15:I[981,["658","static/chunks/658-a698693f56d0116a.js","183","static/chunks/183-6beeeb801c274aaa.js","474","static/chunks/app/%5Btype%5D/layout-631c4730b83c8223.js"],"Posts"] 16:T43e,I’ve been building VT Code, a Rust-based terminal coding agent that combines semantic code intelligence (Tree-sitter + ast-grep) with multi-provider LLMs and a defense-in-depth execution model. It runs in your terminal with a streaming TUI, and also integrates with editors via ACP and a VS Code extension.

* Semantic understanding: parses your code with Tree-sitter and does structural queries with ast-grep.

* Multi-LLM with failover: OpenAI, Anthropic, xAI, DeepSeek, Gemini, Z.AI, Moonshot, OpenRouter, MiniMax, and Ollama for local—swap by env var.

* Security first: tool allowlist + per-arg validation, workspace isolation, optional Anthropic sandbox, HITL approvals, audit trail.

* Editor bridges: Agent Conext Protocol supports (Zed); VS Code extension (also works in Open VSX-compatible editors like Cursor/Windsurf).

* Configurable: vtcode.toml with tool policies, lifecycle hooks, context budgets, and timeouts.

GitHub: https://github.com/vinhnx/vtcode17:T681,I built BindWeave, a subject-consistent video generation model that fuses multimodal reasoning with diffusion to keep your characters, objects, and creative intent perfectly aligned across shots. Instead of prompting frame by frame, BindWeave understands who’s who and what’s happening — maintaining story and visual continuity from single-person clips to multi-actor scenes.

What it does

Cross-Modal Integration for Fidelity – Binds text intent to visual references for faithful generation (MLLM-DiT core).

Single or Multi-Subject Consistency – Keeps identities and roles stable across frames and scenes.

Entity Grounding & Role Disentanglement – Reduces character swaps and attribute drift.

Prompt-Friendly Direction – Understands shot type

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