AI AGENTS
When a task needs more than a rule.
We design agents that interpret information, use tools, and execute multiple steps within a defined process.
With boundaries, traceability, and human control where appropriate.SIGNALS · NOT AUTOMATIC CONCLUSIONS
Where does traditional automation stop being enough?
- 01Information must be read before deciding.
- 02The next step changes with context.
- 03The task consults several sources or tools.
- 04Someone researches, compares, and then acts.
- 05The process keeps context across multiple steps.
- 06Unstructured language meets transactional systems.
These are signals to evaluate. They do not mean every case needs an agent.
CAPABILITIES · NOT SYNONYMS
Conversing, interpreting, and acting are different jobs.
Chatbotconverses.
Automationexecutes known rules.
Integrationconnects systems.
AI modelinterprets or generates information.
AI agentcombines context, decisions, tools, and actions within boundaries.
AI consultingdetermines which capability is needed.
THE AGENT CYCLE
Every action produces new context.
An agent does not receive unlimited autonomy. It operates within defined tools, information, rules, and permissions.
- 01ObjectiveWhat must it complete?
- 02ObserveReceive available context.
- 03InterpretUnderstand the situation.
- 04DecideChoose the next step.
- 05Use a toolAct with permission.
- 06See resultUpdate the context.
- 07Continue, escalate, or finishRespect stopping conditions.
WORK PATTERNS
What an agent can do.
Research
Consult sources · gather context · compare information · prepare findings.
Process
Read documents · classify · extract information · transform data and context.
Coordinate
Execute steps · use tools · maintain context · choose how to continue.
Act
Create or update information · trigger processes · prepare communications.
Escalate
Stop · request approval · route an exception · preserve context.
Each agent’s scope is defined for its process. Not every agent performs every action.
CHOOSE THE RIGHT CAPABILITY
If a rule is enough, we prefer the rule.
When X arrives, execute Y.Automation
Consult A, verify B, and update C.Automation + Integration
Generate a summary.A model may be enough
Read, understand intent, consult systems, and decide.Potential agent
Research sources, compare, decide, and continue.Potential agent
Everything follows known rules.Probably not an agent
CONTROL · PRIVACY · HUMAN INTERVENTION
“Give it access to everything” is not a design.
We define scope, tools, permissions, validations, and stopping conditions. Traceability is designed for the process.
Local, external, or hybrid.
The choice depends on sensitivity, latency, infrastructure, security, and organizational constraints.
Autonomy proportional to risk.
It can act on low-risk tasks, request approval, or stop when an exception occurs.
Without enough context, it does not continue.
It can preserve what it gathered and escalate the decision to a person.
NOT EVERYTHING SHOULD BE AGENTIC
More flexibility also requires more control.
An agent adds interpretation and dynamic capacity. It also adds:
- variability;
- greater complexity;
- a need to validate behavior;
- more control decisions.
EVIDENCE · ANONYMIZED R&D CASE
The constraint was part of the design.
Internal constraints prevented sensitive information from being sent to public or external cloud services.
A research-assistance agent using a fully local, closed model.
Research time fell by more than 75%, without sending sensitive information to external cloud services.
These results reflect a specific implementation and do not imply identical outcomes in other projects.
NEXT STEP
Start with the task. Not the agent.
Tell us which task requires interpreting, deciding, or acting across multiple steps.
Assess a process We may also conclude that simple automation is enough.