Frontier tech insights and engineering notes on GPT-5.4, Claude 4.6, and Gemini 3.1
Curated in-depth articles
Tools don't matter — methodology does. A deep dive into six core methods for mastering AI coding: Spec-Driven Development, Context Engineering, TDD Verification Loops, Multi-Agent Orchestration, Advanced Prompting, and Session Hygiene. Plus a 20+ tool matrix and five anti-patterns to avoid.
Read Full Article →Explore the latest trends and deep analysis in AI tech
AI Agents are not traditional software; we are debugging the reasoning process rather than the code itself. This article explores Trajectory Evaluation, LLM-as-a-Judge, and practical applications of mainstream Agent observability tools like LangSmith and Langfuse.
Read Full Article →The hottest concept in 2026, evolving from Prompt Engineering to Context Engineering. A deep dive into managing the context window through Write, Select, Compress, and Isolate strategies to solve long-context amnesia, hallucinations, and context poisoning.
Read Full Article →Cease the obsession with writing more code; shift focus to deep evaluation thinking. We deconstruct LLM-as-a-Judge biases, the mathematics behind metrics, and reshaping CI/CD defenses for probabilistic systems.
Read Full Article →Stop theorizing, start quantizing. From downloading pre-quantized models, to hands-on weight compression with AWQ/GPTQ/GGUF, to vLLM FP8 zero-calibration production deployment and QLoRA fine-tuning—four routes, each with complete copy-paste code.
Read Full Article →A retrospective of six pivotal technology crossroads in AI's seventy-year history, dissecting the compute constraints, data dividends, and scalability logic behind each historical choice.
Read Full Article →A deep dive into vLLM's core architecture (PagedAttention, continuous batching, APC prefix caching, speculative decoding) for online serving. Covers OpenAI-compatible API setup, performance tuning, token billing systems, and complete Docker deployment with Prometheus monitoring.
Read Full Article →A panoramic view of the capabilities of the top 3 AI models
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Dedicated to technical research and practical sharing in the field of AI large models.
Recording the development context of frontier technologies and exploring the application boundaries of artificial intelligence.