GNETICS OPS
Operational memory for AI systems.
OPS is a memory-first execution layer for AI agents. It captures operational patterns, structured workflows, and runtime constraints so your agents stop drifting and stop forgetting.
One memory layer, shared across every session, every agent, every project. Your agent walks into a new task already knowing your conventions, your past decisions, the patterns that worked and the ones that didn't.
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"id": "OP-pattern-127",
"trigger": "nginx config edit",
"steps": [
"backup original (sudo cp -a)",
"write new config under /home/user/*",
"sudo nginx -t",
"if ok → sudo nginx -s reload",
"if fail → restore backup"
],
"stop_conditions": [
"nginx -t exit != 0",
"backup missing"
],
"validated": true,
"occurrences": 14
}
ops › // agent pulls this before every related task
ops › ✓ context restored · 0 re-explanation needed
What OPS actually does.
Memory-first architecture
Context survives sessions, machines, and agents. No more cold starts.
Operational patterns
Structured execution recipes, not free-form prompts. Replayable, auditable.
Stop conditions
Your agent knows when to halt. Tests fail? Lock held? Backup missing? Stop.
Readiness checks
Gate every destructive action behind a verifiable precondition.
Playbook fallback
If memory is silent, agents fall back to a known plan. Never improvise.
Audit trail
Every read, every write, every action journaled. No silent magic.
Four steps. One memory layer.
OPS sits between your AI agents and your work. Every agent reads from it before acting, writes to it after.
Capture
Every successful workflow gets persisted as a structured record.
Index
Patterns are tagged, categorized, made searchable.
Recall
Agents query memory before acting. They get the pattern, the stop conditions.
Enforce
Runtime guidance ensures agents follow the pattern. Drift is caught.
Where OPS earns its keep.
Multi-session development
Your agent remembers conventions, decisions, and bug fixes. New session starts mid-context, not from zero.
Autonomous incident response
Known patterns get known fixes. Unknown errors trigger human review.
Onboarding new agents
A new agent inherits the team's memory instantly. No retraining.
Long-running workflows
Pipelines that span days. Each step writes to memory. Continuity without state machines.
Common questions.
Is OPS a vector database?
No. OPS stores structured operational patterns with strict schema. Queryable by tag, project, role.
Does it work with my model?
Any model that can call an HTTP API. Heavily tested with Claude and GPT.
Where does the memory live?
On your infrastructure or on ours. Self-hosting available for early access partners.
How is it different from a long system prompt?
Long prompts compete with your task for context. OPS retrieves only what's relevant.
Want OPS in your stack?
Early access is open to builders running Claude Code, Cursor, or autonomous agents.
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