My Engineering Learning Journal

A production-minded ASP.NET Core capstone combining RAG, controlled tools, durable state, human approval, security, observability and agent evaluation.

A practical guide to LangGraph state, nodes, edges, checkpoints, interrupts, replay, human review and safe recovery across agent workflows.

A critical guide to current LangChain agents, tools, structured output, middleware, memory, retrieval and integration behind ASP.NET Core boundaries.

Design bounded agent lifecycles with budgets, approvals, retries, durable execution, tracing, recovery, loop detection and operational controls.

A production-minded guide to A2A 1.0 Agent Cards, messages, tasks, artifacts, delegation, identity, reliability and cross-agent trust boundaries.

Understand current MCP hosts, clients, servers, tools, resources, prompts, versioning, authorisation and safe capability discovery for .NET systems.

Separate model context, conversation, working state, checkpoints, long-term memory and authoritative business data for reliable agent execution.

Compare single-agent, router, planner-executor, supervisor-worker, critic, human review and multi-agent designs using one enterprise scenario.

Build narrow agent tools with strict schemas, resource authorisation, approval, idempotency, timeouts, safe observations and production tracing.

Distinguish chatbots, RAG, structured model calls, workflows and genuine agent loops while designing bounded autonomy around ASP.NET Core.

A practical guide to query routing, decomposition, parent retrieval, contextual compression, HyDE, Corrective RAG, Self-RAG, GraphRAG and bounded agentic retrieval.

A practical guide to permission-aware hybrid retrieval, query rewriting, reranking, thresholds, authority, citations and evaluation with ASP.NET Core and Azure AI Search.

A practical guide to fixed, recursive, semantic, parent-child and document-aware RAG chunking with ASP.NET Core, Azure AI Search and measurable retrieval evaluation.

A production-minded guide to turning PDFs, SQL data and business documents into clean, permission-aware searchable knowledge with ASP.NET Core, Azure AI Search and Document Intelligence.

A practical guide to embeddings, vector similarity, HNSW, Top-K, thresholds, metadata security filters, semantic ranking and hybrid search with ASP.NET Core and Azure AI Search.

A practical mentoring guide to assembling trusted AI context in ASP.NET Core through authorised state, RAG, memory, provenance, token budgets, least-privilege tools and context observability.

A production-focused mentoring guide to architecting secure, resilient and observable LLM features in ASP.NET Core, using BuildEstate Pro as a realistic enterprise case study.

A practical SQL Server 2025 mentoring guide to memory-optimized tables, MVCC, durability, hash and nonclustered indexes, native compilation, ASP.NET Core integration and safe adoption.

A practical mentoring guide to how SQL Server uses statistics, histograms, density and cardinality estimates to predict row counts and choose an execution plan.

A practical mentoring guide to how SQL Server parses, binds, simplifies and transforms T-SQL, estimates candidate plans, chooses an execution strategy and exposes evidence for query troubleshooting.

Part 1 of my practical SQL mentoring series for junior developers: relational thinking, data modelling, normalization, integrity, schema evolution, SELECT, filtering, joins and set-based reasoning.

Part 2 of my practical SQL mentoring series: expressions, aggregation, CTEs, window functions, data modification, transactions, concurrency, idempotency and reliable application data.

Part 3 of my practical SQL mentoring series: index architecture, query optimisation, execution plans, statistics, plan caching, Query Store, data quality, warehousing and modern data systems.

My book-backed study notes and practical exercises for understanding Azure Bicep, from first resources through modules, managed identity, what-if, CI/CD and production governance.

My practical, code-heavy revision handbook for React 19, TypeScript, Server Components, Actions, state, hooks, React Router 7, forms, Auth.js, Node.js, PostgreSQL, Drizzle ORM, testing, CI/CD, performance and production deployment.

A slow, beginner-friendly and code-heavy guide to JavaScript's core mechanisms: values, types, variables, functions, scope, hoisting, closure, this, prototypes, classes, coercion, the event loop, Promises, iterators, modules, performance and framework connections.

A beginner-friendly guide to compile-time reasoning, inference, unions, narrowing, generics, structural typing, type operators, modules and honest runtime boundaries.

Faz’s conversational browser notes: 62 learner questions answered through navigation, parsing, rendering, events, storage, browser security, service workers, memory and DevTools.

Faz’s conversational security notes: 85 junior-developer questions answered patiently through threat modelling, access control, browser attacks, identity, supply-chain integrity and incident response.

Faz’s conversational CSS and accessibility notes: 97 questions about cascade, resilient layout, semantics, keyboard focus, forms, ARIA, design systems and inclusive testing.

Faz’s conversational testing notes: 48 learner questions about trustworthy unit, integration, component, API, database and end-to-end evidence, flakiness and CI.

My structured Azure learning journal, connecting tenants, subscriptions and Bicep with App Service, Functions, containers, data, messaging, identity, monitoring and secure delivery.

Faz Ahmed’s 5,000-word learning notebook on moving from language models and RAG to controlled AI agents—covering tools, memory, orchestration, planning, MCP, A2A, multi-agent patterns, evaluation, safety and a practical first build.

Faz Ahmed’s personal 5,000-word learning notebook on generative AI at AWS—from foundation models, prompting and RAG to agents, evaluation, production architecture, security, responsible AI and a practical first project.

Faz Ahmed’s 5,000-word developer notebook from learning machine learning on AWS—connecting Amazon Bedrock, SageMaker AI, RAG, agents, data engineering, training, deployment, evaluation, security and LLMOps into one understandable journey.

My first structured exploration of bringing AI into secure .NET and Azure systems with Microsoft Foundry, models, agents, RAG, controlled tools and evaluation.