Tech Stack
Tools grouped by architectural role. Each row says where I used them for clients and where I am still studying them.
Production AI, agents and applied MLOps
Agent workflows need explicit permissions, observability and evaluation. Project status lives in Research Labs, and current adoption conditions in the Tech Radar.
| Role | Tools | Where it shows up |
|---|---|---|
| Agentic frameworks & runtimes | LangGraph, Pydantic AI, Google ADK (2.0 workflow model), OpenAI Agents SDK, Claude Agent SDK, LlamaIndex, FastAPI | Client work: multi-agent loan evaluation with LangGraph on GCP (2026). Research: stateful supervision in Durable Agent Workflows |
| Agent protocols & model access | Model Context Protocol (MCP, 2026-07-28 specification), A2A v1.0, Vertex AI Agent Engine, Amazon Bedrock AgentCore, Gemini, Anthropic Claude, Hugging Face, LiteLLM | Client work: Gemini agents on Cloud Run (2024–2025) and ML deployments from Vertex AI Workbench (2025). Research: remote tools, cross-runtime delegation and cost-aware routing in Durable Agent Workflows and Inference Serving |
| Inference serving & routing | SGLang, vLLM, TensorRT-LLM, NVIDIA Dynamo (disaggregated prefill/decode over NIXL), LMCache, llama.cpp, Ollama | Client work: local LLMs behind a pipeline-diagnosis agent (2026). Research: local-first serving, EAGLE-3 speculative decoding and tiered KV cache in Inference Serving |
| Open-weight models & guardrails | gpt-oss, Qwen, Gemma, DeepSeek, Llama, Hermes; Llama Guard, gpt-oss-safeguard, Qwen3Guard | Client work: Hermes-3 in that diagnosis agent (2026). Research: utility-tier routing in Inference Serving; policy-following safety classification in Durable Agent Workflows |
| Vector, graph & memory storage | Qdrant, pgvector, LanceDB (Lance), Milvus, LadybugDB, Graphiti, Mem0 | Research: semantic caching, hybrid Graph RAG retrieval and agent memory in Inference Serving, Open Table Interoperability and Retrieval & Memory |
| Evaluation & benchmarking | DeepEval, Promptfoo, Braintrust, Arize Phoenix, LangSmith, RAGAS; τ²-bench, Terminal-Bench, and SWE-bench Verified as external baselines | Research: regression testing and multi-judge pipelines in AI Evaluation Harness. Public: Eval Statistics sizes the comparisons |
| LLM observability & FinOps | OpenTelemetry (GenAI semantic conventions), Langfuse, Helicone, Arize Phoenix | Client work: token cost telemetry for the loan-evaluation agents (2026). Research: token, latency and cost telemetry in Inference Serving |
Data engineering and lakehouses
Local-first for development: prototype on embedded engines, then verify SQL semantics, catalog support and data contracts on each target cloud engine. The compatibility criteria are in the Tech Radar.
| Role | Tools | Where it shows up |
|---|---|---|
| Processing engines | Polars, DuckDB, Apache Arrow, Apache DataFusion, Apache Spark (PySpark), Databricks, Pandas | Client work: PySpark on Cloudera and Scala on Dataproc (2019–2021); ML deployments across Spark and Databricks (2025). Research: vectorized execution in Open Table Interoperability; local-first verdict in Tech Radar |
| Low-latency analytics | ClickHouse 26.8 LTS | Research: event-query candidate in Streaming Freshness; validate ingestion, duplicates and cost before adoption |
| Streaming & CDC | Apache Kafka 4.3 (KRaft) / Redpanda, Apache Flink 2, Apache Fluss, Debezium 3, Google Pub/Sub, Dataflow | Client work: Pub/Sub and Dataflow streaming ingestion (2022–2023, 2024–2025). Research: streaming ingestion in Open Table Interoperability |
| Orchestration | Dagster, Apache Airflow 3.3; Cloud Composer / MWAA (version-specific support), Prefect 3 | Client work: Airflow and Cloud Composer pipelines (2019–2021, 2022–2023). Research: the orchestrator comparison |
| Storage, table formats & catalogs | Apache Iceberg v3, DuckLake, Delta Lake, Lance, Apache Parquet, Apache Polaris, Unity Catalog, Lakekeeper, Cloud Storage, Amazon S3 | Client work: BigQuery Silver/Gold layers and automated Parquet backups (2023–2024); S3-to-BigQuery ELT (2022–2023). Research: open-table-format integration in Open Table Interoperability |
| Transformation & modeling | dbt Core 1.12, dbt v2.0 (under evaluation), SQLMesh, SQL, Kimball dimensional modeling, Data Vault 2.0, data contracts (ODCS) | Client work: 1,100+ dbt models (2023–2024); Data Vault 2.0 domain models (2019–2021). Research: reproducible dbt diagnosis and patch trials in Log-Driven Code Repair |
Cloud and platform infrastructure
Infrastructure described as code, with policy checks before changes. Cross-cloud portability requires provider-specific designs and validation.
| Role | Tools | Where it shows up |
|---|---|---|
| Public & private cloud | Google Cloud Platform (GCP), Amazon Web Services (AWS); OpenShift / OpenStack as private references | Client work: GCP in every role since 2019 and an AWS lakehouse (About). References: Production Blueprints |
| Infrastructure as Code | Terraform / OpenTofu (modular landing zones), Terragrunt, Crossplane, OPA Rego, Conftest, Kyverno | Client work: multi-project GCP landing zones in Terraform (2024–2025). Research: policy-as-code spike in Tech Radar; foundations in Production Blueprints |
| Containers & orchestration | Docker, Kubernetes (GKE / EKS; DRA, Gateway API Inference Extension), Google Cloud Run (GPU), Amazon ECS / Fargate | Client work: a Kubernetes data platform on GKE (2023–2024); agents on Cloud Run (2024–2025). Research: containerized runtimes across Research Labs |
| GitOps & secrets management | ArgoCD, HashiCorp Vault / OpenBao | Research: GitOps reconciliation and zero-trust credentials in Reproducible Platforms |
| Platform observability | Prometheus, Grafana, Mimir, Loki, Tempo, Pyroscope, Grafana Alloy | Research: centralized SRE telemetry in Cost per Successful Task |
| CI/CD & local toolchain | GitHub Actions, just, uv, pre-commit | Client work: zero-trust CI/CD pipelines (2025). Public: the toolchain this site runs on |
Languages, databases and standards
| Role | Tools | Where it shows up |
|---|---|---|
| Programming languages | Python (free-threading only where profiled), SQL, Rust, Scala, Bash | Client work: Python and SQL in every role; Scala on Dataproc and Hadoop (2019–2021). Research: Rust/Python router experiments in Inference Serving |
| Databases | PostgreSQL, AlloyDB, DuckDB, ClickHouse, MySQL, Redis, BigQuery, Snowflake, Redshift | Client work: BigQuery in every GCP role; Redis session state (2024–2025). Research: target compatibility in Tech Radar |
| Engineering standards | Data contracts (ODCS), schema evolution, idempotency, OpenTelemetry semantic conventions, pre-commit quality gates, Conventional Commits, SemVer | Applied across every project, including this repository |
| Tool UX/UI | Zensical, semantic HTML, token-based CSS, native JavaScript, Playwright, axe-core | This site as a progressive-disclosure and accessibility case; UX/UI principles |