Lab operating system

The lab runs on the systems it builds.

Redditech Labs uses OpenClaw as an agentic operating system for research, development, QA, publishing, and operations. This page describes the public shape of that system without exposing private memory, credentials, or client-sensitive configuration.

Operating claim

Redditech Labs does not only advise on AI workflows. It operates an internal agent workflow daily, logs failures and postmortems, and turns the lessons into shipped software, public research, and reusable playbooks.

Operating loop

01

Brief

02

Agents

03

Build/QA

04

Evidence

05

Human gate

06

Publish

Specialist agents

Research, build, QA, writing, operations, video, cost analysis, planning, and synthesis are split across named agents with durable charters.

LokiKitArchieSaraOliBelleLivBeckyFinnQuillFireflyQuinnMilton

Memory and continuity

Project STATUS files, daily logs, searchable memory, and resume protocols keep work from evaporating when sessions restart.

STATUS.mddaily memoryQMD/vector searchproject resume protocol

Evaluation and routing

The Hybrid Control Plane tests local and cloud models by task type, uses gates to inform routing decisions, and keeps model selection empirical.

promotion gatesLLM-as-judgetask-specific routinglocal/cloud split

Observability and budgets

Telemetry, spend tracking, watchdogs, health checks, and postmortems make the agent system auditable instead of magical.

Langfusewatchdogsspend trackinghealth checks

Human gates

External actions, publishing, credentials, spending, sensitive claims, and destructive operations stay approval-bound.

publishing approvalcredential boundariesclaim reviewsdestructive-action guardrails
Trust boundary

Human gates stay explicit.

Agents can draft, build, test, review, package, and monitor. Humans still approve external publication, spend, credentials, sensitive claims, client boundaries, destructive operations, and anything that changes someone else's system.

What we disclose

Public proof, bounded claims.

Artifacts beat anecdotes: every serious claim needs a page, repo, video, benchmark, or postmortem.

Agents need process, memory, and accountability more than clever prompts.

Local models are promoted by measured task fit, not brand preference.

Sensitive details stay private; public pages show architecture and evidence, not secrets.

Inspect the proof, then the work.