Automations & Integrations

AI Agent Strategy & Design

AI Agent Strategy & Design is a solution design engagement that determines which AI agents your business should run, whether HubSpot Breeze agents, custom agents, or both, and designs their scope, context, guardrails, and escalation paths. It is for teams that want agents doing real work with boundaries decided before deployment, not after an incident.

Book discovery callMessage us
PhaseSolution Design
EngagementProject
DisciplineAI & Automation Solution Design

The problem this solves

Agents deployed without design fail in one of two directions. Too little: a prospecting or support agent with no context from your CRM produces generic output the team quietly stops using. Too much: an agent with broad permissions and no escalation design handles a case it should have handed to a human, and trust in the whole program dies with the first bad transcript.

How we work

We start by identifying where agents genuinely fit: processes with volume, repetition, and tolerance for automation, and we map each to HubSpot native agents, such as prospecting and customer-facing support agents, or to a custom build where the process or stack demands it.

Each selected agent then gets a full design: scope in terms of what it may do, must not do, and must escalate; guardrails; escalation triggers with handoff design; and a permission model. Context sources are treated as a first-class design item, because an agent without CRM context generates output that reads like it knows nothing about the recipient.

The rollout design builds trust deliberately: a supervised phase, sampling review, and explicit criteria for widening the agent scope as it proves itself.

Deliverables

  • Agent opportunity map with fit reasoning
  • Per-agent scope definition: allowed, forbidden, escalate
  • Context and data source design per agent
  • Guardrail and escalation specifications
  • Permission model
  • Supervised rollout plan with scope-widening criteria

FAQ

What buyers ask before scoping.

HubSpot Breeze agents or custom agents: how do you choose?

Breeze first where the job matches, such as prospecting or customer support grounded in your knowledge base, because portal-native context and license economics are hard to beat. Custom wins when the process or the stack goes beyond what Breeze covers. We are a HubSpot partner and transparent about that preference; the fit reasoning is written down either way, so you can challenge it.

Our CRM history is thin. Are agents still worth deploying?

Honestly: weak context produces weak agents, and we say so upfront. An agent working from an empty CRM writes messages with no context about the recipient, and your team will notice before your prospects do. Often the right order is to fix data and context first, then deploy. We would rather delay an agent than launch one that embarrasses the program.

What stops an agent from doing something it should not?

Layers, not hope: explicit scope limits, permission boundaries, escalation triggers for defined situations, human review during the supervised phase, and sampling after it. The design assumes errors will happen and makes them cheap, visible, and correctable instead of pretending guardrails eliminate them.

Brief first, scope follows

Sounds like your situation?

30 minutes, your calendar, no slide deck. We tell you honestly whether this module fits.

Book discovery call