Your team is lean.
Your workload is not.

01 / Field Observation

The work scaled before the system did.

Small teams can run for a long time on memory, inboxes, documents, dashboards, and one person who knows how everything actually works. Then the work gets heavier. The informal system starts to leak.

not just busy. under-instrumented.

Symptoms

• The same questions keep getting answered by the same person.
• Follow-up depends on memory instead of a system.
• A new hire sounds urgent, but the job is still fuzzy.

Common misread

Looks like: We need another person right now.

May be: The workflow is undefined, manual, or trapped in one person's context.

First check: Which parts repeat, which parts require judgment, and which resources already exist?

context bottleneck

this is where the pain becomes a hiring conversation

Before you hire around the bottleneck, inspect the work.

02 / Intervention

Find the right intervention before you build.

Aboriginal Armadillo starts with the work: the people, tools, examples, handoffs, and decisions already in play. Sometimes the right answer is an AI agent. Sometimes it is software, documentation, a workflow change, an existing product, a hire, or nothing at all.

Useful intervention: The smallest practical change that reduces effort in a real workflow.

Custom agents can help with

• Demand Validation
• Landing Page Scaffolding And QA
• Grant Matching Agent
• And more

It should not replace professional judgment, approve risky actions without review, or pretend physical-world work is software.

The goal is not to sell AI. The goal is to reduce operational friction.

03 / Field Procedure

Start with one workflow.

You do not need a finished AI strategy. The first step is a no-cost 20-30 minute call about one workflow that is slow, manual, unclear, or too dependent on one person.

free call first

1. Free fit call

   We learn who you are, what workflow is stuck, and whether there is a real opportunity to inspect.

2. Workflow Assessment

   If there is a fit, we map the workflow, identify bottlenecks, and recommend one next step.

3. Build only if justified

   If custom work is the right answer, we scope a fixed build with clear deliverables and acceptance criteria.

4. Operate and improve

   Once live, support covers hosting, monitoring, updates, bug fixes, model changes, and workflow adjustments.

not everything should become an agent

assess before build

04 / Evidence Drawer

Records from the workshop.

Agent records and artifacts from the workbench.

Built patterns

Agent Catalog

View catalog

Prior work

Artifacts

Open artifacts

Working lessons

Field Notes

Practical observations from building agents, workflows, and small operating systems.Read notes

Selected records

• Do Not Hire Around a Broken Workflow - Why hiring pressure often points to undefined work, not only missing headcount.
• Demand Validation - A weekly demand signal brief for one offer or segment.
• The Workflow Is the Product - Why useful agent work is the system around the model call.
• AgentLabUI / Gofannon - Open-source tooling for turning agent workflows into usable applications.
• Kubeflow for Machine Learning - Production ML systems experience, from lab to deployment.