Meta's Muse Code is a beta terminal-based AI coding agent for macOS and Linux, powered by Muse Spark 1.2 and built for complex tasks across large repos.

Vendor agents give you no settings to configure, only answers to interrogate. These five questions separate a real proof trail from a confident non-answer.

Meta's Muse Code is a beta AI coding assistant built on Muse Spark 1.2. It runs parallel sub-agents, logs crash recovery, and prices at $1.25 per million input tokens.

Meta's Muse Code enters beta to compete with Claude and Codex, promising a contributor tier that's more than 10x cheaper in exchange for usage data.

Gartner reports data center electricity demand rising 26% to 565 TWh in 2026. Here is a six-question email to send your AI vendor before your next contract renewal.

Meta launched Muse, an AI coding agent that runs in your terminal and coordinates subagents with crash recovery. On the benchmarks that matter, it lags behind Claude Code and Codex.

Meta's first AI coding agent, Muse Code, targets Claude and Codex with pay-as-you-go pricing and an optional zero-data-retention tier for enterprise users.

AppWizzy launched an MCP server that connects AI coding agents directly to its project infrastructure. Agents can create, deploy, and monitor cloud projects through a secure OAuth connection.

Supabase released supabase/evals under Apache-2.0 to benchmark Claude Code, Codex, and OpenCode on real engineering tasks inside containerised sandboxes.

A controlled study on 116 Python tasks found that pairing the weaker Codex as reviewer over Claude cut accuracy and more than doubled cost. Hierarchy matters.

A Microsoft Azure and AI MVP lays out how tiered inference routing splits coding requests across on-device, on-prem, and cloud models to cut cloud token usage without dropping quality.

Context isolation and task coordination are the two structural limits hitting autonomous AI coding agents in multi-project environments. Here is what the failure looks like.