These engineering blogs have leveled up my tech skills more than any bootcamp, course, or conference.

Here are the ones worth bookmarking: Netflix Tech Blog
Check here: netflixtechblog.com

Make the most of your weekend.

Don't sleep on this.

Stanford's Autumn 2025 Transformers & LLMs course. 7 lectures. Free.

While others scroll, you could understand how Flash Attention achieves 3x speedup, how LoRA cuts fine-tuning costs by 90%, and how MoE makes models efficient.

➕ What's covered:

➡️ Lecture 1: Transformer Fundamentals
→ Tokenization and word representation
→ Self-attention mechanism explained
→ Complete transformer architecture
→ Detailed implementation example

➡️ Lecture 2: Advanced Transformer Techniques
→ Position embeddings (RoPE, ALiBi, T5 bias)
→ Layer normalization and sparse attention
→ BERT deep dive and finetuning
→ Extensions of BERT

➡️ Lecture 3: LLMs & Inference Optimization
→ Mixture of Experts (MoE) explained
→ Decoding strategies (greedy, beam search, sampling)
→ Prompting and in-context learning
→ Chain-of-thought reasoning
→ Inference optimizations (KV cache, PagedAttention)

➡️ Lecture 4: LLM Training & Fine-tuning
→ Pretraining and scaling laws (Chinchilla law)
→ Training optimizations (ZeRO, model parallelism)
→ Flash Attention for 3x speedup
→ Quantization and mixed precision
→ Parameter-efficient finetuning (LoRA, QLoRA)

➡️ Lecture 5: LLM Tuning
→ Preference tuning
→ RLHF overview
→ Reward modeling
→ RL approaches (PPO and variants)
→ DPO

➡️ Lecture 6: LLM Reasoning
→ Reasoning models
→ RL for reasoning
→ GRPO
→ Scaling

➡️ Lecture 7: Agentic LLMs
→ Retrieval-augmented generation
→ Advanced RAG techniques
→ Function calling
→ Agents
→ ReAct framework

From Stanford Online:
Rigorous instruction. Latest techniques. Free access.

Perfect for:
→ ML engineers building with LLMs
→ AI engineers understanding transformers
→ Researchers working on language models
→ Anyone learning beyond API calls

This weekend: learn the techniques that separate good engineers from great ones.

(I will put the playlist in the comments.)

♻️ Repost to save someone $$$ and a lot of confusion.
✔️ Follow @techNmak for more AI/ML insights. Lecture 1: Transformer

- Class logistics
- NLP overview
- Tokenization
- Word representation
- Recurrent neural networks
- Self-attention mechanism
- Transformer architecture

9 core patterns for building Fault-Tolerant Applications

Fall seven times, stand up eight.

Follow @techNmak for more :) [1.] Circuit Breaker

◾ Acts like an electrical circuit breaker.
◾ When a service experiences repeated failures, the circuit breaker 'trips' & stops sending requests to that service for a period of time.
◾ This allows the failing service to recover without being overwhelmed.

The main circuit breaker states -
◾ Closed: Requests are allowed to pass through.
◾ Open: Requests are immediately rejected with an error.

◾ effective for protecting against cascading failures & isolating problematic services.

Let's understand DOCKER

Follow the 🧵 What is a Container?

How Git Works (1/8) How Git Works (2/8)

Are you preparing for a system design interview? Then you should not miss this post.

Read more in the 🧵

Follow - @techNmak Are you preparing for a system design interview? 👇

Remember,

'Think Tradeoffs, Not Just Tech'

[1.] CAP Theorem
Consistency vs. Availability vs. Partition Tolerance
Choose two => Consistent data, high availability or tolerance to network failures.
(It's actually a choice between C & A)

[2.] Latency vs. Throughput
Fast response times vs. high data processing volume

[3.] ACID vs. BASE
Strict transaction guarantees vs. flexible consistency models

[4.] Monolithic vs. Microservices
Single, unified application vs. distributed, independent services

[5.] SQL vs. NoSQL
Structured data and complex queries vs. flexible schemas and scalability

10 Software Development Best Practices I Learned the Hard Way 😊.

[ If you like my efforts, please repost & follow @techNmak ]

Remember,

✔ Complex code = Complex bugs

✔ Maintainable > Clever 1./ 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐢𝐬𝐧'𝐭 𝐨𝐩𝐭𝐢𝐨𝐧𝐚𝐥
▪️"I'll add logs later" = famous last words
▪️Log EVERY exception with a unique ID
▪️Include request context in logs
▪️Structured logging > string concatenation
▪️Rotate your logs before they fill up your disk