Author

Shan

Shan edits AI Mastery's daily reporting and evaluates new models, developer tools, and infrastructure through an engineering-first lens.

S
ShanEditor & AI Systems Builder

Shan edits AI Mastery's daily reporting and evaluates new models, developer tools, and infrastructure through an engineering-first lens.

AI PlatformsAutomationLLM OpsDeveloper Tools

Recent work

news
Shan • 2026-10-20
InceptionDiffusion LLMBenchmarksPricingAI Models

Inception Mercury 3: 1,068 Tok/s, 1M Context, 8 of 12 Benchmarks

Inception's diffusion LLM claims 1,068 tokens per second, a 1M-token context window, and wins on 8 of 12 self-reported benchmarks against GPT-6 Luna and Claude Haiku 5.5.

Read more →
guides
Shan • 2026-10-20
Claude Agent SDKAI agentsAnthropicWeb researchPython

Build Stateful Web Research Agents with Claude Agent SDK

Run one-off and stateful Claude research agents that search the web, cite sources, and read multimodal inputs with the Anthropic Cookbook pattern.

Read more →
news
Shan • 2026-10-19
AnthropicClaude HaikuPricingBenchmarksModel Release

Claude Haiku 5.5: 90% Price Cut, 1M Context, Adaptive Effort

Claude Haiku 5.5 drops to $0.10 per million input tokens, expands to a 1M context window, and adds adjustable effort—but migration breaks old sampling-parameter calls.

Read more →
news
Shan • 2026-10-18
Open SourceAI AgentsInfrastructurePerplexityCybersecurity

Perplexity SPACE Sandbox: 0 VM Escapes in 108 Red-Team Runs

Perplexity open-sourced SPACE, the Firecracker microVM sandbox behind Perplexity Computer: Rust 0.8.0, 0 escapes in 108 red-team runs, egress bypasses fixed.

Read more →
Build a Titanic Data Analyst Agent with smolagents
guides
Shan • 2026-10-18
smolagentsHugging Facedata analysiscode agentmachine learning

Build a Titanic Data Analyst Agent with smolagents

Use smolagents CodeAgent to explore Titanic data, generate plots, and train an ML baseline from one natural-language prompt.

Read more →
news
Shan • 2026-10-17
Open WeightsMixture of ExpertsStepFunAgentic AIBenchmarksInference

StepFun Opens 600B MoE Weights: 27B Active, 1M Context

StepFun's Step 5 Preview is now open weights: a 600B sparse MoE with 27B active parameters, 1M context, and a $1.00/$2.70 API.

Read more →
Run a Microsoft AutoGen Team as a FastAPI WebSocket App
guides
Shan • 2026-10-17
AutoGenFastAPIWebSocketmulti-agentPython

Run a Microsoft AutoGen Team as a FastAPI WebSocket App

Adapt Microsoft AutoGen's app_team.py into a FastAPI WebSocket endpoint that streams multi-agent chat, persists state, and serves a browser UI.

Read more →
news
Shan • 2026-10-16
Open WeightsMetaMoEMac StudioBenchmarksDeployment

Meta's Muse Spark Open Puts 816B MoE on Two Mac Studios

Meta's open-weight 816B MoE activates 42B parameters, holds 1M context, runs on two M5 Ultra Mac Studios, and leads on MCP-Atlas but trails on coding.

Read more →
news
Shan • 2026-10-15
Open WeightsNVIDIAMultimodalMoEBenchmarksAI Agents

NVIDIA Nemotron 3.5 Super VL: 120B MoE Runs on a Single GPU

NVIDIA's Nemotron 3.5 Super VL combines 120B total parameters with 12B active and runs the NVFP4 checkpoint on one DGX Spark, H200, or GB200.

Read more →
Fine-Tune a Quantized Llama on GSM8K with PEFT LoftQ
guides
Shan • 2026-10-15
PEFTLoftQquantizationGSM8KLlamafine-tuning

Fine-Tune a Quantized Llama on GSM8K with PEFT LoftQ

A step-by-step walkthrough of the Hugging Face PEFT GSM8K LoftQ script: 4-bit NF4 loading, preprocessing, training, and exact-match accuracy.

Read more →
news
Shan • 2026-10-13
Gemini 4 ArgonGoogle DeepMindPricingBenchmarksAI Models

Gemini 4 Argon Ships $2 Input, 1M Token Output

Google's Gemini 4 Argon launches with $2 per million input tokens, $10 per million output tokens, and a 1M-token output limit, undercutting frontier rivals on price.

Read more →
Benchmark Local Models with llama.cpp's llama-eval.py
guides
Shan • 2026-10-13
llama.cppevaluationbenchmarkingLLMGGUFAI engineering

Benchmark Local Models with llama.cpp's llama-eval.py

Use llama.cpp's single-file eval harness to run reproducible AIME, GSM8K, and GPQA benchmarks against a local server with Wilson confidence intervals.

Read more →