ADEXTECHHUB
GitHub ↗RESUME
// engineering-manifesto

Intelligent systems.

I design software around data flows, robust backends, and modular AI integrations. Clean interfaces, sound infrastructure.

// engineering

How I think about engineering.

Organized by domain — not a skills list with fake percentages.

AI ENGINEERING

Building production AI systems, not wrappers.

RAGLLMsAI AgentsEmbeddingsVector SearchContext EngineeringRetrieval EvaluationLangChainLangGraphLlamaIndexCrewAIOpenAIOllamaHugging Face
BACKEND

APIs and data systems that scale.

FastAPINode.jsREST APIsPostgreSQLAuthenticationMulti-tenancySupabaseServerlessPyTorchscikit-learnPandas
FULL STACK

End-to-end product engineering.

TypeScriptReactNext.jsTailwind CSSSvelteServer ComponentsServer ActionsSaaS Architecture
INFRASTRUCTURE

Shipping and maintaining systems.

GitGitHubVercelSupabaseCloud DeploymentsCI/CD
// ai-lab

AI Engineering Lab.

Ongoing experiments. Each may become a system, article, or product.

ADEXTECHHUB :: AI ENGINEERING LABSTATUS: ACTIVE
01
Building RAG Pipelines
Architecting retrieval-augmented generation systems with evaluation and grounding.
RAGLangChainVector Search
ACTIVE
02
Agentic Workflows
Multi-step agent architectures with LangGraph and tool-calling patterns.
LangGraphAgentsTool Calling
ACTIVE
03
Retrieval Evaluation
Measuring and improving retrieval quality: precision, recall, NDCG in production.
EvaluationMetricsQuality
ONGOING
04
Context Engineering
Structuring context windows for long-context LLMs and multi-turn conversations.
ContextPromptingLLMs
ONGOING
05
Tool Calling Architectures
Designing reliable function-calling schemas for agentic systems.
Tool CallingJSON SchemaAgents
RESEARCH
06
Local LLM Experiments
Running Ollama-based local models for private, offline AI workloads.
OllamaLocal LLMsPrivacy
RESEARCH
$lab --list --status=active