60 posts
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.
In 2026 'vector as a feature' wins: PostgreSQL + pgvector suffices for most scenarios. Three architectural thresholds, evaluation traps, and selection criteria.
In 2026 prompt engineering isn't dying but evolving into context architecture. Context orchestration, adaptive prompting, workflow engineering, and Turkish-specific care.
Token prices dropped 80% but bills grow. How to control cost with routing, caching, batching, and prompt discipline — plus a CFO-ready FinOps framework.
RAG for changing knowledge, fine-tuning for stable behavior; often both together. Why LoRA is the default, when RFT, small models, and the KVKK advantage.
On August 2, 2026 the Commission's GPAI enforcement powers took effect. Fines reach EUR 15M/3%; a practical compliance roadmap for companies touching the EU market from Turkey.
In 2026, work runs through orchestration of specialized agents. Six production patterns, MCP/A2A standards, and the cost-debugging-governance triad.
In July 2026 three major providers released new frontier models. An enterprise-use comparison, multi-model strategy, and a right-choice guide.
Agentic RAG moves retrieval inside the agent loop; with context engineering it cuts token usage 19-53%. Production patterns and a decision framework.
Customers now convey intent to agents to start shopping. Recommendation systems, operational impact, and a readiness guide for Turkish e-commerce.
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.
Synthetic data solved fine-tuning's data bottleneck. A field guide to generation methods, the practical recipe, model collapse, and Turkish data scarcity.
Text RAG misses tables, charts, and layout. A field guide to multimodal RAG architectures (ColPali, vision embeddings), evaluation, and KVKK.
With long context we can now put hundreds of examples in the prompt. A field guide to many-shot, trade-offs vs fine-tuning, prompt caching, and Turkish practices.
In self-hosted LLMs, bill and latency come from the serving layer. Manifold throughput via PagedAttention, continuous batching, speculative decoding, and quantization.
AI adoption in law doubled. A field guide to contract review, controlling hallucination with RAG, human judgment, and KVKK.
There's no single best model. A field guide to the August 2026 landscape, the benchmark trap, and a framework for choosing the right model for your work.
A field guide to the EU AI Act Article 50 transparency rules in force on August 2, 2026: chatbot disclosure, deepfake marking, and the KVKK intersection.
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.
2026 vector database guide: Pinecone, Weaviate, Qdrant, Milvus, pgvector comparison table, decision framework, cost, KVKK, and the 'start with pgvector' advice.
Employees are already pasting company data into unsanctioned AI tools. Why banning fails, a governance-first approach, and the KVKK generative-AI workplace guideline.
The way to boost RAG accuracy is hybrid search: combining BM25 and vector with RRF and adding a cross-encoder reranker. The numbers, the architecture, and Turkish tips.
AI in manufacturing 2026: the four ROI areas, the PoC-to-production leap, synthetic data, the ROI calculation, and a field roadmap with KVKK/EU AI Act notes for the Turkish manufacturer.
July 2026 packed five major models into two weeks. Model selection by use case, a comparison table, and an enterprise framework centered on KVKK and the EU AI Act.
Moving from hand-writing prompts to programmable pipelines with DSPy: signature, module, optimizer concepts, code examples, metric definition, a Turkish task, and KVKK-compliant production.
DPO aligns LLMs to human preferences without a separate reward model or RL. Loss intuition, beta, preference data, RLHF comparison, KVKK, and a Turkish example.
In 2026 agent memory is a layer separate from the context window. Short/long-term memory, Letta, Mem0, Cognee and KVKK-compliant production design.
We compare Qdrant, Pinecone, Weaviate, Milvus and pgvector on scale, latency, hybrid search and KVKK. A 2026 decision flow, table, and selection checklist.
There is no single best model in 2026: how to match GPT-5.6, Claude Opus 4.8, Fable 5, Gemini 3.1 and open models to the job, plus routing and KVKK guidance.
Claims automation, underwriting, fraud detection and policy RAG. AI use cases in insurance and KVKK obligations for high-risk automated decisions.
RAG or long context in the million-token era? A practical guide to hybrid architecture, BM25 + vector, RRF, reranking, contextual retrieval, and the KVKK angle.
In production, prompts are living software assets. Registry, semantic versioning, evaluation, observability, rollback, and KVKK/EU AI Act compliance.
Choose SFT, DPO/ORPO/KTO or RFT/GRPO by the data you have. A 2026 fine-tuning guide: method table, RAG comparison, KVKK, and a project checklist.
The three layers of cutting the LLM bill: model, system and application. Prompt caching, model routing, batching and Turkey-specific FX and KVKK risks.
Shadow AI is a daily reality for most employees in 2026. Banning backfires: a discovery playbook, risk table, 30/60/90 plan, and KVKK and EU AI Act guidance.
On August 2, 2026 GPAI enforcement powers go live. Scope, provider-vs-deployer, Article 50 transparency, and a concrete compliance checklist for Turkish companies.
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.
Not 'which one' but 'which fits me.' Real benchmark data, a decision framework, the recall-latency tradeoff, and KVKK/data residency. Synthetic benchmarks lie.
Measure your RAG system's real quality with four core metrics: faithfulness, answer relevance, context precision, and recall. Ragas, LLM-as-a-judge, and Turkish challenges.
As Gartner puts it, context engineering is in, prompt out. How the role evolved, patterns that still work (CoT, few-shot), and managing context at enterprise scale.
Observability is now a production prerequisite. Tracing vs evaluation, hallucination detection, LangSmith/Langfuse/MLflow, and self-hosting options for KVKK.