We are an AI-native consulting firm for product, program, and operations.

What we are

A consulting firm whose entire roster is AI agents.

CeballosWorks runs as a roster of specialized AI agents. Each agent has an explicit identity, decide-vs-escalate boundaries, a behavioral contract, scoped tool and MCP access, and stated limitations. They handle research, diagnosis, planning, financial modeling, quantitative analysis, change management, contracts, business development, marketing, product strategy, UX and accessibility, engineering, and quality review.

Quality gates are human. The critical-thought layer is human. The agents own throughput.

An AI agent drafts every artifact the firm produces. A human decides and edits anything that carries judgment, recommendation, or commitment.

Accessibility is a named deliverable. Every client-facing interface we design or build gets a UX critique and a WCAG 2.2 AA audit before it ships.

How we operate

Five operating commitments.

1. Human judgment where judgment matters.

   The critical-thought layer is human. Agents draft and execute. Product judgment, architectural decisions, prioritization, escalation, and any commitment to a client clear human review. Routine outputs ship on agent confidence with reviewable artifacts.

2. Every agent ships with a written behavioral contract.

   Identity, decide-vs-escalate boundaries, tool and MCP access scopes, communication style, stated limitations. No agent runs without one.

3. Default to the agent.

   When work arrives, the question is which agent. New work without an agent fit is a signal to design one.

4. Artifacts are the source of truth.

   Every agent reads its own profile plus a shared firm context document at session start. No implicit knowledge. Outputs are reviewable.

5. Automation includes the firm itself.

   The same standard applies to BD, intake, billing, and internal ops. Client delivery is one workstream of many.

The roster

A specialized agent for every lane. Each with its own written persona.

• JordanChief of StaffInternal ops, billing, coordination
• AlexSr. Business AnalystDiagnostic, stakeholder synthesis, root cause
• MorganProgram ManagerCharters, WBS, milestones, risk registers
• RileyFinancial AnalystP&L, pricing, ROI modeling, scenario analysis
• SamChange ManagementStakeholder analysis, adoption playbooks
• CaseyResearch & InsightsIndustry briefings, benchmarks, intel
• DrewClient SuccessOnboarding, deliverable packaging, closeout
• QuinnContracts & ComplianceMSA, SOW, NDA, change orders
• ParkerProduct ManagerPRDs, roadmaps, GTM
• SageTechnology & AI AdvisorReadiness scoring, vendor research
• BlakeBusiness DevelopmentFirm BD and client-facing delivery
• TaylorFull-Stack EngineerBuild, deploy, document
• AveryData & Integration EngineerSchema, ETL, system integration
• ReeseQuality & Review LeadOperational artifact review, six-question checklist, per-client dossier
• DakotaInsights AnalystKPI/SLI/SLO design, AHP weighting, statistical inference
• HarperPrincipal UX DesignerUX critique, information architecture, WCAG 2.2 AA audits
• HaydenGeneral ManagerKPI scorecards, monthly and quarterly business reviews
• FinleyMarketing LeadPositioning, audience, campaigns, launches

See how an agent is written.

How an engagement runs

Five phases. Human judgment at every gate.

1. Pre-Engagement Weeks 1 to 2

   Industry briefing, intake, contracts.

2. Discovery Weeks 2 to 4

   Diagnostic, interviews, current-state, financial baseline, AI readiness.

3. Strategy/Design Weeks 4 to 6

   Program plan, KPI framework, change strategy, tech recommendations, build specs.

4. Execution Weeks 6 to 24+

   Program management, modeling, change comms, build and deploy.

5. Closeout Final 2 weeks

   Deliverable packaging, knowledge transfer, reusable asset capture.

Principal

Contact

Currently scoping select engagements.

Best fit is small and mid-market businesses. AI-native delivery makes deeper diagnostics, faster turnarounds, and more iterations economical at this scale.