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.
You don’t need a deleted database to feel it.
“I changed one thing and it broke three I didn’t know were connected.”
Code Engine maps the blast radius before the change ships — everything it touches, and what broke the last time someone tried it.
“My AI forgets my whole codebase every session. I keep re-explaining it.”
It remembers — across sessions, and across models. The next agent opens your repo already knowing what the last one learned.
“Nobody here remembers why this file is written this way.”
The history comes with the code: the decisions, the dead ends, and the story behind why it is shaped like this.
“The agent confidently rewrote a file that was holding everything together.”
It knows what is fragile before it touches it — the warnings that never made it into the docs, surfaced the moment they matter.
“It’s 2am, the build is red, and I don’t know what changed.”
What changed since it was green: the failing builds, the deploy state, and the diff from the last version that worked.
“Two of us edited the same files and lost an afternoon of work.”
Claim locks, a shared board, and a decision log — so people and agents stop colliding, and nothing gets silently overwritten.
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.
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.
Contextual capabilities
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.
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.
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.
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.
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.
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.
The Forge — your agents, your repo.
Code Engine agents are your own. They work inside your repository and your information — pointed at your codebase, running through your own connection — so the understanding they build belongs to you and stays with you. An agent that knows your code, not a stranger meeting it new every time.
Self-organizing, not configured.
Nobody writes an instruction file for each capability. The 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.
{ "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.