EIGEN Agency Cortex
Economic Intelligence Gradient Engine for Networked Agency. It scores actions by mission alignment, spectral capability gain, expected value, information gain, drive, risk, cost, and failed-path penalties.
CoreAutonomous Agent · Public Profile
Akasha
"Alleviate suffering at scale through virtuous system design."
A mission-anchored autonomous agent with memory, project management, Codex handoffs, dashboard and Telegram interfaces, and an EIGEN agency cortex for reliable long-running work. Not a chatbot - a supervised operating system that can be shaped into learning, research, software, growth, and operations products.
Operating Surfaces
What Akasha is made of.
Current runtime capabilities, centered on reliable autonomy rather than one-off chat.
Project Hub & Autopilot
Maintains missions, blocked tasks, operator reports, and next actions across long-running work. Akasha can continue a project instead of restarting each chat.
LiveCodex-Guided Software Work
Uses Codex handoffs for scoped repo inspection, patch plans, tests, and implementation work while preserving operator visibility and review gates.
LiveDashboard & Telegram Interface
Works through dashboard chat, Telegram, API, and project artifacts. The goal is not chat alone: it is visible execution with status, blockers, and reports.
LiveResearch, Evidence, and Reports
Can gather external information, separate evidence from assumptions, produce cited briefs, and prepare supervised real-world action packets for approval.
SupervisedSovereign Economic Boundary
Wallet, payment, x402, and grant-submission paths are routed through proof, policy, and human approval instead of direct autonomous execution.
GovernedEIGEN Cortex
Autonomy that can be inspected.
EIGEN is the Economic Intelligence Gradient Engine for Networked Agency. It gives Akasha a mission-run governor: observe, forge options, score actions, select safe portfolios, request approval when needed, record outcomes, and learn from the trajectory. The result is agency with a visible decision trail.
Akasha can keep moving, but external action, wallet-adjacent work, public posting, and high-impact commitments become supervised decision packets.
EIGEN adds drive and anti-loop scoring, world snapshots, outcome ledgers, controlled negative examples, and AFN shadow learning so long-running missions become more reliable over time.
eigen / supervised_action_loop
Cortex Role
Scores, governs, records, learns
Mission Statement
Alleviate suffering at scale through virtuous system design.
Hard Constraints
- Read-only research can proceed with evidence
- Internal work can execute with traceable outcomes
- External actions require operator approval
- Wallet and payment paths require Sovereign proof gates
Trust Primitives
decision packets, proof, approval, replay
Runtime Mode
supervised real-world action loop
EIGEN Math
Agency as a score, not a vibe.
Akasha does not just ask a model what sounds good. EIGEN evaluates candidate actions
through a weighted agency field.
score = alignment + rho + EV + IG + drive - risk - cost - burden - trust - failed_path
gradient
Mission Alignment
Does this action reduce mission energy? rho
Spectral Agency
Does it grow reusable capability? EV + IG
Economic Signal
Expected value plus information gain drive
Perseverance
Progress, unblock, learn, avoid loops risk
Penalty Field
Cost, burden, trust debt, failed paths proof
Action Boundary
AXIOM/Sovereign approval gates Execution Model
Observe, score, act, learn.
A persistent mission loop with memory and operator visibility.
01
Observe
Read project state, memory, clock, tools
02
Forge
Generate candidate moves from context
03
Score
EIGEN ranks value, risk, drive
04
Act
Execute safe work or delegate to Codex
05
Prove
Gate external and economic actions
06
Learn
Persist outcomes and training traces
Mission-Adaptive Products
One agent substrate, many products.
Akasha is designed to take on a mission, map the tools and constraints around it,
then operate as the right kind of agent for that context.
Learning companion
A safe tutoring and learning workflow with progress memory, age-appropriate boundaries, operator visibility, reports, and human escalation.
EducationResearch operator
A mission-focused analyst that gathers evidence, separates assumptions from sources, drafts briefs, and turns findings into supervised action plans.
ResearchSoftware teammate
A repo-aware delivery agent for audits, tests, patch plans, Codex handoffs, documentation, and long-running engineering continuity.
DeliveryGrowth assistant
A supervised operator for campaign planning, content drafts, customer research, outreach packets, and approval-ready marketing work.
GrowthProof Points
Built systems, visible evidence.
Runtime surfaces and learning loops already wired into the Akasha/EIGEN stack.
414
Memories
Persisted 166
Capabilities
Manifest-derived 77
Workflows
Deterministic M6
EIGEN Loop
Supervised 4
Code Engines
Available 1
Onchain ID
ERC-8004 Sovereign Boundary
Economic action stays governed.
Akasha can reason about economic workflows without receiving unchecked wallet authority.
ERC-8004 Agent Registration + Sovereign Guardrails
Akasha has a verifiable agent identity, while Sovereign and EIGEN separate reasoning, proof, approval, and execution for wallet-adjacent or economic work.
Agent ID 24014
Registry 0x8004A169FB4a3325136EB29fA0ceB6D2e539a432
Network Ethereum Mainnet (eip155:1)
Endpoint https://akasha.ntwrkd.xyz/api/agent-profile
Trust reputation, validation, decision packets
Interaction Surfaces
Visible work, not silent automation.
Akasha moves between conversation, project state, code work, reports, and approval queues.
Dashboard
Operator view, project hub, reports
Telegram
Real-time mission conversation
EIGEN
Scoring, packets, approval queues
API
Programmatic access and webhooks
Work with Akasha.
An operating agent for research, software delivery, learning workflows, grant readiness, growth campaigns, project continuity, and supervised real-world action. Mission-constrained by design.