Useful autonomy without losing control, traceability and cost discipline.
Analysis on agents, orchestration, tools, memory, human supervision and safe boundaries for agentic workflows.
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Architecture and orchestration
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Tools, memory and context
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Supervision, permissions and audit
Design agents with operational control
Agentic workflow design with clear limits, logs and autonomy criteria.
Design agents with operational controlSanity-published content connected to this editorial pillar.
1 published article
MemPalace put agent memory on the industry’s broader radar. The problem: the conversation started badly, with polished benchmarks, inflated narratives, and little production maturity.
AI in production
From impressive pilots to systems that survive real operations.
AI in productionLLM integration, RAG and hybrid architecture
Models connected to the business without fragile improvisation.
LLM RAG integrationMLOps, LLMOps and AIOps
Reliability, evaluation and observability for AI that cannot become a black box.
MLOps LLMOps AIOpsAI governance, audit and security
Practical controls for AI that must be explainable, traceable and safe.
AI governanceInfrastructure, FinOps and AI cost
Platforms, latency and cost so AI operates without invoice surprises.
AI infrastructure FinOpsResilient systems for production AI
Architecture, fallback and response when automation fails.
resilient AI systemsHyperlean, ROI and margin with AI
Before scaling, prove where AI changes cost, revenue or predictability.
AI ROIAI-powered SaaS products
AI as product layer, support, retention and expansion — not just chatbot.
AI SaaS