A text-message AI agent becomes useful when it understands attention as a scarce resource. The right budget tells it which events deserve an immediate ping, which decisions can wait for a digest, and which noisy signals should never reach you at all.
Most failed personal agents do not fail because they cannot act. They fail because every alert feels equally important. An attention budget fixes the operating agreement.
Do not say that calendar, email, delivery, or finance events are always urgent. Instead define the conditions that justify interruption: time sensitivity, irreversible consequences, human waiting cost, and confidence in the source.
Choose a maximum number of proactive pings per day. A strong default is three immediate interruptions, one midday digest, and one end-of-day review.
Let the agent interrupt when delay creates cost: a missed ride, a customer waiting, a payment risk, a family logistics issue, or a task that blocks another person.
Before an agent escalates, it should cite where the signal came from and whether it has seen conflicting evidence.
The agent needs permission to do nothing. Add rules for marketing emails, repeated reminders, low-confidence summaries, and alerts outside your active projects.
Use these modes as a horizontal policy. They work whether your agent watches SMS, email, calendar, browser work, or human-in-the-loop task updates.
For urgent, high-confidence items that degrade quickly if ignored.
For important items that matter today but do not need a real-time notification.
For ambiguous items where another human or tool must verify before action.
For low-value noise that should be logged without consuming attention.
The first version should be simple enough to audit. If the agent cannot explain why it interrupted you, the rule is not ready.
List the five situations where interruption is welcome. Keep the list small. Text-message agents get better when their permission surface is narrow and legible.
Quiet hours should be strict. Bypasses should be rare and named: family emergencies, direct customer commitments, security events, or time-boxed logistics.
Require two signals for non-obvious urgency. For example, a calendar change plus a message from the attendee is stronger than either signal alone.
Mark each ping as useful, too early, too late, unnecessary, or missing. Feed those examples back into the agent prompt and operating policy.
Before sending a proactive text, classify the event as interrupt, batch, escalate, or archive. Interrupt only when the event is time-sensitive, confidence is high, and waiting creates real cost. Include the source, the reason for urgency, and the smallest useful action I can take.
Supers is useful when you want a personal agent that can live close to real workflows instead of staying in a chat tab. Start with the text message AI assistant, then connect work that needs browsing through computer-use cache workflows or have an agent assemble static pages through AI website-building workflows.
Attention budgets are not just a preference layer. They are the policy layer that decides whether an autonomous assistant feels trustworthy.
Yes at first. A strict cap creates visible tradeoffs. Once the agent has a history of useful choices, you can add context-aware exceptions.
The agent should move non-critical items into the next digest and only bypass the cap for named emergency categories.
Only for reversible actions that you have explicitly approved. Anything irreversible should require confirmation or escalation.
Use real failures. Tell the system prompt what went wrong, why the alert was premature or missing, and what should always happen next time.
Supers can help you shape text-message workflows, browser actions, and repeatable agent tasks around rules that stay calm under real-world noise.