Tag: #ai-engineering

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• The 2026 Vision Model Development & Fine-Tuning Guide — CNN, ViT, DETR, SAM 2, VLMs and a Real Decision Tree ♪ Listenable

  Vision model development in 2026 is no longer 'grab a ResNet and call it a day.' Between CNNs, ViTs, DETR variants, SAM 2, and VLMs like LLaVA, Qwen-VL, Gemini Vision, and Claude Vision, your choice for the same photo ca

  2026-05-14 · 20 min read #computer-vision#vision-model#cnn#vit#detr

• The Developer's Podcast Curation 2026 — From Latent Space to Changelog to SE Daily, the Commute-Sized Signal ♪ Listenable

  If books are the skeleton of judgment and videos are the muscle, podcasts are the blood vessels running through that muscle. Commute, walk, dishes, drive — the half-attention hours of your week — that's where the industr

  2026-05-14 · 26 min read #developer-podcasts#latent-space#changelog#podcasts#learning

• LLM Landmark Papers Guide — From Attention to GPT, LLaMA, DeepSeek, o1, and Claude (with References, 2026)

  Where do the real shifts in LLMs come from? From Attention is All You Need in 2017 to the reasoning models of 2026, this guide organizes the 20-odd landmark papers you must know, by era and theme. Each paper is compresse

  2026-05-14 · 15 min read #llm#research-papers#transformer#gpt#llama

• Agent Evaluation Systems in 2026 — Inspect AI vs Promptfoo vs Phoenix vs LangSmith vs OpenAI Evals (You're Measuring the Agent, Not the Model) ♪ Listenable

  LLM evals measure the model. Agent evals measure whether the model plus the harness plus the tools actually carry a task to completion. They are different problems. This is a map of the 2026 landscape — Inspect AI from U

  2026-05-14 · 20 min read #agent-evaluation#inspect-ai#promptfoo#phoenix#langsmith

• AI Coding Assistant Limitations 2026 — An Honest but Fair Take on What Doesn't Work ♪ Listenable

  AI coding assistants are powerful. But the shape of that power is not uniform. Deep bug debugging, large-codebase architecture, subtle performance regressions, concurrency correctness, genuinely new tech, multi-repo chan

  2026-05-14 · 21 min read #ai-coding#ai-limitations#honest-take#ai-engineering#claude-code

• Anatomy of an AI Harness — The Scaffolding That Turns a Model Into an Agent (Loop, Tools, Context, and Building Your Own)

  The model is the engine; the harness is the car. Put a different car around the same engine and the driving experience changes completely. In 2026, the real center of gravity in AI engineering isn't the model — it's the

  2026-05-14 · 16 min read #ai-harness#ai-agent#llm#agent-loop#tool-execution

• Python Complete Guide — FastAPI, AsyncIO, Pydantic, uv, Polars, AI Engineering (Season 2 Ep 5, 2025)

  Python used to be the "slow, GIL-locked" language. The 2024-2025 Python is a completely different beast — free-threading (No-GIL) experiment, JIT compiler, the revolutionary uv package manager, Polars with a Rust-backed

  2026-04-15 · 11 min read #python#fastapi#asyncio#pydantic#uv

• AI Engineering in Practice — LLM API, RAG, Agents, LoRA/DPO, Vector DB, Evaluation, Observability, Prompt Injection (2025)

  The real difficulty of production LLM API calls, why RAG is not simple lookup, agent patterns (ReAct, Plan-Execute, ReWOO), when to and when NOT to fine-tune (LoRA, QLoRA, DPO), a vector DB decision matrix, why LLM evalu

  2026-04-15 · 7 min read #ai-engineering#llm#rag#ai-agent#lora

• What is an AI Harness: Skills, Context, Hooks, and Permissions — The Orchestration Architecture Controlling AI ♪ Listenable

  An AI Harness is an orchestration layer that wraps and controls AI models. We dissect the 7 building blocks — System Prompt, Tools, Context, Skills, Hooks, Permissions, and Memory — and show how to build one with the Cla

  2026-03-23 · 35 min read #ai-harness#claude-code#agent-sdk#skills#context