Showing 73–96 of 510 articles, newest first.
What is prompt engineering? The deliberate design of the instruction that gets the output you want from a language model: role, task, context, constraint, and output format.
In RAG, chunking strategy is not one setting; it varies by document type. The right chunk size, overlap ratio and method for contracts, tables and manuals.
How to build an enterprise AI strategy, where to start, and why most strategies are never executed? A layer-by-layer guide that turns vision into a measurable roadmap.
What is data quality? Data quality is the sum of dimensions — accuracy, completeness, consistency, timeliness, uniqueness, and validity — that determine data's fitness for its intended use. This guide: a clear definition, the six quality dimensions, measurement metrics, the data cleaning process, the impact on AI and RAG projects, common mistakes, and FAQs.
What is data governance? Data governance is the set of policies and processes that define the ownership, quality, security, and usage rules of data in an organization. This guide: a clear definition, the difference from data management, core components, the KVKK dimension, its role in AI projects, implementation steps, and FAQs.
I explain from the field the differences between SFT, DPO and RFT and when to use each: the fine-tuning decision from demonstrations to rewards, with KVKK notes.
The four core metrics for measuring RAG systems: faithfulness, answer relevancy, context precision and recall. Evaluation with RAGAS, thresholds and context trust.
I compare the leading LLMs as of August 2026 through an enterprise buyer's eyes: capability, cost, latency and KVKK data residency, with practical picks.
Moving beyond brittle hand-written prompts: a practical guide to meta-prompting and metric-driven, programmatic prompt optimization with DSPy.
The strongest levers to control LLM cost in production: token economics, prompt caching, semantic cache and model routing, illustrated with 2026 pricing moves.
Pure vector search misses exact terms; pure keyword search misses meaning. A practical guide to combining BM25 and vector search in RAG with RRF and contextual retrieval.
The European Commission's supervision and enforcement powers over GPAI providers took effect on 2 August 2026. A practical roadmap for Turkish companies plus the KVKK link.
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.
Building RAG is easy, proving it reliable is hard. Retrieval/generation metrics, reference-free evaluation with RAGAS, OpenTelemetry spans, and cost-per-successful-output.
Prompt engineering is now engineering, not art. Automated optimization with DSPy, an eval-driven workflow, structured output, prompt chaining, and Turkish-specific evaluation.
Inference is now 55-80% of AI cost. Model routing, caching, quantization, and the metric that matters: cost-per-successful-output. An LLM FinOps framework and the Turkey FX context.
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 August 2026 frontier landscape: neck-and-neck on SWE-bench Verified, separation on SWE-bench Pro. Which model for which job, benchmark literacy, and the Turkish-performance criterion.
“Fine-tuning or RAG?” is a false dilemma. The 2026 sequence: Prompt → RAG → Fine-tune → Distill. LoRA/QLoRA, small language models, distillation, and the KVKK-sensitive self-host decision.
As of August 2, 2026 the EU AI Act GPAI enforcement powers and Article 50 transparency rules are live. What changed for Turkish firms, who is in scope, and a 90-day action list.
The 2026 agent protocol stack: MCP for tools, A2A for agent coordination. The attack surface each brings, OWASP agentic risks, and enterprise security controls.
AI in e-commerce moved from recommendation to action. Conversational commerce, autonomous purchasing, ROI figures, and compliance with Turkey’s August 1, 2026 advertising rules and KVKK.
2026 RAG is no longer linear. Adaptive routing, the agentic retrieve-reason-retrieve loop, five production patterns, and the highest-ROI intervention: hybrid retrieval + reranker.
MIT NANDA: 95% of enterprise AI pilots produce no P&L impact. ROI measurement shifts from productivity to revenue. A value-first framework for CTOs/CDOs.