Blog
AI engineering insights, practical advice, and things I'm learning.
Ai Engineering
How to Build Enterprise AI with Mistral Forge on Your Own Data
Learn how Mistral Forge helps enterprises build custom AI models with private data, synthetic data, evals, and flexible deployment.
Mistral Forge · Enterprise Ai · Custom Models
Ai Engineering
How to Deploy NVIDIA Dynamo 1.0 for Production AI Inference Across GPU Clusters
Learn how to use NVIDIA Dynamo 1.0 to orchestrate scalable AI inference with KV routing, multimodal support, and Kubernetes scheduling.
Nvidia Dynamo · Inference Optimization · Gpu Clusters
Ai Engineering
How to Run NVIDIA Nemotron 3 Nano 4B Locally on Jetson and RTX
Learn to deploy NVIDIA's Nemotron 3 Nano 4B locally with BF16, FP8, or GGUF on Jetson, RTX, vLLM, TensorRT-LLM, and llama.cpp.
Local Llms · Edge Ai · Nvidia
Career
AI Engineer Career Path: Skills, Salary, and How to Get Started
AI engineering is a distinct role from ML engineering or data science. Here's what AI engineers do, what skills you need, what the pay looks like, and how to break in from other software roles.
Career · Ai Engineer · Skills
Ai Agents
How to Choose Between GPT-5.4 Mini and Nano for Coding Agents and High-Volume API Tasks
Learn when to use GPT-5.4 mini vs nano for coding, tool use, subagents, and cost-sensitive API workflows.
Openai · Gpt 5 4 Mini · Gpt 5 4 Nano
Ai Engineering
How to Deploy Mistral Small 4 for Multimodal Reasoning and Coding
Learn how to deploy Mistral Small 4 with reasoning controls, multimodal input, and optimized serving on API, Hugging Face, or NVIDIA.
Mistral Small 4 · Mistral Ai · Multimodal Models
Ai Engineering
How to Get Started with Open-H, GR00T-H, and Cosmos-H for Healthcare Robotics Research
Learn how to use NVIDIA's new Open-H dataset and GR00T-H and Cosmos-H models to build and evaluate healthcare robotics systems.
Healthcare Robotics · Physical Ai · Robotics Datasets
Prompt Engineering
System Prompts: How to Write Effective LLM Instructions
System prompts define how your LLM behaves. Here's how to structure them, what mistakes to avoid, and how provider-specific behavior affects your prompt strategy.
System Prompts · Prompt Engineering · Llms
Prompt Engineering
Chain of Thought Prompting: A Developer Guide
Chain of thought prompting makes LLMs reason through problems step by step. Here's when it works, when it doesn't, and how to implement it with practical patterns.
Chain Of Thought · Prompt Engineering · Reasoning
Prompt Engineering
Few-Shot Prompting: How to Guide LLMs with Examples
Few-shot prompting teaches LLMs by example instead of instruction. Here's how to choose examples, format them, and know when few-shot is the right approach vs. fine-tuning.
Few Shot Prompting · Prompt Engineering · Llms
Ai Engineering
How to Use Claude Across Excel and PowerPoint with Shared Context and Skills
Learn how to use Claude's shared Excel and PowerPoint context, Skills, and enterprise gateways for faster analyst workflows.
Anthropic · Claude · Excel
Ai Coding
Agent Skills vs Cursor Rules: When to Use Each
Cursor has both rules and skills for customizing the AI agent. They overlap, but they're not the same. Here's when to use each and how they interact.
Agent Skills · Cursor Rules · Cursor
Ai Agents
How to Add Memory to AI Agents
AI agents without memory forget everything between turns. Here's how to implement conversation buffers, sliding windows, summary memory, and vector-backed long-term recall.
Ai Agents · Memory · Conversation History
Ai Coding
How to Create Your First Agent Skill
A step-by-step guide to writing an agent skill from scratch: directory structure, SKILL.md format, effective descriptions, common patterns, and a complete working example.
Agent Skills · Cursor · Claude Code
Ai Agents
How to Evaluate and Test AI Agents
Evaluating AI agents requires different metrics than evaluating LLMs. Here's how to measure task completion, trajectory quality, tool-use accuracy, and regression across agent systems.
Ai Agents · Evaluation · Testing
Ai Coding
What Are Agent Skills and Why They Matter
Agent skills are portable packages of instructions that extend AI coding agents. Here's what they are, how they work, and why the open standard changes how developers work with AI tools.
Agent Skills · Cursor · Ai Coding
Ai Engineering
How to Reduce LLM API Costs in Production
LLM API costs add up fast in production. Here are the practical strategies that work: prompt caching, model routing, batching, output limits, and cost-per-task tracking.
Llm Costs · Prompt Caching · Ai Engineering
Ai Engineering
LLM Observability: How to Monitor AI Applications
Traditional monitoring doesn't cover LLM applications. Here's what to log, how to trace multi-step chains, and how to detect quality regressions before users do.
Observability · Monitoring · Llm Ops
Ai Engineering
How Function Calling Works in LLMs
Function calling lets LLMs interact with external systems by requesting structured tool executions. Here's how the loop works, how to define tools, and what to watch for across providers.
Function Calling · Tool Use · Llms
Ai Agents
How to Build Stateful AI Agents with OpenAI's Responses API Containers, Skills, and Shell
Learn how to use OpenAI's Responses API with hosted containers, shell, skills, and compaction to build long-running AI agents.
Openai · Responses Api · Ai Agents