Ship the company brain behind your AI workers
Turn your company's knowledge, decisions, processes, standards, and memory into the context your AI workers need to understand your business and execute real work. We build and integrate the harness around it: skills, tools, workflows, approvals, and evals to deliver working AI workers for your business.
Operational Audit
Active session
Who I Am
I Design AI Harnesses
My thesis: An agent is only as good as the harness around it. Models will keep changing. The durable advantage is the company brain, designed tools, reusable skills, and evals that let a model do real work reliably - and get better when the next model arrives. I help founders turn that layer into a system they can understand, govern, and continuously improve.
That's what turns raw AI into reliable Operator Agents that run real operational workflows. I built this for my own company first. Now I build it into yours - so your agents operate reliably, not randomly.
Who I Work With
→ Service providers building AI-native client delivery
→ Teams whose automations break from hallucinations and drift
→ Founders burning tokens on unreliable, ungrounded AI
→ Businesses ready to make their agents dependable
Partnership Principles
Organization Design Before Automation
Raw AI hallucinates because it has no grounding. We structure your agent rules and decision trees into a Knowledge System your agents read before they act - so every action is grounded in how your business actually works.
The Layer Between Agents and Tools
Your agents don't touch your tools blindly. The Knowledge System sits in the middle - governing what agents know, decide, and do across CRM, database, email, and Slack. Reliable operations, not guesswork.
Proof, Not Theory
I built this for myself first. Everything I show you, I've tested and validated running my own Operator Agents. This is the exact knowledge layer I run my company on. That's your playbook.
What We Build
Organization Systems We Design
Every organization needs a different operating model for working with AI. We design the systems that connect roles, agents, tools, knowledge, skills, and human decisions - grounded in how your organization creates value and makes decisions.
agent rules Knowledge Base
Your business rules and agent rules structured into a machine-readable knowledge base agents read before every action - no guessing, no drift, no hallucinated steps.
Orchestration Integration Layer
The governed layer between agents, tools, and people. It routes work, controls access, preserves context, and makes every decision observable across your operating stack.
Custom Knowledge Systems
Bespoke knowledge infrastructure designed from the ground up for your operations - proprietary schemas, custom retrieval, and grounding tuned to your specific workflows.
The Thesis
Agents Will Do the Vast Majority of Technical Work
Real AI operations aren't about pretty interfaces. They're about structured knowledge, complex workflows, and integrated systems that let agent swarms execute autonomously. Agents orchestrate themselves. They work in parallel. They scale infinitely. That's how operators compete at 100X speed.
100X
Operational speed
24/7
Autonomous execution
∞
Scalable agents
The Harness Gap
The model isn't the bottleneck. The scaffolding is.
Your agent is only as good as the harness around it. Thin prompts, tool sprawl, and no memory of how your business works mean every session starts from zero. Harness Operations turns model capability into reliable business execution.
No company brain
The model has no durable access to your policies, edge cases, or institutional knowledge. You re-explain context every session.
Tools without design
Integrations get bolted on without thinking through granularity or error handling, so the model picks wrong or gets unusable data back.
Nothing compounds
Every task is solved from scratch. No skills library, no shared procedures, no institutional AI knowledge building over time.
Can't be trusted at scale
No evals, no visibility into why the model decided what it decided. It stays stuck in a toy use case forever.
Raw model vs. engineered harness
Raw AI Agents
Harness-engineered agents
The Solution
Agent = Model + Harness
The models are incredibly capable, but a raw model is trapped without the right environment. We engineer the deterministic scaffolding around it: a company brain, designed tools, reusable skills, and evals that prove the system is working. The model changes. Your harness compounds.
BRAIN → Company knowledge
Structured, current access to your policies, edge cases, and institutional knowledge - so every session does not start from zero.
TOOLS → Designed integrations
MCP integrations and APIs designed around useful granularity, safe actions, clear errors, and the work your business actually needs done.
SKILLS → Reusable procedures
Reusable procedures the model can draw on, so capability compounds instead of every task being solved from scratch.
