Production-grade tutorials for the infrastructure technologies that power modern distributed systems. Each guide covers core concepts, architecture, setup, usage examples, best practices, and FAQs.
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The perception-reasoning-action loop, short-term and long-term memory, RAG with vector databases, planning patterns, tool calling, and multi-agent coordination.
The 5 essential Python frameworks every AI engineer must master: LangGraph, PydanticAI, LlamaIndex, DSPy, and vLLM / FastAPI.
AI Agent vs Agentic AI vs Multi-Agent Systems. Side-by-side comparison, L1–L5 autonomy spectrum, structural patterns, and decision guide.
Episodic, Semantic, and Procedural memory beyond naive RAG. Mem0 continuous extraction, Letta (MemGPT) virtual paging, and entity graphs.
Advanced & Agentic RAG. Hybrid search (BM25 + Dense), cross-encoder reranking, parent-child chunking, Self-RAG, and RAG Triad evaluation.
Stateful agent workflows with cyclic graphs. State reducers, Postgres checkpoints, time-travel debugging, and human-in-the-loop interrupts.
Orchestrate collaborative teams of AI agents. Agent roles, backstories, sequential and hierarchical delegation, and multi-tier memory.
Official framework for multi-agent delegation, handoffs, input/output guardrails, and OpenTelemetry tracing.
Build multi-step agents in JS/TS with Zod schemas, streamText, tool calling loops, and Next.js integration.
Fine-tune open-weights models (Llama 3.1, Qwen 2.5) for deterministic tool calling with Unsloth, LoRA, and QLoRA.
Cut agent token spend by 90% and TTFT by 80%. KV cache architecture across Gemini, Claude, and OpenAI.
Synthesize verified multi-turn agent trajectories, Evol-Instruct mutation operators, and sandbox rejection sampling.
Safely execute untrusted LLM-generated code. E2B Firecracker MicroVMs, WASM (Pyodide), and container runtimes.
Autonomous browser navigation with Playwright & Computer Use. Accessibility trees vs vision coordinates, and stealth architecture.
Ultra-low latency speech pipelines: WebRTC, LiveKit, OpenAI Realtime API, Gemini Multimodal Live, and barge-in interruptions.
Programmatic prompt compilation. Signatures, ChainOfThought, BootstrapFewShot, and MIPROv2 self-optimizing LLM pipelines.
Deterministic and LLM-as-a-Judge evaluations. DeepEval, Ragas, trajectory testing, hallucination scoring, and CI/CD pull request gating.
Mitigate indirect prompt injection, SSRF, and tool poisoning. Dual-LLM Privilege Isolation architecture and NeMo Guardrails colang.
Production Slack Bolt interactive approvals, LangGraph & Temporal pause-and-resume checkpointers, and HMAC cryptographic tokens.
Distributed event streaming platform. Topics, partitions, producers, consumers, KRaft mode, and real-time data pipelines.
Lightning-fast in-memory data structure server. Strings, Hashes, Lists, Sets, Sorted Sets, Pub/Sub, and caching patterns.
Stateful stream processing framework. DataStream API, event time, watermarks, checkpointing, and real-time analytics.
Vector databases for RAG pipelines and agent memory. Qdrant, Milvus, pgvector — embeddings, HNSW indexing, and metadata filtering.
Enterprise search engines for full-text & vector retrieval. Inverted index, k-NN vectors, BM25 hybrid search, RRF fusion, and cluster sizing.
Real-time analytical database for AI telemetry, token accounting, and agent execution traces. MergeTree engines and ZSTD compression.
Overcome vector search blind spots. Labeled Property Graphs (Neo4j, Memgraph), Cypher queries, and community detection for multi-hop agent reasoning.
Build fault-tolerant autonomous AI agents that survive server restarts. Deterministic workflow replay, event sourcing, and human-in-the-loop signals.
Masterless wide-column storage for billions of AI agent session messages. LSM-tree write path, tunable consistency, and ScyllaDB's C++ asynchronous engine.
Scale agent swarms and batch embedding pipelines across GPU clusters. Plasma zero-copy shared memory, stateful actors, and model serving.
Sub-10ms search-as-you-type engines without JVM memory overhead. Compare Meilisearch (Rust) and Typesense (C++) with out-of-the-box typo tolerance.
Deploy and manage containerized AI agents at scale. Pods, services, deployments, HPA autoscaling, Helm charts, and GPU node pools.
The most advanced open-source database. JSONB for agent state, CTEs, window functions, advanced indexing, partitioning, and replication.
Batteries-included Python framework. ORM, REST APIs with DRF, admin panel, authentication, middleware, and production deployment.
Distributed task queue for async AI agent workloads. Workers, brokers, retry strategies, periodic scheduling, and Flower monitoring.
Amazon Web Services for AI agents. Bedrock for LLMs, Lambda for serverless tools, DynamoDB for state, SQS for messaging, and ECS for containers.
Google Cloud for AI agents. Vertex AI & Gemini for LLMs, Cloud Run for containers, Firestore for state, Pub/Sub for messaging.
Microsoft Azure for AI agents. Azure OpenAI for GPT, Functions for serverless, Cosmos DB for state, Service Bus for messaging.
Design and build complex workflows. Compare LangGraph, AutoGen, and CrewAI for state, loops, tool execution, and human-in-the-loop.
Serverless NoSQL compared. Learn AWS DynamoDB, GCP Firestore, and Azure Cosmos DB for session memory, state sharding, and TTL.
Anthropic open standard. Connect LLMs to local data resources, databases, custom prompts, and executable tool servers.
Standard protocols for agent message passing, target handoffs, task negotiation, and execution synchronization.
Type-safe production agent framework by Pydantic. Structured outputs, type validation, dependency injection, and contract reliability.
Event-driven agentic RAG and query orchestration. Multi-source routing, reranking, and dynamic context retrieval workflows.
Trace, monitor, and evaluate production agents. OpenTelemetry, Arize Phoenix debugging, and DeepEval CI/CD test automation.
Unit testing and mock testing for Python AI agents. Test prompts, tool calls, agent runs, and validate output structures using pytest.
Enterprise CI/CD & Tier-1 SWE deployment stages: Unit/integration test gating, keyless AWS OIDC & GCP WIF, Beta, Gamma 1:1 parity, and Prod Canary progressive delivery.
Infrastructure as Code masterclass: CloudFormation YAML templates, intrinsic functions, change sets, drift detection, and AWS CDK v2 (TypeScript & Python) L1/L2/L3 constructs.
Hardware architecture masterclass: CPU vs GPU vs TPU vs custom ASICs, memory bandwidth wall, NVLink 5, vLLM serving, and training/inference pipeline orchestration.
Run Llama 3.3, DeepSeek-R1, and Qwen 2.5 on consumer laptops, Apple Silicon Macs, and budget RTX GPUs using Ollama, llama.cpp, and Open WebUI.
X.509 PKI, TLS 1.3 handshakes, Keystore vs Truststore across Java, Linux, Python, Go & Docker, zero-trust mTLS, and OpenSSL diagnostic recipes.
Self-hosted automation pipelines for Python AI agents. Jenkinsfiles, docker agent nodes, credential storage, and evaluation reporting.
Superfast Python package resolution and virtualenv creation using Astral's uv tool. Learn project locking, workspace dependencies, and offline caching.
