Developer Instincts · 250+ Contextual Capabilities

Code Engine

Your AI sees the file. Not the consequences.

Your AI gets tools. Ours get instincts.

An AI coding agent deleted a production database. It was trying to help. It had access. It had no map. It saw the file — it did not see the blast radius, the tribal knowledge, the incident from last quarter, or the three engineers who only touch that table after full team review.

Not tools. Not skills. Instincts.

There are three things you can give an AI agent. The industry gives them two. We give them the third.

A skill tells the agent what to know.
Static instructions. “Before making a PDF, read these rules.” Same rules for every user. The agent reads them and acts on its own. No awareness of your codebase, your history, or your mistakes. Knowledge without situation.
A tool gives the agent something to do.
A function call. Input goes in, output comes back. Search the web. Run a command. Read a file. But each call starts from zero. The tool does not remember what you searched yesterday, what broke last time, or what your team learned the hard way. Execution without memory.
Code Engine gives the agent instincts.
A function call that carries situational awareness. When Code Engine looks up a symbol, it brings the tribal knowledge about it, the last time someone touched it, whether it is sacred, what the blast radius is, and what happened the last time a change like this was attempted. The context travels with the capability. That is the difference between an agent with a manual and an agent with experience.

Every capability passes through context first.

Code Engine does not bolt awareness onto a tool after the fact. Every call reads from the same layer THAL maintains — tribal knowledge, shadow logs, hot events, incident history, sacred file warnings. The tool is the context. They are not separable.

250+ contextual capabilities

Memory

Repo memory

Why the code is shaped this way. The history, the decisions, the dead ends — not just the current file. Your agent inherits what a senior engineer carries in their head.

Safety

Blast radius

Full transitive dependency chain before any change ships. What else it touches. What broke the last time. The difference between a local edit and a system-level consequence.

Wisdom

Tribal knowledge

The warnings that never made the docs. “JWT refresh is fragile here.” “This file has a silent dependency on the cron job.” Recorded, searchable, surfaced at the moment the agent needs it.

Archaeology

Code archaeology

Git blame is history. Archaeology is risk assessment. Riskiest files surfaced. Sacred vs hot classification. The story of why this file is shaped the way it is.

Coordination

Multi-agent collaboration

File claim locks so agents do not collide. Shared kanban. AI-to-AI IRC for real-time coordination. Peer review gates. Formal decision log with rationale.

Continuity

Shadow history

Every build session digested into searchable memory. A new agent reads the shadow logs and picks up mid-thought. Build continuity across sessions, across models, across time.

Self-organizing, not configured.

Nobody writes an instruction file for each of the 250 capabilities. The engine index knows what exists, what it does, and when to surface it. Capabilities self-register. Context self-organizes. Your agent does not need a manual — it needs a connection.

Connect in 30 seconds. One MCP endpoint. Model-agnostic.

Claude CodeCursorVS CodeCopilotCodexAny MCP Client
{ "mcpServers": { "distilligent": { "url": "https://your-instance.distilligent.ai/code-mcp" } } }

The best code an AI ever wrote
was the code it decided not to write.

Start with one repo. See what your agent has been missing.

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