Glossary hub
AI Agent Glossary
The DH79 glossary explains terms buyers are likely to meet when choosing managed AI agents, including multi-agent systems, retrieval-augmented generation, human-in-the-loop AI, approval gates, least-privilege access, agent orchestration, AI workspaces and prompt injection. Each definition explains why the term matters in a business setup.
Who this is for
- Founders who want clear definitions before approving an AI project.
- Teams reviewing safety, access and workflow terms.
- Buyers comparing provider language and promises.
Why this matters
AI terminology can make simple operational decisions feel more complicated than they are. A glossary helps buyers understand the controls and architecture without getting lost in vendor language. The important test is whether the work is frequent enough, valuable enough and controlled enough for an agent to help without hiding risk. DH79 starts with a narrow workflow because useful agents need clear inputs, clear outputs and a named human owner.
Example workflow
Read the glossary definitions when a term affects access, safety, cost, scope or ownership, then follow the related service and safety links. The workflow is designed so the agent prepares, drafts, summarises or monitors, while a human remains responsible for approval where judgement, reputation, compliance or customer trust is involved.
What DH79 sets up
- Plain-English definitions.
- Business examples and risks.
- Links into safety and implementation pages.
- CTA route for turning definitions into a scoped plan.
How this appears in a DH79 setup
- Define agent architecture terms.
- Explain human review and access-control language.
- Clarify workflow and memory concepts.
- Help buyers ask better provider questions.
What tools they can connect to
- Gmail, Outlook and shared inboxes
- Google Workspace, Microsoft 365, Notion, Drive and SharePoint
- HubSpot, Pipedrive, Salesforce or lightweight CRM systems
- Slack, Teams, calendars, task tools and internal knowledge bases
- Website CMS, spreadsheets, forms and reporting dashboards where access is scoped
What stays human
- Interpreting risk for the business.
- Approving access and permissions.
- Choosing how definitions apply to a workflow.
DH79 deliberately avoids promising fully autonomous business judgement. The safest commercial gains usually come from agents preparing the work, making gaps visible and giving humans better drafts, summaries and reminders.
First 30 days
- Clarify terms used in the first workflow.
- Map terms to practical controls.
- Use safety pages before granting access.
- Review with DH79 during the workflow audit.
Safety and GDPR-aware controls
- Treat security terms as operating decisions, not decoration.
- Use least-privilege access from the start.
- Keep approval gates explicit.
- Define prompt-injection and data-boundary risks before connecting tools.
Pricing and scope
DH79's managed package starts from £5,000/month inside an agreed operating scope. Work that needs unusual volume, specialist integrations or regulated review is scoped before launch so costs and responsibilities are clear.
How to judge whether this should be your first agent
A good first agent is not the most exciting idea in the business. It is the workflow with clear inputs, repeatable steps, visible mistakes and a human owner who can approve the output. For ai agent glossary, DH79 looks for a task where the agent can define agent architecture terms, connect only to gmail, outlook and shared inboxes, and leave interpreting risk for the business with a person. That makes the pilot easier to measure and safer to improve.
- Bring two or three real examples of the current workflow, including a strong example and a messy edge case.
- Decide who owns approval, who receives the draft or summary, and what would count as a useful first-month result.
- Start with a draft, research, preparation, triage or monitoring task before allowing any agent to take external action.
FAQs
Can DH79 set up ai agent glossary without our team managing prompts?
Yes. DH79 maps the workflow, builds the agent instructions and private workspace, connects the agreed tools, sets approval rules, monitors usage and improves the system. Your team should understand the operating rules, but it should not have to manage tokens, hosting or prompt maintenance.
What should stay under human approval?
External messages, legal or financial commitments, sensitive client communication, medical or regulated judgement, unusual edge cases and anything that could affect reputation should remain human reviewed unless a narrower approval policy is agreed.
How quickly can the first workflow go live?
A narrow first workflow is normally designed during the first month. The first 30 days focus on workflow audit, data and tool access, agent build, controlled testing, team feedback and a decision on what to improve or add next.
How does DH79 reduce risk?
DH79 uses scoped permissions, least-privilege access, human approval gates, logs, draft-only modes for sensitive work, clear escalation rules and monthly review. The aim is useful operational leverage without handing important judgement to an unsupervised system.
Is this suitable for business owners who need plain-english ai agent definitions?
It is most suitable when business owners who need plain-english ai agent definitions have repeatable research, drafting, preparation, follow-up, admin or monitoring work and want a managed service rather than a DIY platform. If the first use case is too vague, DH79 starts by narrowing it into a controlled pilot.
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