EVALS → Proof it works
A measurable way to know what the model decided, where it fails, and whether each change actually improves the system.
Your agent is only as good as the harness around it.
Use Cases
Harness Setup Across Your Operating Stack
Human-Agent Teams for Every Function
Every function requires judgment, coordination, and accountable execution. We design human-agent teams around how your organization creates value - connecting the right roles, tools, skills, context, decision rights, and approvals across 12 core functions.
Leadership
Workflows
- › Strategic decision support
- › Board reporting automation
- › Executive dashboards
Real-time operational intelligence across all departments
Product
Workflows
- › Feature request processing
- › Product roadmap automation
- › Release coordination
Agents handle triage, prioritization, and cross-team coordination
Engineering
Workflows
- › Ticket routing & assignment
- › Code review automation
- › Deployment workflows
CI/CD orchestration and intelligent task distribution
Design
Workflows
- › Design feedback collection
- › Asset management
- › Design system maintenance
Automated design reviews and component documentation
Marketing
Workflows
- › Campaign automation
- › Lead nurturing sequences
- › Content calendar management
Agentic landing pages + automated customer engagement
Sales
Workflows
- › Lead qualification agents
- › Deal pipeline automation
- › Sales forecasting
Agentic revenue operations - qualify leads, close deals 24/7
Customer Success
Workflows
- › Customer onboarding agents
- › Health score automation
- › Churn prevention workflows
Proactive customer intelligence and automated support
Support
Workflows
- › Ticket routing intelligence
- › FAQ automation
- › Escalation workflows
AI agents as first responders, intelligent escalation
Operations
Workflows
- › Process optimization
- › Vendor management
- › Compliance tracking
Agents automate operational procedures and rule-based tasks
Finance
Workflows
- › Invoice processing
- › Expense automation
- › Financial reporting
Agentic accounting - agents handle data entry, reconciliation, analysis
People Ops
Workflows
- › Recruitment automation
- › Onboarding agents
- › Compliance workflows
Agentic HR - agents handle hiring, learning, payroll coordination
Agent Ops
Workflows
- › Agent swarm orchestration
- › Performance monitoring
- › Workflow optimization
Monitor and optimize your entire agent infrastructure
Every engagement needs coordination. Every agent needs a role.
Harness Operations works when every agent has the context, tools, skills, and guardrails it needs to do useful work. That is how model capability becomes a dependable operating layer across the business.
Start with one delivery workflow. Orchestrate the system around every engagement.
Get the Free AI Worker OS →Harness Operations
The right AI worker for where the work lives
Each worker is built around a real job, connected to the company brain, and delivered with a workspace your team can use to manage context, tools, skills, approvals, and results. Start at $2k per worker.
Internal AI Worker
For teams that need one useful AI worker inside support, research, internal operations, or another workflow.
Audit of current AI usage
Company brain + designed tool layer
Reusable skills and procedures
Basic evals to prove it is better
From $2k per department function
Workspace setup included
External AI Worker
For businesses that need an AI worker to handle customer conversations, requests, research, or service delivery outside the internal team.
Customer-facing workflow design
Company brain and approved knowledge
Designed tools, skills, and guardrails
Human handoff and escalation paths
Evals for quality and safety
From $2k per department function
Workspace setup included
Embedded AI Worker
For AI-native companies that need a custom worker built into their own product, owned outright, and ready to run on their infrastructure.
Custom-built, model-agnostic harness
Full orchestration and guardrails
Company brain, tools, skills, and evals
Yours to run on any infrastructure
Custom scope, starting at $50k
Workspace setup and handoff
You are not buying another prompt. You are getting a working AI worker, the workspace around it, and a foundation that can grow as your team adds more workflows.
AI Worker Workspace
Harness Operations Workspaces
A shared workspace where your team manages the company brain, AI workers, tools, skills, approvals, and results in one place.
Conversational Workspaces
Natural language interfaces that let your team query, route, and act on operational data without switching tools.
AI Command Centers
Unified operational dashboards with real-time delivery status, agent activity logs, and workflow intelligence.
