Recorded case

Engineering that can show its work

TVIJO connects operators, bounded agent work and knowledge that can be checked and reused.

Reviewed 15 October 2026 · scope: implemented

Recorded method and findings

The objective is to reduce coordination overhead while keeping results reviewable. A useful autonomous step has a known owner, a narrow scope, a budget, an acceptance condition and a durable handoff. Routine reversible decisions can be made within those bounds; unknown costs and conflicting ownership stop the affected action.

Recorded method and findings

This wiki distinguishes code, historical runtime checks and future product work. It is a guide to the operating method, not a claim that a complete unattended agent business is already running.

Recorded method and findings

Status labels apply to the specific evidence described here. Verified means that the cited observation or check has a receipt; implemented means that code or an operating method exists. Neither label proves every deployment, a security certification or future results.

Practical checklist

Start with the outcome and the smallest testable task. Use actual receipts to distinguish completed execution from accepted work. Keep operator attention for consequential decisions and unresolved conflicts.

Sources & scope

Swarm coordination implementation specification 2026-10-15
Evidence-based agent review contract 2026-10-14
Economical verifiable automation guide 2026-10-14

Keep exploring

AI orchestration: from a prompt to an accepted resultA practical design for delegation, evidence and recovery.Shared memory without shared mistakesKeep facts, hypotheses and permissions distinct across agent sessions.AGENTORCH: the orchestrator has a concrete jobAGENTORCH names the orchestration role: plan, assign, observe, reconcile and accept.The task packet is the interfaceA good task describes a verifiable outcome rather than an invitation to improvise without limits.AGENTJUDGE: acceptance follows evidenceA reviewer checks the task, the artifact version and each acceptance criterion.Measure cost per accepted resultSmall task benchmarks illustrate why task class and acceptance matter more than a cheap model label.Budgets and outages belong in the state machineA reliable operator view distinguishes working, waiting, failed, blocked and accounting uncertainty.Keep VECTORBASE, evaluate retrievalUse a private source-linked index to find evidence; do not treat search results as authority.SPIDER: evidence collection and useful progressThe first implementation reads an explicit project-evidence list and produces a dated operator digest without model calls.DSHREMBOT and tmux: one operator viewAuthenticated project commands, budget visibility and explicit schedule controls connect the operator to existing execution lanes.The AI worker–Hugging Face incident: learn from controlsThe incident reports support specific engineering lessons, not a controlled ranking of our system.What the supplied AI worker screenshot actually provesThe screenshot records a safeguard-triggered switch in one session; it does not explain the exact trigger. The observation is the supplied screenshot dated 15 October 2026.Training our own model: a gated research directionA proprietary model is an option to test after retrieval, prompts and routing have measurable limits.A bilingual knowledge product with visible limitsPublish useful explanations first, then expand languages when the evidence and workflow are ready.Free learning, custom projects and future challengesTurn evidence-backed engineering into clear offers and a useful developer community.Trust the sender, not a public checksumBind the complete message to an explicitly trusted authority.