3. Execution Loops, Planning, and Self-Correction
True agents plan, execute, evaluate outcomes, and adapt strategies when intermediate steps fail.
The Concept
Enterprise tasks are rarely solved in one pass. Agents must decompose complex goals, choose actions, evaluate outcomes, and refine the plan when results are incomplete.
Execution loops provide this adaptive control. Instead of a single response, the system runs iterative cycles that connect planning, action, reflection, and retry logic.
This looped architecture improves resilience when tools fail, APIs are rate-limited, or retrieved evidence conflicts with user expectations.
Technical Implementation
Represent plans as explicit state machines with step status, dependencies, and rollback paths. Store these plans so execution can resume safely after interruptions.
After each tool call, run a lightweight evaluator that checks whether acceptance criteria were met. If not, route the flow to replanning with preserved context.
Set hard iteration limits and failure budgets to prevent infinite loops. Escalate unresolved cases to a human review queue with full trace context.
Reason-Act-Reflect Loop
Enterprise Scenario
An operations agent coordinates incident response: gather telemetry, execute diagnostics, summarize probable causes, and update stakeholders with confidence scoring.
Operational Outcomes
- Improved task completion for multi-step objectives.
- Faster recovery from transient API/tool failures.
- Clear escalation when confidence drops below thresholds.
