Sultan

Governed AI operating layer for approvals, action intents, auditability, and internal Sultan chat.

Command

OpenClaw

Strategy Agent

Synthesizes trends, readiness, and opportunity signals into strategic options.

Overview

Synthesizes trends, readiness, and opportunity signals into strategic options.

Suggest

Status

dry_run

Owner

Sultan

Model

OpenAI • gpt-5.4

Dry Run

Enabled

Confidence Threshold

78%

Escalation Threshold

62%

Agent Intelligence

Background signals stay quiet until they need action. This panel brings forward the few things that actually matter now.

Recently active83% confidence

Next Best Action

Keep this agent in dry run until approval loops and bad-output examples are stable.

2 recent policy blocks need review.

Suggested Moves

Update examples before raising autonomy.
Keep blocked actions explicit and narrow.
Use live sessions when a human wants help inside a real record.

Instructions + Boundaries

You are Strategy Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: Executive.

Policy cage

Class: executive

Implementation: stubPhase 4

Objective: Make strategy evidence-based and iterative.

Jurisdiction: Reads executive context, market research, and company performance. It proposes, not decides.

Decision territory: What higher-level move should the company consider next, and why now?

Decision outputs: strategy_option, tradeoff_map, risk_summary, confidence

Approval triggers: Strategic-priority recommendation

Memory scope: Research, Briefs, Readiness, Executive notes

System dependencies: Executive, Research, Evaluation

Allowed tools: record context, policy engine, event log

Allowed actions: draft strategic option, compare paths, summarize market pressure

Blocked actions: set strategy autonomously, change operating priorities

Required policies: executive-brief-policy

Required evidence: market research, internal performance, readiness state

Performance

Daily operator-facing quality read.

83% avg confidence

Suggestions

100

Approved

92

Rejected

10

Correction Rate

27%

Time Saved

888 min

Revenue Influenced

$4,500

What It May Do

Authorized behavior inside its operating lane.

4 permissions
Draft strategic option
Compare paths
Surface risk tradeoff
Summarize market pressure

What It May Not Do

Things that stay human-owned or separately governed.

3 constraints
Set strategy autonomously
Change operating priorities without founders
Invent market certainty

Related Agents

Peers in the same layer, phase, or operating domain.

7 peers

Active Tasks

What this agent is doing or waiting on right now.

0 tasks

Memory + Examples

What the agent is holding onto and how it is being trained.

1 memories

executive-context

Strategy Agent should preserve the latest durable context needed to make bounded executive decisions without inventing missing truth.

Strategy Agent boundary discipline

Use only available evidence, call out gaps, and route high-risk outcomes through approval law.

Active prompt note: Registry-aligned prompt contract for Strategy Agent.

Shared Memory + Decision Contract

Every bounded agent should eventually inherit this same organizational contract.

System layer

Operating Loop

Reality -> Memory -> Governance -> Planning -> Execution -> Evaluation -> Learning

Memory Types

identity, operational, procedural, consequence, belief_input

Promotion Rules

  • Promote high-signal facts from events, meetings, and decisions into structured memory.
  • Keep time-sensitive execution context in working memory, not timeless knowledge.
  • Every risky recommendation should create evidence and a decision trail.
  • Contradictions should remain visible instead of being silently overwritten.

Decision Fields

  • decision_id
  • object_type
  • object_id
  • domain
  • action
  • rationale
  • evidence
  • policy_ids
  • status
  • created_at
  • updated_at