Loading content
Observable symptom: High latency, expensive token bills, debugging that requires reconstructing emergent behaviour from logs. Suitable correction: Walk the decision heuristic. Sketch the simpler alternative side-by-side before you commit. Context: Mirrors the L3 anti-pattern: reaching for multi-agent when an L2 workflow would have sufficed.
Use this profile to understand the building block briefly, place it in the model, and switch to the 360° assessment when needed.
Theoretical construct: explains a term, principle, or mental model.
What organizes, connects, or makes decisions possible.
Over-agentification is an anti-pattern in which more autonomous AI agents or agent layers are used than a task needs for reliable results.
The term arose as a counterpoint to uncritical expansion of agentic systems. It follows the principle of the simplest sufficient solution and reflects practical experience with latency, cost, opaque decisions, and complex failure chains.
Every added agent layer introduces state, handoffs, and failure paths. First compare a deterministic function, a single model call, or a workflow with a multi-agent design. Agents are justified when autonomy and specialization provide measurable additional value.
An autonomous component that plans, decides, uses tools, or coordinates other agents.
A deliberate limit on the state, handoffs, testing, operations, and debugging a system can afford.
A working lower-autonomy solution used to test the value and cost of an agentic design.
This anti-pattern sharpens architecture choices for AI systems. A simpler baseline, measurable quality goals, bounded responsibilities, and strong traces help avoid needless cost and irreproducible behaviour.
Where this building block is located in the topic model.
No structure path available.
Explore how this building block connects to concepts, methods, technologies, and tools.
These sources establish the term and its professional meaning.
All direct connections of the current building block in a compact text view.
This classification shows where the building block typically matters, how demanding it is, and what kind of impact it has in the model.
The level within the organization (enterprise, domain, team) at which the AssetBlock is applied.