Tag: #ai-engineering
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 9 posts
The 2026 Vision Model Development & Fine-Tuning Guide — CNN, ViT, DETR, SAM 2, VLMs and a Real Decision Tree
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#detrThe Developer's Podcast Curation 2026 — From Latent Space to Changelog to SE Daily, the Commute-Sized Signal
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#learningLLM 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#llamaAgent Evaluation Systems in 2026 — Inspect AI vs Promptfoo vs Phoenix vs LangSmith vs OpenAI Evals (You're Measuring the Agent, Not the Model)
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#langsmithAI Coding Assistant Limitations 2026 — An Honest but Fair Take on What Doesn't Work
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-codeAnatomy 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-executionPython 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#uvAI 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#loraWhat is an AI Harness: Skills, Context, Hooks, and Permissions — The Orchestration Architecture Controlling AI
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