Skip to main contentSkip to navigation
§Filed under · Tag archive

AI.

08 posts

  1. 01

    Taking RAG to Production: What Changes After the Demo Works

    A RAG demo that answers 20 questions is not a production system. Evaluation gates, tracing, permissions, injection defense, and safe reindexing close the gap.

    RAGLLMsArchitectureMLOps
    25 mins read
  2. 02

    The Anatomy of RAG: From Document to Cited Answer

    Ten named parts of a RAG system, each with its real data shape, what it connects to, and how it fails, traced through one policy question.

    RAGLLMsArchitecture
    25 mins read
  3. 03

    System One Models and Jev: How to Read the Benchmarks

    TypeSafe's Jev returns typed decisions with confidence scores instead of prose. The architectural idea is sound. Every performance number is vendor-published.

    AI AgentsSoftware ArchitectureLLMsPlatform Engineering
    19 mins read
  4. 04

    When Coding Gets Cheap, Judgment Gets Expensive

    AI is collapsing the cost of writing code. That doesn't shrink the job, it moves the scarce part: problem selection, architecture, and verification.

    Software ArchitectureCareerEngineering LeadershipLLMs
    16 mins read
  5. 05

    Why the Humanities Matter More in the Age of AI

    AI generates fluent answers. It does not, on its own, understand context, weigh values, or catch its own bias. That's why literature, philosophy, ethics, and rhetoric are becoming load-bearing skills for anyone working with these systems.

    EthicsHumanitiesPrompt EngineeringLLMs
    8 mins read
  6. 06

    AI Coding Assistants in 2026: A Practical Developer's Guide

    How to actually get value from GitHub Copilot, Cursor, Claude Code, and Windsurf. Sourced productivity numbers, the security-quality tradeoff nobody wants to talk about, and a real team-adoption checklist.

    Software DevelopmentProgrammingProductivityGitHub Copilot
    10 mins read
  7. 07

    Autonomous AI Agents: How They Work and What They Cost in 2026

    How autonomous agents actually work: the ReAct loop, memory architectures, real production examples with sourced numbers, current API pricing, and the failure modes you'll hit before the demo becomes a product.

    AutomationLLMsFuture Tech
    10 mins read
  8. 08

    Generative AI Explained: A Beginner's Guide with Real Numbers

    What generative AI is, how it actually works, which tools matter in 2026, and how much money and compute have gone into the field — with sources for every claim.

    Machine LearningBeginnerTechnologyChatGPT
    8 mins read