Abstract Algorithms
Understand how systems work.
One deep article at a time.
Abstract Algorithms is a calm engineering publication for distributed systems, AI infrastructure, data structures, and production tradeoffs.
01
Mental model
02
Production
03
Tradeoffs
Start with who you want to become. Then move through concepts, systems, pressure, and readiness.
Latest deep dives
The article is the primary surface: long-form explanations, diagrams when they matter, and enough production reasoning to make the idea usable.

LLM Skills vs Tools: The Missing Layer in Agent Design
TLDR: A tool is a single callable capability (search, SQL, calculator). A skill is a reusable mini-workflow that coordinates multiple tool calls with policy, guardrails, retries, and output structure.
16 min read

Little's Law: The Secret Formula for System Performance
TLDR: Little's Law (\(L = \lambda W\)) connects three metrics every system designer measures: \(L\) = concurrent requests in flight, \(\lambda\) = throughput (RPS), \(W\) = average response time. If l
9 min read

Fine-Tuning LLMs: The Complete Engineer's Guide to SFT, LoRA, and RLHF
TLDR: A pretrained LLM is a generalist. Fine-tuning makes it a specialist. Supervised Fine-Tuning (SFT) teaches it your domain's language through labeled examples. LoRA does the same with 99% fewer tr
30 min read

How AI Coding Agents Work: Models, Context, Sessions, and Memory
TLDR: An AI coding agent is an LLM stapled to a tool registry, wrapped in an orchestration loop that painstakingly rebuilds state on every single API call โ because the model itself is completely stat
34 min read
Explore related systems
A lightweight way to move from one system idea to the next while staying close to the articles.
Concept collections
Follow the durable themes.
Collections gather related articles around systems behavior, not course modules or visible learning machinery.
Open ExploreA quiet mentor when you need one
Ask for a simpler explanation, a comparison, or the next concept. The content stays in front.
Continue learning
A simple next step from what you have been reading. No complex roadmap required.
Balancer
Practice the hard parts
Small simulations and prompts for reasoning about failure, latency, consistency, and tradeoffs.
Practice
Focused moments, not a separate product.
Use simulations when a visual change makes the underlying system easier to reason about.
Open PracticeKafka Rebalance Simulation
Observe partition movement, consumer lag, and assignment strategy in real time.
Quorum Consistency Simulator
Tune N/R/W values and visualize stale-read risk vs availability.
RAG Pipeline Visualizer
Step through retrieval, reranking, context assembly, and generation.