Operational Memory Layers
AI systems that retain context across sessions, team members, and projects - building institutional intelligence.
Agentic Environments
Developer-grade AI environments with MCP systems, ACP integrations, and custom agent tooling built in.
24
Active Workflows
7
AI Agents Online
183
Tasks Automated
Delivery Pipelines
Recent Agent Activity
Orchestration Infrastructure
The Infrastructure That Makes Agent Teams Work
Knowledge is built into the orchestration system - not kept apart as a static repository. We connect agents, MCP tools, skills, memory, approvals, and observability into one operating layer that coordinates client delivery safely and predictably. Your agents know what to do, which tools to use, when to collaborate, and when a person needs to decide.
50+
Tool integrations
12+
AI models supported
100%
Grounded agents
0
Hallucinations
Protocol Layers
Knowledge Infrastructure Protocols
Model Context Protocol
The infrastructure layer that connects AI models to your operational data, tools, and systems. We build MCP servers that give your agents access to everything they need to operate.
Agent-to-Agent Protocol
The coordination layer that enables multi-agent workflows. A2A infrastructure allows your AI agents to communicate, delegate tasks, and collaborate across complex operational environments.
Universal Commerce Protocol
The commerce layer that enables agents to understand and execute transaction workflows. UCP systems allow agents to process orders, manage inventory, and handle commerce operations autonomously.
Agent Payments Protocol
The fintech layer that enables autonomous payment execution and financial workflows. AP2 allows agents to validate payments, process transfers, and manage financial operations securely.
Agent Development Kit
The development layer that gives you tools to build, deploy, and manage custom agents. ADK provides SDKs, frameworks, and utilities for rapid agent development and integration.
AI Models & Dev Tools We Integrate
Operational Tools We Connect
Knowledge System Layer
agent rules · Guardrails · Governance · Grounding
What We Build
Your first AI worker, built around your workflow
AI Worker Build
Core offerA tightly scoped first worker designed around one workflow, one model environment, and the business context it needs to execute reliably.
Conversational Operational Interfaces
InterfaceNatural language layers over your business operations - query, act, and route without leaving the conversation.
Custom AI Worker Systems
Custom buildExtend the first worker with the company brain, designed tools, reusable skills, workflow orchestration, and human approval where it matters.
Harness Engineering Services
Dev EnvironmentDeveloper environments configured for agentic workflows, durable execution, evaluations, tool use, and MCP systems.
Harness Setup
WorkflowConfigure the instructions, skills, MCP tools, routing logic, approvals, and observability that let a model operate at its actual ceiling.
AI Knowledge & SOP Infrastructure
KnowledgeLiving operational knowledge bases that AI agents actively maintain, surface, and enforce across your team.
AI-Enabled Work Allocation Systems
DeliveryIntelligent project coordination that tracks, routes, and escalates delivery milestones via AI agents.
MCP Tooling & Agent Infrastructure
InfrastructureLow-level infrastructure for AI agent communication, context sharing, and tool access.
Operational AI Command Centers
Command CenterCentralized dashboards that surface operational intelligence across every workflow, team, and system.
AI Workflow Automation
AutomationReplace manual operational work with AI-driven automation that learns and adapts over time.
Harness Audit & Roadmap
ConsultingFind the gaps keeping your agents at 20%: missing context, weak tool access, brittle prompts, unclear feedback, and model-specific dependencies.
AI Memory & Context Systems
MemoryPersistent memory infrastructure that gives AI agents long-term context about your business, team, and operations.
Our Process
How We Ship Your First AI Worker
We start with the work, not the worker. You bring us a workflow worth handling; we determine the harness required and ship a tightly scoped first version you can use, test, and improve.
Harness Audit
Start hereWe map the models, prompts, context, tools, workflows, and human handoffs already in place. Then we identify the gaps keeping performance below its ceiling.
Architecture Design
BlueprintWe design the stable operating layer: context and memory, instructions, skills, MCP tools, action boundaries, routing, and feedback loops.
Custom Harness Setup
BuildWe build and connect the harness around your model stack, giving agents the right information, capabilities, and constraints to do real work.
