Eddie
AI-first full stack / DevOps
+ systems architect

Skills & Expertise

AI / ML Engineering

Practical intelligence systems: autonomous agents, copilots, tool-calling workflows, RAG pipelines, vector search, structured reasoning, and multimodal understanding.
Model selection across GPT-5/4o/mini, o3, Claude 3.5, and Llama 3.x—balancing capability, cost, latency, and control.
Retrieval architecture: embeddings, chunking strategies, re-ranking, normalization, and safety layers.
Evaluation: prompt iterations, offline evals, hallucination audits, and latency/cost optimization.
Vision and speech: image parsing, STT/TTS pipelines, and multimodal agent loops when they add real leverage.
Tooling: REST-first, lightweight orchestration, and minimal dependencies to preserve ownership.

Autonomous Agent Systems

Design of recursive, self-improving agent architectures (CORE ASi OS, TelophonAi, CareerAider).
Action models with memory routing, task planning, self-reflection loops, and system-level observability.
Safe autonomy patterns: guardrails, sandboxed execution, live monitoring, and systematic rollback strategies.
Integration with real environments (APIs, webhooks, schedulers, trading engines, hardware, and cloud functions).

Web Engineering

Next.js 15 / React 18 / TypeScript with clean, accessible interfaces and fast Edge delivery.
Streaming UI, keyboard-first flows, gesture-safe audio, and realtime interactions.
MDX publishing pipelines with SEO-ready routing, metadata, and long-form content support.
Performance work: image optimization, code-splitting, caching, and low-TTFB practices.
Tailwind + component libraries for production polish and maintainability.

Backend & APIs

Node/TypeScript services with crisp HTTP contracts, authentication layers, and rate limits.
Webhooks, background workers, ingestion pipelines, ETL tasks, and event-driven automation.
Observability through structured logs, metrics, and simple dashboards that surface issues early.

Data & Databases

Relational discipline with PostgreSQL + Prisma for clarity, safety, and long-term velocity.
Vector search with pgvector; Redis for hot paths and session/state caching.
Schema design, migrations, indexing, and query tuning for predictable performance.

Cloud & DevOps

Deployments across Vercel, AWS Lambda/S3, Azure Functions, and containerized environments.
Docker when needed; Kubernetes only when scale and reliability justify it.
GitHub Actions pipelines for build, lint, type-checking, and Playwright smoke tests.
Cost-aware engineering: efficient token use, caching, cold-start mitigation.

Audio & Music Systems

AI-assisted creation pipelines, music generation workflows, and Web Audio integrations.
Studio skills across recording, mixing, mastering, and automated media processing with ffmpeg.
UX patterns for persistent playback, safe autoplay, and multimedia-rich interfaces.

Blockchain (Practical Use)

Smart contracts and crypto payments where they enable automation, trust, or verifiability.
Focused on utility, not hype.

IT & Security Foundations

Systems administration, backup strategies, access control, and incident response basics.
Secrets management, least-privilege defaults, auditing, and threat-aware design.

Project Leadership

Outcome-focused execution with clear specs, tight iteration cycles, and measurable delivery.
Operational rigor: SOPs, handoffs, and documentation that future teams can inherit.
Strategic alignment: translating business goals into roadmaps and shipped value.

Working Style & Principles

Keep systems simple, stable, and easy to own.
Favor transparency in code, prompts, and processes.
Engineer for the future without wasting money in the present.
Prioritize user impact—AI is a multiplier, not a magic trick.