineer — Build ETL pipelines
  2. Data Analyst — Create dashboards and reports
  3. Data Scientist — Predictive modeling
Or use the data-stack pack:
npx github:dmicheneau/opencode-template-agent install --pack data-stack
  1. LLM Architect — Design RAG or fine-tuning strategy
  2. Prompt Engineer — Optimize prompts for quality
  3. AI Engineer — End-to-end implementation

​
When to Use

  • Building AI features from scratch
  • Integrating multiple ML components
  • Selecting models and frameworks
  • End-to-end AI system design
  • Exploratory data analysis
  • Building predictive models
  • Statistical hypothesis testing
  • Feature engineering
  • Designing RAG systems
  • Fine-tuning LLMs
  • Optimizing inference latency
  • Prompt engineering at scale
  • Deploying models to production
  • Setting up model monitoring
  • Implementing A/B testing
  • Managing model lifecycle

Build docs developers (and LLMs) love

Get started for freeTalk to us