HEFESTO
Multi-Agent Harness Engineering
Engineering Reliable Multi-Agent Systems through Harnesses, Runtimes, Governance and Control Planes
$200
Mission and vision
Mission
Train engineers to design the system that controls the agents: harnesses, runtimes, governance, and a control plane on paper — governable, verifiable, observable, reproducible.
Vision
A Governed Multi-Agent Harness System that separates ROLE, MODEL, HARNESS, PROVIDER, TOOLS, STATE, POLICY, and EVIDENCE, and that does not add agents by default.
Why HEFESTO
HEFESTO studies the engineering required to turn one or more AI models into governable, verifiable, observable, and reproducible agentic systems. It does not teach prompt writing, and it does not stop at creating an agent. The object of study is the system that controls the agents.
Holding the model fixed and changing the harness can change performance materially. The result still depends on Model × Harness, not on either one in isolation.
Who it is for
AI engineers, agentic-systems engineers, software and platform architects, ML / MLOps / LLMOps engineers, coding-agent developers, and technical leads who must govern multiple models and providers. Prior multi-agent experience is not required. Python or Go, Git, APIs/CLIs, basic LLMs, and tool calling are.
What it is not
Not Kratos core. Module IX designs a minimal control plane on paper. Seal, seats, receipt, and `/start` stay in Kratos / bridle. Labs are your repo.
What you'll be able to do
- Design a Governed Multi-Agent Harness System that does not collapse ROLE, MODEL, HARNESS, PROVIDER, TOOLS, STATE, POLICY, EVIDENCE
- Decide Single Agent vs Multi-Agent vs Multi-Harness without assuming more agents are better
- Run a harness-swap experiment with model and task held constant
- Separate verification from production, and refuse correlated-failure folklore
- Design a minimal control plane on paper — without teaching the Kratos product
Course content
Phase 1 — HARNESS
Module 1 — From Model to Agent System
Module 2 — Harness Anatomy
Phase 2 — CONTEXT
Module 3 — Context Engineering for Agents
Phase 3 — ROLES
Module 4 — Role Engineering & Capability Scoping
Phase 4 — MULTI-AGENT
Module 5 — Single-Agent vs Multi-Agent
Module 6 — Multi-Agent Orchestration & Coordination
Phase 5 — VERIFICATION & FAILURE
Module 7 — Verification Engineering
Phase 6 — MULTI-HARNESS
Module 8 — Multi-Harness Systems & Adapter Architecture
Phase 7 — CONTROL PLANE
Module 9 — Minimal Agent Control Plane & Governance Engine
Phase 1 · Module 1: From Model to Agent System (6 components + Lab L1) · Module 2: Harness Anatomy (6 components + Lab L2). Phase 2 · Module 3: Context Engineering for Agents (6 components + Lab L3). Phase 3 · Module 4: Role Engineering & Capability Scoping (6 components + Lab L5). Phase 4 · Module 5: Single-Agent vs Multi-Agent (6 components + Lab L4) · Module 6: Multi-Agent Orchestration & Coordination (6 components + Lab L6). Phase 5 · Module 7: Verification Engineering (6 components + Lab L7). Phase 6 · Module 8: Multi-Harness Systems & Adapter Architecture (6 components + Lab L8). Phase 7 · Module 9: Minimal Agent Control Plane & Governance Engine (6 components + Lab L9).
Instructor
Elmer Niño
Founder, VTAlgo Group · Systems Engineer · MSc in Computer Science
Algorithmic trader since 2008, running trading as an enterprise. HEFESTO is harness engineering: the system that controls the agents — not another agent, and not the Kratos product.
HEFESTO
Multi-Agent Harness Engineering
Ingeniería de sistemas multi-agente fiables mediante harnesses, runtimes, gobernanza y planos de control
$200
Misión y visión
Misión
Formar ingenieros para diseñar el sistema que controla a los agentes: harnesses, runtimes, gobernanza y un plano de control en papel — gobernable, verificable, observable, reproducible.
Visión
Un Governed Multi-Agent Harness System que separa ROLE, MODEL, HARNESS, PROVIDER, TOOLS, STATE, POLICY y EVIDENCE, y que no añade agentes por defecto.
Por qué HEFESTO
HEFESTO estudia la ingeniería necesaria para convertir uno o varios modelos de IA en sistemas agentivos gobernables, verificables, observables y reproducibles. No enseña a escribir prompts, y no se detiene en crear un agente. El objeto de estudio es el sistema que controla a los agentes.
Mantener el modelo fijo y cambiar el harness puede modificar materialmente el rendimiento. El resultado sigue dependiendo de Model × Harness, no de uno de los dos aisladamente.
A quién va dirigido
AI engineers, ingenieros de sistemas agentivos, arquitectos de software y de plataforma, ingenieros ML / MLOps / LLMOps, desarrolladores de coding agents y technical leads que deban gobernar múltiples modelos y proveedores. No se exige experiencia previa en sistemas multi-agent. Sí Python o Go, Git, APIs/CLI, LLMs básicos y tool calling.
Qué no es
No es Kratos core. El Módulo IX diseña un plano de control mínimo en papel. Sello, asientos, receipt y `/start` quedan en Kratos / bridle. Los labs son tu repo.
Lo que vas a poder hacer
- Diseñar un Governed Multi-Agent Harness System que no colapse ROLE, MODEL, HARNESS, PROVIDER, TOOLS, STATE, POLICY, EVIDENCE
- Decidir Single Agent vs Multi-Agent vs Multi-Harness sin asumir que más agentes es mejor
- Correr un experimento de harness-swap con modelo y tarea fijos
- Separar verificación de producción, y rechazar el folklore de fallos independientes
- Diseñar un plano de control mínimo en papel — sin enseñar el producto Kratos
Contenido del curso
Phase 1 — HARNESS
Module 1 — From Model to Agent System
Module 2 — Harness Anatomy
Phase 2 — CONTEXT
Module 3 — Context Engineering for Agents
Phase 3 — ROLES
Module 4 — Role Engineering & Capability Scoping
Phase 4 — MULTI-AGENT
Module 5 — Single-Agent vs Multi-Agent
Module 6 — Multi-Agent Orchestration & Coordination
Phase 5 — VERIFICATION & FAILURE
Module 7 — Verification Engineering
Phase 6 — MULTI-HARNESS
Module 8 — Multi-Harness Systems & Adapter Architecture
Phase 7 — CONTROL PLANE
Module 9 — Minimal Agent Control Plane & Governance Engine
Phase 1 · Module 1: From Model to Agent System (6 components + Lab L1) · Module 2: Harness Anatomy (6 components + Lab L2). Phase 2 · Module 3: Context Engineering for Agents (6 components + Lab L3). Phase 3 · Module 4: Role Engineering & Capability Scoping (6 components + Lab L5). Phase 4 · Module 5: Single-Agent vs Multi-Agent (6 components + Lab L4) · Module 6: Multi-Agent Orchestration & Coordination (6 components + Lab L6). Phase 5 · Module 7: Verification Engineering (6 components + Lab L7). Phase 6 · Module 8: Multi-Harness Systems & Adapter Architecture (6 components + Lab L8). Phase 7 · Module 9: Minimal Agent Control Plane & Governance Engine (6 components + Lab L9).
Instructor
Elmer Niño
Fundador, VTAlgo Group · Ingeniero de Sistemas · MSc en Ciencias de la Computación
Trader algorítmico desde 2008, que lleva el trading como una empresa. HEFESTO es ingeniería de harness: el sistema que controla a los agentes — no otro agente, y no el producto Kratos.