Technical Articles

Practical articles, in-depth tutorials, and architectural insights on software engineering, AI, and systems.

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How to build reliable RAG with semantic chunking

Learn practical engineering steps to prevent AI hallucinations by splitting texts by context and removing vector noise.

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IA•2 min

Why activists want to freeze new frontier AI models

Understand the lawsuit filed in the San Francisco Superior Court by civic groups demanding a freeze on frontier AI model training.

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IA•3 min

How to mitigate hallucinations in RAG with cross-validation

Learn how to implement semantic verification layers in retrieval-augmented generation pipelines to stop false AI responses.

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IABackend•3 min

How to Implement Secure Function Calling with JSON Schema

Learn how to protect your artificial intelligence against malicious parameters using strict schema constraints to ensure structured responses.

IAEngenharia•4 min

How Claude Code Projects coordinates multiple autonomous agents

Explore how Claude Code Projects revolutionizes software engineering through parallel subtask orchestration, strict context isolation, and autonomous drift mitigation.

IA•3 min

Meta Muse, Wonder and Ember: Which AI model to choose?

Discover the new Meta Superintelligence Labs architecture with Muse, Wonder, and Ember. Learn which model to use for complex reasoning, assistants, and repetitive tasks.

IA•3 min

Can Gemini, ChatGPT and Claude stop Amazon fraud? Tested

Compare the technical performance of Gemini, ChatGPT, and Claude in detecting fake Amazon messages, evaluating false positives and SMTP headers.

IA•2 min

How to replace Photoshop with local AI in Krita via GPU

Learn how the Krita AI Diffusion plugin replaces cloud generative fill with local models running entirely on your own GPU hardware.

IAEngenharia•4 min

How to Implement Secure Function Calling with JSON Schema

Protect your AI applications against injections and critical failures using rigorous input parameter validation in LLM tool calls.

IA•3 min

How to use persistent instructions in Gemini 4 Hydrogen

Discover how Gemini 4 Hydrogen revolutionizes development with persistent instructions. Read technical analysis, latency benchmarks, and productivity gains.

IAEngenharia•3 min

How to create persistent vector memory for AI agents

Learn how to build long-term memory layers for AI agents using vector databases, efficient indexing, hybrid search, and data pruning.

IAEngenharia•4 min

How to implement MCP protocol in AI agents securely

A practical engineering guide on the Model Context Protocol (MCP) to connect local data sources and external tools to LLMs with context isolation and command validation.

IA•1 min

Gemini 4 Hydrogen: Costs and What Changes for Developers

Evaluate the cost-benefit of Gemini 4 Hydrogen for your AI applications. We analyze token pricing, context windows, and response latency to understand the direct impact on software architecture and user experience.