
Services · Agent Management
Agent Management.
Agents break. Rarely loudly. Almost always expensively. We run the monitoring, the evals, and the maintenance so your agents stay useful for years, not weeks.
The hard part of agents isn't building them. It's keeping them working.
A model update changes behavior. A prompt drift corrupts outputs. An API deprecation silently fails. Most teams notice weeks later, after the damage. Agent management means owning the whole lifecycle: build, deploy, monitor, iterate, retire.
- Agent design and task scoping
- Build using Claude, OpenAI, or local models
- Eval suites that catch regressions
- Observability and error tracking
- Scheduled retraining and prompt updates
- Monthly reliability and usage reports
What you walk away with
- Agents that stay on-task, not just on-line
- Early warning when model behavior drifts
- Measurable ROI, not vibes-based hype
- A team freed from babysitting the bots
Build the agent once. Keep it running forever.
See it working
Live demos tied to this service.
Type a prompt, watch a real system run. These are the same patterns we'd install for you.
Wiring it all together
Workflow Builder
Drag blocks onto a canvas. Chain them into an automation. Hit run and watch AI execute every step, live.
See it liveRecruiting
Hire Copilot
Paste a JD + a resume. Get a culture-fit score, structured interview questions, and outreach draft.
See it liveStaying top-of-mind
Social Content Engine
Drop in your site, LinkedIn, and Facebook. Get a brand voice, a 14-day calendar, and three on-brand images. Live.
See it liveTechnology development
Dashboard in 60 Seconds
Type your title + industry. We pick the six KPIs you should actually be watching, and flag the two you almost certainly aren't.
See it liveCommon questions
What people ask before they book.
The hard part of agents isn't building them. It's keeping them working.
A model update changes behavior. A prompt drift corrupts outputs. An API deprecation silently fails. Most teams notice weeks later, after the damage. Agent management means owning the whole lifecycle: build, deploy, monitor, iterate, retire.
What does Agent Management from Create A Legacy include?
Agent design and task scoping. Build using Claude, OpenAI, or local models. Eval suites that catch regressions. Observability and error tracking. Scheduled retraining and prompt updates. Monthly reliability and usage reports.
What results can I expect from Agent Management?
Agents that stay on-task, not just on-line. Early warning when model behavior drifts. Measurable ROI, not vibes-based hype. A team freed from babysitting the bots.
Who is Agent Management designed for?
Agent Management from Create A Legacy is designed for business owners, founders, and operators who want measurable results without long ramp-up times. We work with solopreneurs, small businesses, growth companies, and organizations across the United States.
What does ongoing AI agent management include?
Agent management covers the full lifecycle after launch: monitoring for behavioral drift, eval suites that catch regressions when model providers update, prompt optimization, API deprecation handling, usage reporting, and scheduled retraining. Most teams notice when an agent breaks weeks after the damage — we catch it the same day.
How do you know when an AI agent is underperforming?
We build eval suites specific to each agent's task that run on a schedule. These compare current outputs against a known-good baseline. Combined with real-time observability into error rates and output quality, we can detect drift before it affects your business.
From the Legacy Lab
Further reading on agent management.
recipe
AI Tool Selection: How to Build the Right AI Stack
Most AI tool waste comes from buying before mapping the workflow. A four-layer selection framework for operations leaders who want a stack the team actually uses.
Readrecipe
AI Change Management: A 90-Day Team Adoption Plan
AI tools fail when teams quietly work around them. A 90-day adoption and training framework for operations leaders: pilot, champion, then systematize.
Readteardown
Why Most AI Implementations Fail: A DFW Business Teardown
Most AI projects stall somewhere between the demo and the real week. Here are the failure patterns we see most, the foundation layers underneath them, and the operational fix.
ReadAnswer a few quick questions and see where your business is losing time and revenue. If there's a fit, we'll book a Friction Assessment.
