In-depth insights into software architecture, best practices, and lessons learned from real production systems.
A practical analysis of when microservices make sense and when they do not. Based on real successes and failures in distributed systems architecture.
The discipline that replaced prompt engineering: assembling state, tools, retrieval, history, and constraints into the model's window at the right moment. From two years shipping AI features in production.
Practical production tuning for .NET — cutting allocations, using Span<T>, avoiding async pitfalls, and profiling what actually matters under load.
Tenancy isolation models, data partitioning, and authentication for multi-tenant platforms — drawn from building and operating ToyCRM in production.
These videos are carefully curated external resources selected by Profectus Lab to help engineers understand modern AI and system design principles.
~1:56:00 A rare hands-on explanation of GPT internals, connecting theory with real code. Ideal for engineers who want to truly understand how modern LLMs are built.
~1:00:00 Karpathy's full hour walkthrough of how LLMs actually work — inference, training, fine-tuning, and the emerging LLM-OS picture. The clearest single-shot mental model on the internet for engineers new to the field.
~27:00 3Blue1Brown's signature visual treatment of the transformer architecture. The single best 30-minute primer for engineers who want the intuition before the math.
~16:00 StatQuest's hallmark step-by-step teaching style applied to the attention mechanism. Removes the magic and leaves you with a working intuition for self-attention.
~14:00 3Blue1Brown's visual proof of how networks actually learn. The clearest mental model of gradient descent and the chain rule available in 15 minutes.
~18:00 Breaks the "neural networks are black boxes" myth. Step-by-step walk through the math with the simplest possible example — the right starting point if neural nets feel impenetrable.
~50:00 Mosh Hamedani's hands-on intro that walks from zero through a real ML pipeline in Python. The fastest end-to-end ML primer for engineers who already know Python.
~15:00 Michael Phi pairs every transformer concept with a clean animation. The right second video to watch after 3Blue1Brown — same intuition, different angle.
~6:00:00 The MCP track keynote with the Anthropic team. If you want to understand why MCP became the industry-standard protocol for connecting LLMs to tools in 2025, this is the single best primary source.
~2:00:00 A hands-on workshop from Anthropic on building production agents with the Claude Agent SDK — tool use, sub-agents, hooks, MCP servers, and the patterns that scale beyond the demo.
~8:00:00 The keynote stream from the largest technical AI conference of 2024. A snapshot of the state of AI engineering — what shipped, what worked, what didn't — straight from the teams building it.