GITLAI
SHEET 01 · AGENTSEMPLOYED.AI
GET IN THE LOOP AI · OMAHA, NEBRASKA
A working drawing, not a brochure

Software is installed.
Agents are employed.

GITLAI puts AI agents to work the way you'd put a person to work: a written job description, a named supervisor, guardrails, a scoreboard, and a test built from the job description, signed before anything gets built.

And the solution is not always an agent. We use agents to find the problem before deciding whether an agent is the solution.

01 · The difference

Stop installing. Start employing.

Legacy software · the installation era

Nature: a spreadsheet sits still until someone opens it.
Action: installed, configured, clicked.
Relationship: a tool your people operate.
Governance: hand them a login and hope.

AI agents · the employment era

Nature: reads, decides, answers, escalates, acts. In your name.
Action: managed, supervised, directed.
Relationship: a worker your people manage.
Governance: write the job, name a manager, set limits, check the work.
02 · The method

The job description comes first

Write
The job description: duties, exclusions, access, supervisor, scoreboard, guardrails.
Test
A test built from the job description, signed before the build. If it's in the job, there's a trap for it in the test.
Review
A named supervisor checks the work. Every action logged. Agents get performance reviews too.
Revise
Corrections fold back into the job description. The capability compounds.

Rules, heuristics, AI, and human judgment. Each where it belongs.

roledutiessystems accessresumeknowledge + the gap rulea named supervisorthree listsscoreboardguardrailssign-off

The ten parts of an agent job description · The Job Description Comes First, GITLAI whitepaper, 2026

03 · Why now

The machines got good faster than organizations learned to employ them

THE GAP
77.3%
Agent task success in real-world tasks
Up from 20% a year earlier. Corporate AI investment reached $581.7B in 2025.
Source: Stanford HAI, The 2026 AI Index Report, April 2026
~30%
Organizations at basic maturity in AI governance and controls
Nearly 60% name knowledge and training gaps as the biggest barrier.
Source: McKinsey, The state of AI trust in 2026, March 2026
7%
PE portfolio companies running AI at enterprise scale
Talent is the most-cited constraint.
Source: FTI Consulting, 2026 Private Equity AI Radar, May 2026

The engines work. The employment discipline is what's missing, and it can't be bought off a shelf. The engine is a commodity. The job description is the asset.

04 · Where to start

Start with Phase One

Phase One is focused and short. We learn from the people who run the business, map the data and the key-person risk, and diagnose before we prescribe. Then we build the proof with your team: the first agent's job description or an AI-enabled build when the work calls for it, tested in your environment, with a sequenced roadmap your team can execute, with or without us.

The real deliverable is capability that stays after we leave.

Jason Gilbreath, Managing Principal & Founder, GITLAI, LLC
jrgilb1@gmail.com · getintheloop.ai · jasongilbreath.com

Phase One

  • Fixed fee. Priced as one step, agreed before we start.
  • Weeks, not quarters. A checkpoint, not a commitment.
  • Working proof in your environment. On your systems, your data, your team.
  • You keep everything either way. Job descriptions, tests, roadmap: yours.
Start with Phase One
GITLAI — because your team belongs in the loop.