Agents mark the shift from one-shot Q&A to multi-step workflows — and in enterprise settings the hard part is not intelligence but control. This cluster covers tool calling and MCP, multi-agent systems, error handling and rollback, and agent security.
When is a multi-agent system really necessary? The single-agent vs multi-agent decision, agent division of labor, coordination cost, error propagation, and orchestration patterns for enterprise AI.
Agent error handling is the reliability discipline that stops error propagation in multi-step tasks through validation, retries, rollback, and human handoff.
What is the difference between an AI agent and a chatbot? A chatbot talks and answers; an AI agent plans toward a goal, uses tools, and completes multi-step tasks autonomously.
What is agentic AI, how does an agent work, and where should it not be used? Autonomous task architecture with planning, tools, memory, and human approval.
How do you do tool definition in agent architecture? A good tool schema: a clear name, a description that says when to use it, well-typed parameters, and readable errors.
Stateless LLM calls aren't enough for agents. Short/long-term memory, episodic-semantic-procedural memory, and practical architecture in light of KVKK's Agentic AI guideline.
The value of agentic AI is not in intelligence but in managing autonomy with discipline. A five-level autonomy ladder, ROI-vs-risk balance, human-in-the-loop thresholds, and a CTO/CDO evaluation framework.
The 2026 agent protocol stack: MCP for tools, A2A for agent coordination. The attack surface each brings, OWASP agentic risks, and enterprise security controls.
In 2026, work runs through orchestration of specialized agents. Six production patterns, MCP/A2A standards, and the cost-debugging-governance triad.
Pilots not reaching production? A field guide to why and how to build an AI CoE, agentic workforce governance, and the KVKK/talent/budget dimension in Turkey.
An agent at 90% in testing drops to 70% in production. A field guide to the reliability gap, pass^k, LLM-judge biases, and a production evaluation framework.
AP2, signed mandates, its relation to ACP, and agentic commerce in Turkey's BDDK/KVKK context — what e-commerce businesses should do, from the field.
In 2026 agent memory is a layer separate from the context window. Short/long-term memory, Letta, Mem0, Cognee and KVKK-compliant production design.
Short- and long-term memory architecture for AI agents: vector DBs, summary buffers, decay policies, the ACE loop, failure modes, and KVKK-ready compliance patterns.
The secret to agentic AI success is discipline, not the model. Four bottlenecks in pilot-to-production, maturing frameworks, and KVKK/EU AI Act governance.
Agentic commerce is the third wave: agents research and buy on the user's behalf. Google 'Buy for me', 4x conversion, the trust problem, and KVKK personalization limits.
Agentic AI in e-commerce: conversational product discovery, autonomous customer service, and personalization. A 2026 Turkish field guide to building it all within KVKK limits.
The number-one cause of AI agent failure is memory. A field guide to short/long/graph memory architectures, multi-scope patterns, LangGraph, and KVKK-compliant retention for 2026.
As agents reach production the real risk is governance. I build the agent inventory, traceability, permission limits and accountability framework from a CTO/CDO lens.
Most agent pilots die before production. The cause is not the model but governance, traceability and context management. I share a solution architecture from the field.
Shopping agents, conversational commerce, and dynamic pricing drive conversion — how do you keep the KVKK balance? E-commerce use cases and risk mitigation.
MIT: 95% of pilots deliver no measurable P&L. The three layers that carry agent pilots to production: measurement, infrastructure, strategy. A governance framework for CTOs/CDOs.
MCP connects tools, A2A connects agents. The Agentic AI Foundation, signed Agent Cards, and the three-layer stack: the 2026 map of enterprise multi-agent architecture.
Shopping agents are reshaping discovery and conversion. Conversational commerce architecture, recommendations and KVKK-compliant personalization for Turkish e-commerce.
Grouped by format, newest first within each group.
Agentic AI is the architecture in which a large language model — instead of producing a single answer — autonomously completes multi-step tasks by combining planning, tool use, memory and feedback loops.