Start with a bounded job
Autonomy needs edges.
A strong first agent takes on a task with a clear beginning, an observable result, and a meaningful human escalation path. Open-ended ambition can come later.
STIPDOT / Field note / AI agents
The agent is not the product. The completed work is.
The most useful way to assess an AI agent is not by how autonomously it appears to reason, but by whether it can own a valuable piece of work safely and repeatably.
Build the control loop
The work must stay legible.
Production agents need evaluation, traceability, permissions, and feedback. The operator should know what changed, why it changed, and how to intervene.
Earn expansion
Trust compounds through evidence.
The best path is to prove value in one workflow, deepen integration, then extend into adjacent work once users understand the system’s limits and strengths.
Investor question
What gets better with every completed task?
Look for a learning loop: customer context, structured feedback, proprietary workflow data, or a distribution advantage that makes the product harder to replace.
Apply the idea
A practical test: the bounded research agent.
Consider an agent that prepares a weekly account brief from approved internal notes. Define the allowed sources and output format first. Compare it with the current manual process on factual accuracy, source coverage, review time, and cost. Require approval before it writes into a customer record or sends anything externally. A polished summary is not enough: the reviewer needs to trace claims, correct omissions, and recognize when the source material cannot support an answer. Expansion should follow evidence that the whole workflow, including review and recovery, has improved.
Generative AI should elevate taste, not erase it. ↗
AIGC creates an abundance of first drafts. Its lasting value will be measured by whether people can use that abundance to make better choices and more original work.
Field note / AI & workThe best AI gives people more room to do the work only they can do. ↗
The point of workplace AI is not to make people busier. It is to reduce avoidable coordination and give expertise, care, and judgment more room to matter.
Field note / TrustResponsible AI is the operating system for scale. ↗
As an AI product moves from a small group of enthusiastic users to consequential use, trust becomes an engineering, product, and leadership discipline.
Field note / AI & lifeA better future is one where intelligence is more widely available. ↗
AI can make daily life more dignified when it helps people understand complex systems, access services, learn new skills, and maintain more time for one another.
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Questions to take into a product review.
Start with the investor question: What gets better with every completed task?
Task boundary
Which actions can the agent take independently, which need approval, and what event ends the task?
Recovery
When a tool fails or an input is ambiguous, can a person resume the work without reconstructing the whole run?
Acceptance
What share of completed tasks meet the user’s standard after counting review effort and correction costs?