The AI Merge helps software engineers build depth in modern AI engineering: models, agents, RAG, vision systems, inference, evals, monitoring, infrastructure, deployment, and AI-assisted engineering workflows.
These repos focus on the engineering around AI systems — the parts that matter once a prototype has to work in a real product:
- How models behave inside applications
- How agents, tools, RAG, and multimodal systems are structured
- How inference, latency, deployment, and infrastructure affect product decisions
- How evals, monitoring, and reliability fit into the system
- How software engineers can use coding agents without losing ownership of the codebase
| Area | What it covers |
|---|---|
| AI foundations | Model behavior, tokens, embeddings, attention, fine-tuning, hallucinations — the fundamentals before building on top of models. |
| AI systems | RAG, agents, tools, vision, speech, multimodal applications, workflows, APIs, product architecture. |
| Deployment & infrastructure | Cloud, edge, containers, queues, runtimes, inference engines, GPUs, latency, memory, batching, quantization, cost tradeoffs. |
| Evaluation & monitoring | Test sets, regressions, traces, feedback loops, confidence gates, observability, failure analysis. |
| AI-assisted engineering | Specs, coding agents, review loops, TDD, test harnesses — workflows that keep engineers in control of the codebase. |
Built around complete AI systems, not isolated snippets.
| Project | What it is | Status |
|---|---|---|
| Kubrick | An open-source MCP multimodal AI agent course — built with Miguel Otero Pedrido. |  |
| Production Hub | Hands-on techniques for optimizing and serving AI models in production. |  |
| Computer Vision Hub | Building Computer Vision and Deep Learning solutions on video and image data. |  |
| The AI Atlas | A 220+ slide visual guide to the AI engineering field — diagrams, mental models, and system maps. | Join waitlist |
| MAVS | A full-stack wildlife monitoring AI system — MLOps, LLMOps, agents, multimodal workflows and edge AI inference. | Subscribe for updates |
| Where | What you get |
|---|---|
| Website | The main hub for products, courses, visual guides, and current work. |
| Newsletter | Field notes, technical breakdowns, and essays on AI engineering systems. |
| Repositories | Reference code, examples, and implementation patterns. |
