Blog

Building Agentic Web Scrapers That Scale to Millions of Records

How to architect a production-grade agentic scraping system using LangChain and Playwright - with fault tolerance, proxy rotation, and LLM-based semantic extraction that survives site redesigns.

10 min readJune 25, 2025

Building a Production RAG Pipeline with LangChain and FastAPI

Most RAG tutorials show you a hello-world demo. This post covers the real engineering - chunking strategy, retrieval tuning, hybrid search, and wrapping everything in a FastAPI service that handles 100+ concurrent users.

11 min readJune 29, 2026

LLMs

What I Learned Evaluating LLMs at Turing: Red-Teaming Frontier Models

I spent 2024 evaluating and red-teaming frontier LLMs at Turing.com. Here are the failure patterns I found most consistently, how to write RLHF feedback that actually influences training, and what surprised me about how capable these models really are.

7 min readJune 29, 2026

Computer Vision

Fine-Tuning YOLOv8 on a Custom Dataset: A Practical Guide From Annotation to Deployment

A practical walkthrough of fine-tuning YOLOv8 on a custom object detection dataset - annotation strategy, augmentation, hyperparameters, and the mistakes that cost the most training time.

9 min readJune 30, 2026

Building MCP Servers: How to Give Your AI Agents Real-World Tools

A practical guide to building Model Context Protocol (MCP) servers that connect LangChain agents to live data, APIs, and local tools - the architecture powering the next generation of agentic AI.

9 min readJuly 1, 2026

Scraping & Automation

Stealth Web Scraping in 2026: Bypassing Bot Detection with Playwright

A technical deep-dive into modern bot detection systems and how to build Playwright scrapers that reliably pass them - browser fingerprinting, TLS signatures, behavioral patterns, and proxy architecture.

9 min readJuly 1, 2026

Context Engineering: The Skill That's Replacing Prompt Engineering in 2026

Context engineering is how top AI teams manage what goes into an LLM's context window - memory, state, tool results, and retrieved knowledge. Here is how it works and why it matters more than prompt engineering.

9 min readJuly 1, 2026

Prompt Injection Attacks on AI Agents: How They Work and How to Stop Them

Prompt injection is the most underestimated security risk in production AI agents. Here is how attackers exploit it, why agents are uniquely vulnerable, and the defense strategies that actually work.

8 min readJuly 1, 2026

Multi-Agent Orchestration in 2026: How to Build AI Systems Where Agents Collaborate

Single agents hit ceilings fast. Multi-agent systems - where specialized agents divide work, check each other, and pass results - are how production AI teams are shipping complex capabilities in 2026.

9 min readJuly 2, 2026

Small Language Models Are Ready for Production: When SLMs Beat GPT-4 Class Models

Small language models - under 14B parameters - now match or beat frontier models on narrow tasks while running locally, costing orders of magnitude less, and responding 3-5x faster. Here is when to use them.

8 min readJuly 2, 2026

How AI Coding Agents Work: The Architecture Behind Cursor, Claude Code, and Devin

AI coding agents are not just autocomplete on steroids. They run tool loops, read codebases, write files, run tests, and iterate. Here is the actual architecture that makes them work.

9 min readJuly 7, 2026

Reasoning Models in Production: When to Use Thinking Mode vs Standard LLMs

Reasoning models like o3 and Claude Opus 4 think before they answer - running internal chain-of-thought before producing output. Here is when that actually helps and when it is overkill.

8 min readJuly 7, 2026

Model Context Protocol (MCP): The Standard That Makes AI Agents Actually Useful

A deep technical guide to Anthropic's Model Context Protocol — how it works, why it matters for AI agents, and how to build your own MCP server from scratch.

10 min readJuly 9, 2026

AI Engineering

Vibe Coding in 2026: What It Actually Is and How to Ship With It

Vibe coding is not hype. It is a real shift in how engineers build software. Here is an honest breakdown of what works, what does not, and how I use it to ship faster.

8 min readJuly 9, 2026

LangGraph Tutorial: Build Stateful AI Agents in Python (2026 Guide)

LangGraph is the production standard for AI agents in 2026. This guide covers state, nodes, edges, memory, and conditional branching with real working code.

10 min readJuly 9, 2026

Groq API Tutorial: Build Ultra-Fast LLM Apps in Python (2026 Guide)

Groq delivers LLM inference at 300-800 tokens per second - 10-50x faster than OpenAI. This guide covers setup, chat, streaming, Whisper STT, and when to use Groq in production.

9 min readJuly 9, 2026

Computer-Use AI Agents: Teaching Models to Operate a Screen Like a Human

Computer-use agents drive a mouse and keyboard by looking at screenshots instead of calling APIs. Here's how they work, where they beat traditional automation, and where they still fall apart.

9 min readJuly 10, 2026

GraphRAG: When Vector Search Isn't Enough for LLM Retrieval

Standard RAG retrieves isolated chunks and misses relationships between facts. GraphRAG builds a knowledge graph over your documents so the LLM can reason across connected entities. Here's when it's worth the added complexity.

9 min readJuly 13, 2026

AI Agent Evaluation: How to Benchmark Agents Before They Break in Production

Most teams ship AI agents with zero systematic evaluation and find out about failure modes from angry users. Here's the evaluation framework I use before any agent goes live - built on real LLM red-teaming experience at Turing.com.

10 min readJuly 15, 2026

What It Actually Costs to Build an AI Agent in 2026: A Real Pricing Breakdown

Businesses asking 'how much to build an AI agent' get wildly inconsistent answers because the question is underspecified. Here's an honest cost breakdown by project type, based on real client engagements - and what actually drives the price up or down.

8 min readJuly 16, 2026

AI Agent Memory: Building Agents That Actually Remember Across Sessions

Most AI agents forget everything the moment a session ends. Here's how production memory systems work - short-term vs long-term memory, vector-based recall, and the architecture that lets an agent get smarter about a specific user over time.

9 min readJuly 15, 2026

AI Agent Observability: How to Monitor Production Agents Before Your Users Complain

Traditional application monitoring doesn't tell you why an AI agent gave a wrong answer. Here's how to build tracing, evaluation, and alerting for agentic systems - so you catch failures before they reach a client's inbox.

8 min readJuly 16, 2026