
Agentic Architecture Options Part 5: Reflexion (Self-Correction) Architecture
Reflexion architecture uses self-correction and memory to fix errors, but high costs and latency make it best for deterministic tasks.

Reflexion architecture uses self-correction and memory to fix errors, but high costs and latency make it best for deterministic tasks.

Plan-and-Execute architectures prioritise structured, hierarchical workflows over reactive loops, delivering superior predictability and parallel execution for complex, multi-step business tasks.

ReAct architecture boosts performance via iterative reasoning, yet faces high costs and latency. It’s best for narrow, specialised research tasks.

BDI architecture offers a transparent, resource-efficient framework for goal-directed RAG, though it requires stable environments and rigorous upfront plan engineering.

Microsoft 365 E7 offsets AI infrastructure costs by bundling Copilot and governance, though consumption-based pricing creates significant fiscal unpredictability.

Ray White boosted productivity by integrating Canva APIs into core workflows, slashing content creation time and automating brand governance through AI.

Ignore ‘SaaSpocalypse’ hype. SaaS remains your stable system of record; use AI ‘vibe-coding’ only for niche, high-value edge innovations.

Effective AI deployment requires matching specific request types to varied agentic architectures, balancing performance, cost, and latency for optimal outcomes.

AI offers efficiency, but risks work intensification. Success requires a human-led ‘cyborg model’ to ensure technology empowers teams without eroding well-being.