Engagement length
Usually starts with a narrow pilot, then moves into monthly operation if the workflow proves useful.
commercial AI agents · for the humans running agents
AI agent operations for real business work
An AI agent operator is the person or function responsible for safely running agent infrastructure: deciding what gets delegated, supervising outputs, approving risky actions, and improving the system over time.
Tessera helps founders and operators turn that role into a practical operating model: scoped workflows, bounded tools, visible logs, human approval gates, and measurable commercial outcomes. The result is useful AI leverage without pretending the agent is an employee.
Buying question
Can this keep running with accountability after launch?
You are not looking for another AI demo. You are looking for a way to operate agents responsibly: what can be delegated, where humans stay in control, what tools an agent may touch, and how performance is measured.
Tessera starts with one high-value workflow, builds the operating boundary, deploys the agent system, and keeps it observable so the human operator can trust it before it expands.
Fit guidance
You probably need this if…
- You are the founder, operator, or technical lead expected to make AI agents useful inside the business.
- You already have recurring workflows that keep falling between people, tools, or meetings and need a supervised agent layer.
- You need the system to keep running after launch, with logs, escalation, and someone accountable for improvements.
You probably do not need this if…
- You only want a chatbot embedded on a website or Slack channel.
- The workflow is rare, ambiguous, and politically sensitive enough that it still needs human ownership end to end.
- You are not ready to give a system scoped access to the tools or source material it needs to operate.
What you get
Starting point
One bounded workflow with clear triggers, tools, decisions, and failure modes.
Client involvement
Weekly operator review, access approvals, and fast feedback on exceptions while the agent system earns trust.
Output
A working agent workflow with logs, escalation rules, improvement backlog, and a clear human operating rhythm.
Use cases
Delivery coordination
Use agents to track tasks, read project updates, identify blockers, draft client-ready summaries, and keep delivery moving without manual status archaeology.
Research and synthesis
Turn messy source material into structured decisions, reports, competitive intelligence, and implementation briefs your team can act on.
Revenue operations
Monitor leads, follow-ups, quotes, invoices, and client opportunities so commercial work does not disappear under busywork.
Technical operations
Watch logs, triage alerts, create implementation tasks, and hand off scoped fixes to developers or coding agents with useful context.
Content operations
Convert product knowledge, case studies, and research into drafts, internal links, metadata, and distribution assets.
Executive assistance
Maintain context across email, calendar, notes, tasks, and decisions without forcing leaders to become prompt engineers.
Matched proof
Backlog execution agent
Tessera uses supervised agent workflows to monitor delivery boards, pick up assigned work, produce implementation PRs, and keep stakeholders updated.
See execution proofGrowth reporting operating system
A recurring reporting workflow turns scattered ecommerce data into weekly commercial narrative, anomalies, and next actions.
See reporting proofInternal operating model
Every agent workflow runs with bounded tools, status logs, escalation rules, and human approval for external or sensitive actions.
Review controlsProcess
01
Assign ownership
Name the human operator, review rhythm, approval responsibilities, and escalation rules before the agent takes on real work.
02
Instrument
Add status logs, run summaries, decision trails, alerts, and improvement backlog items so performance is observable.
03
Operate
Run the workflow repeatedly, review exceptions, tune prompts and boundaries, and measure whether it saves senior time.
04
Improve
Expand scope only after the operating model proves reliable, documented, and commercially worth keeping.
FAQ
What is an AI agent operator?
An AI agent operator is the human role responsible for supervising agent workflows: scoping what agents may do, approving risky actions, reviewing logs, and improving the operating model.
Is Tessera selling AI operators?
No. Tessera provides the operating model, implementation, and retained supervision around AI agent workflows. The operator remains human; the agent is the system being operated.
Does this replace my team?
No. Agents remove repetitive analysis, coordination, and admin loops so your team can spend more time on judgement, creative direction, and execution.
What makes this different from a chatbot?
A chatbot waits for prompts. An operated agent workflow has triggers, allowed tools, success criteria, escalation rules, and a log of what happened.
Do agents act without approval?
Only inside agreed low-risk boundaries. Anything external, destructive, financial, or reputation-sensitive keeps a human approval gate.
Where should we start?
Start where work is frequent, rule-shaped, commercially meaningful, and currently handled by a senior person who should be doing higher-value work.
Can this work with our existing tools?
Yes. The point is to operate across the tools you already use: email, Slack, Asana, Shopify, GitHub, analytics, docs: not add another dashboard nobody opens.
If the workflow matters, make it operational.
Bring one messy workflow. Tessera will map the risk, define the operator boundary, and show the smallest useful system worth deploying.