Interactive builds · Handbooks · Field notes

Learn the systems
by breaking them.

Interactive system-design builds, LLM handbooks & agentic-engineering field notes — free and open source

Don't just read how large systems work — take one apart in the browser, watch it fall over, and build the intuition that sticks. Made by an AI engineer shipping in the open, with a little joy.

request-flow.svg
ClientGatewayapi-aapi-bCachePrimary DB
All systems nominalclient → gateway → api → cache → db

Tap a node to take it down — watch it reroute or fall over.

Daily practice

Come back tomorrow.

A fresh challenge and a lab every day — keep the streak alive.

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Run it yourself · no server

Everything here actually runs.

Real Python & TypeScript, executed in your browser — no install, no backend. Every algorithm and system-design page carries an editor like this: read it, edit it, run it, break it.

Try it live on the algorithm pages
01
Shelf 01 · Interactive builds

Builds you can break.

System designs, AI systems, algorithms, and labs — every one is a working build. Build Netflix step by step, make the calls, break the system, run the quiz.

★ Featured · Fully interactive

Design Netflix

Build a planet-scale video streaming service. See how the play path splits authorization from byte delivery, how origin storage and CDN edges serve immutable segments, how an adaptive-bitrate ladder adapts to any connection, how a parallel transcoding pipeline builds it, and how Open Connect, recommendations and QoE events fit together.

9 stepsAdvanced⚡ Chaos mode
Start building →
System DesignReal systems, step by step.All 50 designs →
02
Shelf 02 · The library

Longer form, for when you're ready.

Full-length handbooks and visual roadmaps — agentic AI, LLM evals, RAG, Angular, Python. Free to read, take what you need.

N°01
Handbook N° 01~45 min read

The Prompting Handbook.

A friendly, hands-on field guide for everyday humans — learn the CRISP framework, spot bad prompts, practice with real recipes, play a drag-and-drop game, and test yourself with a quiz. No code required.

Read handbook →
N°02
Handbook N° 02~60 min read

The Agentic AI Interview Handbook.

Twenty topics every senior AI engineer should be able to reason about live — from eval pipelines to reliability patterns for generative systems.

Read handbook →
N°03
Handbook N° 03~75 min read

The Senior AI Engineer Interview Handbook.

60 questions across architecture, production incidents, agentic systems, RAG, evals, cost, safety, and leadership — what staff-level AI interviewers actually probe for.

Read handbook →
N°04
Handbook N° 04~50 min read

50 Angular Interview Questions.

A visual handbook covering components, change detection, RxJS, signals, routing, forms, performance, and testing — what interviewers actually probe for in senior Angular roles.

Read handbook →
N°05
Handbook N° 05~50 min read

50 Python Interview Questions.

Fundamentals to advanced: data structures, OOP, iterators & generators, the GIL, asyncio, memory, testing, and the standard library — a visual walk through everything a Python interview touches.

Read handbook →
N°06
Handbook N° 06~55 min read

51 LLM Evals Interview Questions.

Golden sets, LLM-as-judge, regression testing, offline vs online evals, RAG evals, agent evals, red-teaming, and observability — demystified for interviews and production.

Read handbook →
RoadmapsTransit maps through AI.All roadmaps →
N°01
Roadmap N° 0118 stations · ~15h

Prompt Engineering Roadmap.

A visual transit-map roadmap from tokens and CRISP through chain-of-thought, RAG, and agent prompting to production monitoring. 18 stations across 3 tracks — interactive, free, your own pace.

Open roadmap →
N°02
Roadmap N° 0218 stations · ~13h

Data Structures & Algorithms Roadmap.

A visual transit-map roadmap from Big-O and arrays through hashing, sorting, and trees to graphs, Dijkstra, A*, and dynamic programming. 18 stations across 3 tracks — seven of them fully playable. Interactive, free, your own pace.

Open roadmap →
N°03
Roadmap N° 0318 stations · ~16h

AI Engineer Roadmap.

A visual transit-map roadmap to become an AI engineer in 2026. From how LLMs work through embeddings, RAG, agents, and fine-tuning to evals, guardrails, inference serving, and observability. 18 stations across 3 tracks — Foundations, Build, Production.

Open roadmap →
N°04
Roadmap N° 0418 stations · ~17h

MLOps Roadmap.

