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.
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.
Microsoft’s complex five-layer licensing hierarchy causes 15-40 per cent budget waste. Mastering these layers ensures commercial competence and prevents costly capability duplication.
Microsoft’s rapid rebranding and licensing shifts create market confusion. Executives must track new SMB tiers and E5 bundles to optimise procurement.