Test & Govern
ValidateWe evaluate task performance, failure modes, permissions, approvals, and observability before the harness becomes part of daily operations.
Harness Operations
OngoingWe monitor outcomes, learn from corrections, tune the system, and expand capabilities as your business and model stack evolve.
Why We're Different
We Engineer Harnesses, Not Just Prompts
Most AI agencies add surface-level automations to existing structures. We engineer the environment around the model: the company brain, tool pipelines, reusable skills, orchestration, guardrails, and evals that make AI part of how the business actually works.
Get the Free AI Worker OS →
Book a 30-minute audit call. We'll show you exactly where your current setup is leaving capability on the table.
Community
Follow the Journey
We explore AI-Native Organization Design in public - how roles, workflows, decision rights, tools, and human-agent collaboration reshape the way organizations operate.
X / Twitter
@aiagentship
Knowledge Systems, grounded agents, and reliable operations. Building in public.
AI Agentship
Knowledge system architectures and agent operations insights.
GitHub
aiagentship
Knowledge system SDKs, MCP servers, and agent frameworks.
YouTube
AI Agentship
Knowledge system architecture and grounded agent operations.
Tech Stack
Built on Proven Foundations
We design AI-native operating models on top of your existing stack - connecting tools, knowledge, governance, and orchestration without forcing a wholesale replacement.
FAQ
Common Questions
What is an AI worker build?
It is a tightly scoped implementation of one AI worker for one primary workflow. We build the harness around the model - company context, knowledge, tools, skills, approvals, testing, documentation, and handoff.
Why build a harness instead of hard-coding to a model?
Models keep upgrading. A brittle integration breaks when the model changes; a durable harness lets you swap in a stronger model while preserving the context, tools, skills, and workflows your business already built.
Who needs an AI worker?
Teams with a repeatable workflow that consumes time, requires judgment, and could be handled better with the right company context, tools, skills, and human approval.
What goes into an AI worker build?
One primary workflow, one model environment, company knowledge and context, a limited number of tool or MCP integrations, reusable skills, human approval where needed, testing, documentation, and handoff.
How does MCP fit into the system?
MCP gives agents structured access to the tools and data they need. We design how those capabilities fit into the organization’s operating model, with permission boundaries and governance so access is purposeful, auditable, and safe.
Do humans remain involved?
Yes. Human-in-the-loop governance is designed into the workflow. Agents can move work forward within defined boundaries, while people set direction, review consequential decisions, resolve exceptions, and maintain accountability for organizational outcomes.
Can you work with our existing tools?
Yes. We orchestrate across your current stack - CRMs, project management, communication, documents, databases, and internal systems - using MCP and APIs where appropriate. The goal is to coordinate your tools, not force a wholesale replacement.
How do you make orchestrated agents reliable?
We map the delivery system, define agent responsibilities, encode organizational knowledge into the workflow, add guardrails and approval points, then evaluate and observe the system in production. Reliability comes from the architecture around the models - not from prompts alone.
How long does an orchestration engagement take?
We begin with a focused mapping and architecture phase, then build and test the highest-value delivery workflows first. Scope depends on your service model, tool ecosystem, and the number of agent roles involved.
Start the conversation
Get the Free AI Worker OS →
Bring us the workflow you want handled. We'll help identify the right first AI worker and the harness required to make it useful.
Get the Free AI Worker OS →
Bring us the workflow you want handled. We'll scope a first AI worker and tell you what harness it needs to work reliably.
Inside Harness Operations
Agent orchestration architectures
See how agent teams coordinate real client work
MCP & governance blueprints
Copy-paste grounded agent patterns
Weekly Q&A sessions
Direct access to me. Real questions. Real answers.
Resources on grounded agent operations
Everything you need to scale agents reliably
Why This Matters
Organization design is the foundation of an AI-native company
Becoming AI-native requires more than prompts and isolated automations. We redesign the operating model that coordinates people, agents, tools, knowledge, workflows, and decisions around the work your organization actually does.