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Harness Engineering: Build the Runtime That Turns an LLM Into an Agent (Part 3/3)
Part 3: The Memory — Skills, Todos, Subagents, and the Full PictureThis is Part 3 of a 3-part series.…
TypeSafe’s Jev AI Model and the Hidden Language Tax in LLMs
Jev replaces open-ended generation with choices, scores, and probabilities. Its bigger idea is more…
Jev introduces a new shape of LLM - System One, aka Decision Models
Last week TypeSafe AI unveiled Jev, their first example of a new category of model that they are calling…
How Test-Time Scaling Allocates LLM Reasoning Across Depth, Width, and Feedback
Test-time compute is the work an already-trained model performs for one request while producing, checking, or…
Pruning LLMs Like a Physicist: Block Removal as an Ising Optimization Problem
Back to Articles Pruning LLMs Like a Physicist: Block Removal as an Ising Optimization Problem Team Article…
Not Every AI Decision Needs an LLM: Inside TypeSafe’s Jev
Jev gives up text generation for typed probabilities, low latency, and a very different role inside…
llm-keys-ui 0.1
Release: llm-keys-ui 0.1 This plugin solves a very specific problem. I've started using Codex Remote to run…
How Constrained Decoding Makes LLM Outputs Follow a Schema
An LLM can return JSON that parses perfectly, matches every required field, and is still dangerous to…
5 Prompt Optimization Strategies That Actually Improve LLM Output
This article covers five prompt optimization strategies such as: prompt optimization, prompt engineering, LLM…
The Local LLM Stack in 2026
The friendly app is the door. The real game is GGUF, engines, caches, and chips.Continue reading on…
Harness Engineering: Build the Runtime That Turns an LLM Into an Agent (Part 1/3)
Part 1: The Core — Agent Loop, Tools, and PermissionsThis is Part 1 of a 3-part series. Part 2: The…
How To Write With An LLM
How To Write With An LLM Thomas Ptacek on using LLMs as copyeditors, not as writing assistants: Rule Number…
PrismML hopes its tiny LLM will change how we all use AI
If AI lab PrismML isn’t on your radar yet, it should be — not because it’s raised gobs of money (it…
LLMs respond differently to harmful prompts when AI watermarking is used
In response to a new European Union law, AI platforms are implementing new schemes for watermarking the…
Benchmarking Local LLM Servers: llama.cpp, llamafile, LM Studio, and Ollama
Running an LLM locally is more than choosing a model. The serving tool plays an essential role, as it…
How Sparse Attention Makes Long-Context LLMs Cheaper, and What It Misses
An LLM can accept a very long prompt without treating every earlier piece the same way. The model represents…
Estimators in Scikit-LLM: A KDnuggets Cheat Sheet
Scikit-LLM wraps language models in the scikit-learn estimator API, so it drops into a Pipeline or a…
[AINews] Jev: a “System One Model” that only decides/classifies/routes/scores — >100x faster, >200x cheaper than small frontier LLMs
AIEi Paris (Sep 23-24) and AIE NYC (Oct 12-14) is >50% sold out, AIE CODE (Nov 10-12 in SF) and AIEi Shanghai…
Stop Treating LLMs Like Search Engines: Building Reliable TypeScript Agents
Move beyond zero-shot prompts by coupling LLM orchestration with Zod validation boundaries, idempotency, and…
How to Fine-Tune a Large LLM on Low VRAM Without Renting a GPU
Eight steps, the arithmetic that decides whether it’s worth starting, and the check that will fail…
How to run a trillion-parameter LLM on a CPU with 8 GB of RAM
Someone else’s engine, the four reductions that take 5,560 GB down to 8.24, and the one-minute test that…
Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference
When you build an application on top of a large language model (LLM), the prompt you send to the model…
Model-agnostic PII detection with LLMs
A configurable, instruction-driven detector that runs on any large language model (LLM) managed on Amazon…
Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM
On August 12, 2026, Alibaba’s Qwen team released Qwen3.8-2.4T-A95B. This is the first time a Qwen-Max-class…