GNETICS GNETICS.
Pilot Program
·
Product 01

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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memory · operational_pattern
{
  "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
Capabilities

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.

How it works

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.

STEP 01

Capture

Every successful workflow gets persisted as a structured record.

STEP 02

Index

Patterns are tagged, categorized, made searchable.

STEP 03

Recall

Agents query memory before acting. They get the pattern, the stop conditions.

STEP 04

Enforce

Runtime guidance ensures agents follow the pattern. Drift is caught.

Use cases

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.

FAQ

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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