A visual transit-map roadmap for MLOps in 2026. From reproducibility, data versioning, and experiment tracking through training pipelines and model serving to monitoring, drift, governance, and LLMOps. 18 stations across 3 tracks — Foundations, Pipelines, Operations.

Open roadmap →
N°05
Roadmap N° 0518 stations · ~16h

System Design Roadmap.

A visual transit-map roadmap for system design in 2026. From APIs, databases, caching, and load balancing through sharding, queues, consistent hashing, and consensus to end-to-end designs of Twitter, YouTube, and Uber. 18 stations across 3 tracks — Fundamentals, Building Blocks, Real Systems.

Open roadmap →
N°06
Roadmap N° 0618 stations · ~17h

Generative AI Roadmap.

A visual transit-map roadmap for generative AI in 2026. From how text and images are generated through diffusion, multimodal, sampling, and fine-tuning to evaluating, securing, and shipping generative products. 18 stations across 3 tracks — Foundations, Techniques, Production.

Open roadmap →
N°07
Roadmap N° 0718 stations · ~16h

Backend Engineer Roadmap.

A visual transit-map roadmap to become a backend engineer in 2026. From HTTP APIs, SQL, NoSQL, caching, and auth through API design, message queues, testing, and observability to Kubernetes, CI/CD, sharding, and reliability. 18 stations across 3 tracks — Foundations, Core Backend, Production.

Open roadmap →
N°08
Roadmap N° 0818 stations · ~17h

Frontend Engineer Roadmap.

A visual transit-map roadmap to become a frontend engineer in 2026. From HTML, CSS, layout, and JavaScript through TypeScript, React, state, and data fetching to bundlers, rendering, Core Web Vitals, and deployment. 18 stations across 3 tracks — Foundations, Core Frontend, Production.

Open roadmap →
N°09
Roadmap N° 0918 stations · ~18h

DevOps Roadmap.

A visual transit-map roadmap to become a DevOps engineer in 2026. From Linux, networking, Git, and Docker through CI/CD, Terraform, Kubernetes, and secrets to observability, SRE, GitOps, and cost. 18 stations across 3 tracks — Foundations, Core DevOps, Production.

Open roadmap →
N°10
Roadmap N° 1018 stations · ~18h

Data Engineer Roadmap.

A visual transit-map roadmap to become a data engineer in 2026. From SQL, Python, and data modeling through Spark, Kafka, Airflow, and dbt to data quality, governance, partitioning, and CDC. 18 stations across 3 tracks — Foundations, Core Data, Production.

Open roadmap →
N°11
Roadmap N° 1118 stations · ~19h

Machine Learning Roadmap.

A visual transit-map roadmap to become a machine learning engineer in 2026. From math and feature engineering through regression, trees, neural networks, CNNs, and transformers to experiment tracking, MLOps, drift, and responsible AI. 18 stations across 3 tracks — Foundations, Core ML, Production.

Open roadmap →
N°12
Roadmap N° 1218 stations · ~18h

Cloud / AWS Roadmap.

A visual transit-map roadmap to learn cloud engineering on AWS in 2026. From EC2, S3, VPC, and IAM through serverless, containers, IaC, and messaging to Well-Architected, multi-region, cost optimization, and DevOps. 18 stations across 3 tracks — Foundations, Core AWS, Production.

Open roadmap →
N°13
Roadmap N° 1318 stations · ~16h

AI Harness Roadmap.

A visual transit-map roadmap to build an AI harness — the runtime around a model that turns it into an agent. From the messages API, tokens, and structured output through tool calling, the agent loop, context management, memory, and sandboxing to permissions, subagents, evals, observability, and cost control. 18 stations across 3 tracks — Model I/O, the Agent Loop, Production.

Open roadmap →
The Workshop

Built by an AI engineer who would rather ship things than talk about shipping things.

Vibe Engines is a one-person workshop publishing open-source tools, technical writing, and long-form handbooks at the intersection of LLMs, agentic systems, and developer tools. Everything here is made for the people doing the actual building — founders shipping MVPs on weekends, technical solopreneurs stitching together stacks, engineers trying to level up on the parts of AI that matter.

Nothing here is theoretical. Every repository ships something that works. Every handbook is written from the workshop floor, not the lecture hall. Some of the tools will get used. Some won't. That's the point of running a workshop in public — you get to find out.

Read more about the workshop