A deep dive into the Cline compromise: how an attacker used a GitHub dangling commit, a typosquatted account, and prompt injection against an AI triage agent to achieve remote code execution on Cline's GitHub Actions CI/CD runners.
A deep dive into why traditional SAST tools missed the CVSS 10.0 n8n vulnerability and how CodeQL's taint tracking with barriers can detect this class of missing validation bugs.
How a missing path validation check in n8n's Git node enabled authenticated RCE, and how CodeQL's taint tracking can catch this pattern of external library bypass vulnerabilities.
Detailed cost comparison of AWS S3 Vectors vs Pinecone across usage patterns, revealing the real pricing dynamics.
Benchmarking AWS S3 Vectors latency across index sizes from 100 to 1M vectors and comparing with traditional vector databases.
We exploited an unsanitized `eval()` in an AI agent's memory filter for full RCE. Learn how it worked and the top steps to avoid similar AI memory-injection flaws.
Learn how Claude Code Observability reveals AI session costs and performance using OpenTelemetry and Grafana dashboards.
Learn how to build a production-grade AWS Athena MCP server that gives AI agents secure access to your data warehouse.
A practical guide to building retrieval-augmented generation pipelines on AWS with Bedrock and Pinecone.
Learn how Claude 4 Sonnet delivers near-instant responses and extended thinking with powerful coding and AI agent capabilities.
Explore Claude 4 Opus, Anthropic's advanced AI model for superior coding, extended reasoning, and tool integration. Learn its features and how to implement it effectively.
An engineer-friendly overview and playbook for defending against LLM memory injection attacks.
An overview of RAG, combining language models with external knowledge retrieval.
Prompt injection vulnerabilities in LLMs and how to mitigate them.
Learn how to protect AI systems from parameter pollution vulnerabilities with OWASP AI Security Labs.
Learn effective methods for combining data from multiple data sources. Master data join techniques in SQL and Python to merge multiple datasets into one unified view.
Learn how to identify, exploit, and mitigate the critical Next.js middleware authentication bypass vulnerability (CVE-2025-29927) with practical code examples and multiple defensive strategies.
A quick experiment on using GPT-4o-mini for document classification.
Learn how to build an AI agent's code execution environment with Jupyter Kernel Gateway
Research on the energy consumption of AI and its impact on global energy usage.
Learn about Large Language Model (LLM) evaluations, their importance, key metrics, and advanced evaluation techniques. Discover how to build effective evaluation sets, integrate human feedback, and compare LLM models.
Read about how I converted OpenAI's Swarm multi-agent educational framework to TypeScript using AI. Explore the conversion process, key insights, and the resulting TypeScript version.
Learn how to create a lightweight LLM text-to-SQL engine in Python. This guide explains generating SQL from natural language queries without relying on heavy frameworks.
Learn how I coordinated code changes across two open-source projects to save an AI agent system 90% on their LLM costs. Discover the challenges, solutions, and the impact of this cost-saving initiative.
Explore the process of tasking an LLM code agent with building a vector database service using FastAPI. Learn about the challenges, iterations, and final product of this AI-driven development experiment.
Learn why early-stage SAAS startups should embrace vendor lock-in with major cloud platforms. Discover the advantages, leverage cloud platform startup programs, and turbocharge your growth.
Learn about Mean Reciprocal Rank (MRR), a key evaluation metric in information retrieval systems. Understand its importance, formula, calculation, and applications in search engines and QA systems.
Web crawling has become more challenging due to advanced browser fingerprinting techniques. Learn how websites detect and block crawlers, and discover strategies for maintaining effective data collection.
Learn how to conquer the Spark small files problem in large-scale web crawling. Discover a robust solution for optimizing data storage and retrieval in Spark jobs.
Learn how to use the EDIT_DISTANCE function in BigQuery to calculate Levenshtein Distance for fuzzy string matching, data deduplication, and spell checking.
This guide demonstrates how to use Claude's tool use capability in conjunction with Pydantic to generate structured AI responses. By combining these technologies, developers can ensure consistent, type-safe output from Claude that integrates seamlessly with Python applications.
Learn how to make large language models (LLMs) behave predictably and provide structured outputs for production systems. Explore techniques for prompt engineering, JSON mode, function calling, and data validation with Pydantic.
Learn how to build an email classifier using affordable Language Models (LLMs) like GPT-4-mini and Ollama. Automate your inbox management with machine learning.
Learn how to build an effective Large Language Model (LLM) system. Explore key components, building blocks, and advanced techniques for designing LLM systems.
Explore the technical details of Llama 3's synthetic data generation approach for code generation tasks. Learn how this self-supervised learning system generates, solves, and learns from diverse coding challenges.
Learn how to perform cohort analysis in BigQuery to understand user behavior and engagement over time. Discover the benefits of using BigQuery for cohort analysis and advanced techniques for analyzing user cohorts.
Ever wondered how the top tech companies deploy their applications so seamlessly? It all starts with an efficient CI/CD pipeline.
Learn how to effectively find and match data in BigQuery using SQL functions, joins, window functions, and user-defined functions. Explore key concepts and practical examples for efficient data matching.
Learn how to build a flexible LLM evaluation tool with dynamic schema generation, synthetic data creation, and model evaluation using Python and LLMs.
Learn how to use Whisper audio to text conversion for long files with our Python script. Overcome file size limits and easily transcribe podcasts, interviews, and lectures. Step-by-step guide with code examples.
Learn how to standardize messy addresses using SQL. This guide provides SQL macros for cleaning up street addresses, city names, states, and ZIP codes.
Using LLMs to create a facial recognition platform for crowd analysis and recognition on protest footage.
Learn how to use LLMs, gpt-3.5-turbo, to scrape and clean code from the web
Learn how to host a Nextjs static app on AWS Cloudfront and S3 using AWS CDK. Static apps are great for SEO, performance, and cost.
A guide on deploying Next.js on AWS amplify with AWS CDK
Ever wondered how the top tech companies deploy their applications so seamlessly? It all starts with an efficient CI/CD pipeline.
Learn how to build a age and gender predictor using deep learning in TensorFlow
In my last tutorial, you learned how to create a facial recognition pipeline in Tensorflow with convolutional neural networks. In this tutorial, you’ll learn how a convolutional neural network (CNN) and Long Short Term Memory (LSTM) can be combined to create an image caption generator and generate captions for your own images.
Learn how to build a facial recognition pipeline with deep learning in Tensorflow. This tutorial will show you how to preprocess images, train a convolutional neural network model, and generate embeddings for use in clustering and classification tasks.