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9 min readProgrammatic SEO for SaaS: When It Works and When It Backfires
Generating pages at scale can build topical authority or trigger manual actions. Here is the line between useful and spam, with real examples from developer tool companies.
9 min readWe Replaced 6 SaaS Tools With One: What 6 Months of Real Data Shows
We replaced Slack, Google Meet, TimeCamp, and three other tools with Zlyqor. Here is what the real numbers look like after 6 months.
10 min readNeural Networks Explained: A Visual Guide for Software Developers
A neural network is layers of mathematical functions that transform inputs into outputs. Here is how they work, why depth matters, and what developers need to know.
7 min readOverfitting and Underfitting in ML: How to Diagnose and Fix Both
Overfitting memorizes training data and fails on new data. Underfitting is too simple to capture patterns. The train vs. validation loss curve tells you which you have. Learn to diagnose and fix both with dropout, regularization, early stopping, and more.
11 min readBuilding a RAG System From Scratch: A Complete Implementation Guide
RAG retrieves relevant documents at query time and adds them to the prompt. Five steps: chunk, embed, store, retrieve, evaluate. Here is the complete implementation.
9 min readWhen Not to Use Machine Learning: Simpler Solutions That Actually Work
Most ML projects fail not because ML is hard but because ML was the wrong tool. A decision tree, a regex, or a database query solves most 'AI' problems faster.
10 min readVector Databases Explained: What They Are and When to Use Them
A vector database stores embeddings and finds the most similar ones to a query. SQL cannot do this. ChromaDB, Pinecone, Weaviate, pgvector, and Qdrant compared.
10 min readAI Agents Explained: What They Are and How They Actually Work
An AI agent is an LLM that can take actions and loop until a goal is achieved. The four components, the ReAct loop, what production agents actually do, and honest limits.
11 min readHow to Build an AI Agent: A Practical Guide for Developers
Building an AI agent requires an LLM with tool calling and a loop that runs until completion. Five steps with working code, common failure patterns, and when to use a framework vs. build from scratch.
9 min readAI Agents vs AI Assistants: What's the Actual Difference?
Assistants respond to requests. Agents pursue goals autonomously. The technical differences, when you actually need an agent vs. an assistant, and an honest 2026 state-of-the-art.
10 min readMulti-Agent Systems: When You Need More Than One AI Agent
Multi-agent systems coordinate specialized agents to handle tasks too complex for one agent. Four coordination patterns, real use cases, frameworks, and the hard problems that come with distribution.
9 min readAI Gateways in 2026: Cloudflare vs Portkey vs LiteLLM vs Custom
An AI gateway sits between your application and LLM providers to handle routing, fallback, caching, rate limiting, and cost tracking. This guide compares Cloudflare AI Gateway, LiteLLM, Portkey, and building your own.