LogicLegion

LogicLegion Framework

AI agents are ready to build. Enterprises need proof before they ship.

LogicLegion is the governed control plane for agentic software delivery. It connects agents, repos, tickets, CI, memory, and approvals into one evidence trail where agents can act, but gates decide what advances.

Proof is process and custody, not a promise of model correctness.

The missing layer is verification capacity

Agents can generate, edit, test, and deploy faster than conventional teams can review. Enterprises cannot ship from chat transcripts, screenshots, or model confidence. They need a control plane that turns agent work into evidence-backed state transitions.

LogicLegion starts with evals, traces, policy gates, explicit owners, artifact hashes, and release decisions. The agent is not the trust boundary. The evidence trail is.

Proof is not correctness

Proof means a verifiable evidence trail plus enforced gates: proof of process, custody, and release decision, not proof that a model output is correct.

Model output correctness is measured through evals and review. LogicLegion proof is narrower: what was requested, what changed, what evidence was available, which policy applied, who approved the risk, and what decision was recorded.

  • Requirement-to-proof evidence
  • Versioned policies
  • Artifact hashes
  • Eval and test results
  • Human approvals and overrides
  • Release and rollback decisions

The durable value is the customer's flywheel

LogicLegion is not defensible because orchestration is hard to copy. The durable value compounds in the customer's governed flywheel: proprietary domain data, expert corrections, eval sets, skills, local or hosted models, and deployment locus.

LogicLegion instruments and governs that flywheel. It supplies the evidence, portability, memory promotion, and gate enforcement around it.

The five gates

Strict where failure is expensive. Lightweight where learning is cheap.

SpecifyLockBuildProveShip
GateWhat happens
SpecifyCapture intent, acceptance criteria, non-goals, glossary, and negative constraints.
LockRatify scope through policy, owner review, and manifesto rules.
BuildRoute scoped work to execution nodes such as Codex, Cursor, Hermes, or OpenClaw.
ProveAttach tests, traces, evals, reviews, environment contracts, and requirement-to-proof evidence.
ShipRelease only after the proof ledger records the release decision and known gaps.

Orchestration is deliberately swappable. The durable layer is the evidence and the flywheel.

High-rigor work goes through the tribunal

LatentBuild handles ambiguous tickets, incidents, and multi-repo changes. It runs a six-phase evidence tribunal: read-only discovery and architecture review before implementation, then adversarial review before ship.

1Intake
2Problem discovery
3Intervention design
4Architecture review
5Implementation
6Adversarial review

The tribunal is the high-rigor instantiation of Build + Prove: Intake and Discovery refine Specify, Design and Architecture harden Lock, and Implementation plus Adversarial Review produce the Prove evidence required before Ship.

Open the tribunal

Memory is context, not authority

LogicLegion can use GBrain as the memory substrate and Hermes, OpenClaw, Codex, or Cursor as agent hosts. Retrieved memory can inform work, but it cannot authorize a gate transition.

Agents may propose memory. Durable enterprise knowledge requires source attribution, review, promotion, indexing, expiry, and retirement.

Repo custody starts in dry-run

LatentBuild enrollment plans host setup, repo policy, OpenSpec custody, mission ledgers, preflight checks, agent hosts, and memory providers before anything executes. Standalone mode remains valid; connected modes mark cloud actions as gated events.

ModeCustody surface
StandaloneRepo-local OpenSpec, mission ledger, policy, hooks, and CI preflight
ConnectedLocal custody with LogicLegion policy/context guidance after explicit auth
ManagedCloud-backed policy and evidence metadata with local proof still required
Device loginHost registrationRepo registrationPolicy fetchEvidence upload

The providers are converging on the same controls

The point is not that any one vendor has solved agent reliability. The point is that frontier providers and cloud platforms are independently converging on the same control surface: evals, guardrails, traces, policy gates, tool mediation, and lifecycle governance. The names change; the mechanism does not.

Source familyConvergent control
OpenAIGuardrails, tool mediation, tracing, trace grading, agent evals
AnthropicWorkflows vs agents, simple composable patterns, explicit tool use
GoogleDeployed-agent evaluation workflows
MicrosoftSecurity, observability, governance, lifecycle checkpoints
Meta / open weightsAcceptable-use boundaries, evals, red-teaming
OWASP / OpenTelemetryLLM risk taxonomy, GenAI trace conventions

Trust is computed from evidence, not assigned by marketing

Proof levels are computed from ledger events, artifact hashes, evidence levels, policy versions, and approval records. They degrade when evidence goes stale or policy changes invalidate prior assumptions.

  • Proof ledger
  • Governed memory
  • Controlled execution
  • Risk-adaptive gates
  • Human approval semantics
  • Retention, export, and incident response

Start with one bounded workflow.

Pick work with messy inputs, verifiable outputs, and recoverable failure. Build the proof path once, then reuse it as the paved road for the next workflow.

Start a spec