18 patterns for this issue
Cost-Optimization Agent Reports an Autonomous Resize or Termination as Successful Based on the Cloud API's Synchronous "Request Accepted" Response, Without Polling the Resource's Actual Post-Action State
A Cost-Optimization Agent That Selects a Cost-Reduction Playbook for a Flagged Resource by Semantic Similarity Over Its Tags, Name, and Description Pulls a Playbook Written for a Fault-Tolerant Batch Workload -- Recommending Migration to Spot/Preemptible Instances -- and Applies It to a Latency-Sensitive, Interruption-Intolerant Workload That Shares Overlapping Tag Vocabulary but Cannot Tolerate the Same Risk
A Small Edit to a Source Document Triggers Full Re-Embedding/Re-Analysis of the Entire Document Instead of an Incremental Update to Just the Changed Portion
Agent stays on generic frontier-model prompting for a high-volume, narrow, repetitive task long after fine-tuning or distillation would outperform it on both cost and quality.
A Coordinator Broadcasts Full Shared Context/History to Every Sub-Agent Regardless of Relevance, Multiplying Token Cost by Agent Count
A Cost-Analysis Agent Identifies an Underutilized Instance as a Rightsizing Candidate but Notes in Its Free-Text Reasoning That the Instance Is Excluded Because of an Active Maintenance Freeze or Production-Critical Designation, and a Downstream Execution Agent That Acts on a Structured Candidate List Never Sees the Exclusion Note, Resizing the Protected Instance Anyway
Agent Re-Derives an Identical Multi-Step Plan From Scratch for Every Occurrence of a Routine, Frequently-Repeated Operation
Agent's "Reused" Plans Are Not Actually Parameterized, So Near-Identical Requests Still Trigger Full Re-Planning Instead of a Template Substitution
A Stable Prompt Prefix (System Prompt, Tool Schemas, Few-Shot Examples) Is Retransmitted and Rebilled at Full Price on Every Call Instead of Using Available Prompt-Caching
Verbose but Relevant Prompt Content Is Sent Uncompressed at Full Token Cost When Established Compression Techniques Would Preserve Meaning at a Fraction of the Length
Agent Runs Multiple Self-Critique/Verification Calls by Default, Regardless of Whether the Task Actually Benefits From Them
Agent Has No Negative-Cache/Failure-Memory, So It Regenerates and Re-Serves an Answer Already Confirmed Wrong When the Same or a Similar Question Recurs
Agent Recommends Downsizing Compute Resources Based on Average Utilization, Ignoring Peak Load Requirements That Drive Actual Capacity Needs
A Cost-Optimization Agent Calls a Cloud-Provider Billing/Cost-Export Tool to Decide Whether to Autonomously Resize or Terminate Underutilized Resources, the Tool Returns a Cached or Delayed Billing Export That Predates a Recent Spend Spike or Recent Manual Remediation, and the Agent Acts on Spend Data That No Longer Reflects Current Reality
Conversation History and Tool Output Are Appended Every Turn With No Truncation or Summarization, So Total Session Cost Grows Superlinearly as the Conversation Lengthens
Agent Skips Upfront Planning on a Task That Genuinely Needed It, Causing Failed Attempts and Expensive Rework
N Expensive Model Calls Run in Parallel to Vote/Merge on an Answer, for Tasks a Single Call Would Have Handled Just as Well
Agent Runs a Full Planning/Decomposition Call for Tasks Simple Enough to Execute Directly
Agentic planning, learning, and architecture-level cost waste — distinct from Cost Efficiency (GitHub)‘s execution-level patterns (batching, retries, model routing). This goal covers failures where a known cost-optimization technique (plan reuse, prompt caching, adaptive ensembling, negative caching, compression) exists but isn’t applied, or is applied incorrectly.
Total: 13 patterns