Create, deploy, evaluate, retire, and replace agents.
Every agent is created, deployed, maintained, and eventually retired.
Creating an agent is a deliberate design act — not something that just happens.
Moving an agent from design to daily operation takes time and deliberate effort.
New agents are most fragile in their first month — they need extra attention and support to survive.
Agents need regular maintenance — scheduled reviews prevent gradual degradation.
Sometimes you should improve an existing agent; sometimes you should replace it entirely.
Track versions of your agents so you can compare, rollback, and learn from changes.
Define clear criteria for when an agent should be retired rather than maintained. Without explicit retirement criteria set in advance, you will hold onto agents long past the point where they serve you — because the sunk cost of building them, the identity you attached to them, and the absence of a forcing function all conspire to keep dead agents on life support.
Retire agents gracefully — document what they did, why they're being retired, and what replaces them.
When retiring an agent ensure its responsibilities transfer to a new agent or are consciously dropped.
Understanding your past agents — even failed ones — reveals patterns in how you build cognitive systems.
Your full set of active agents is a portfolio that should be balanced and diversified.
Periodically review and rebalance your agent portfolio — retire underperformers, invest in high-value agents.
New agents can inherit properties and patterns from existing successful agents rather than being built from scratch.
Create reusable templates for common agent patterns to accelerate creation of new agents.
Some agents outlive their usefulness but persist because removing them feels risky or costly. Legacy agents consume resources, create confusion, and block the deployment of better alternatives. Identifying them is the first step toward a clean epistemic portfolio.
Documentation should evolve with the agent — outdated docs are worse than no docs.
Too many agents create coordination overhead that can exceed their collective value.
Knowing where each of your agents is in its lifecycle helps you allocate attention appropriately.
The way you create, maintain, and retire agents mirrors how you learn, practice, and let go of knowledge. Recognizing this parallel turns agent management into a form of self-directed development.