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Uğur Kaval

AI/ML Engineer & Full Stack Developer building innovative solutions with modern technologies.

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15 articles tagged with this topic.

Beyond Chatbots: Engineering Production-Grade AI Agents with Tool Use
AI/ML

Beyond Chatbots: Engineering Production-Grade AI Agents with Tool Use

Stop treating LLMs as oracles and start treating them as orchestrators. Learn how to build reliable, schema-validated agents that interact with real-world APIs using modern 2026 patterns.

June 5, 20266 min read
Beyond the Linter: Engineering AI-First Review Pipelines in 2026
AI/ML

Beyond the Linter: Engineering AI-First Review Pipelines in 2026

Manual code reviews are a bottleneck that costs your team millions in lost velocity. Here is how I built a multi-agent AI pipeline that catches race conditions, generates property-based tests, and reduced our MTTR by 42%.

June 1, 20266 min read
Beyond Vector Search: Building Production Knowledge Graphs with LLMs
AI/ML

Beyond Vector Search: Building Production Knowledge Graphs with LLMs

Vector embeddings are hitting a wall. Learn how to build a robust, queryable knowledge graph from unstructured text using LLMs, Pydantic, and Graph databases for true multi-hop reasoning.

May 28, 20265 min read
Vector Database Comparison: Pinecone vs Weaviate vs Qdrant for Real Workloads
AI/ML

Vector Database Comparison: Pinecone vs Weaviate vs Qdrant for Real Workloads

Scaling vector search to 100M+ embeddings requires more than just picking a popular name. I compare Pinecone, Weaviate, and Qdrant based on 2026 production performance, architectural trade-offs, and true cost of ownership.

May 24, 20265 min read
Beyond Text: Engineering Production-Grade Multimodal AI in 2026
AI/ML

Beyond Text: Engineering Production-Grade Multimodal AI in 2026

Stop treating images and audio as secondary metadata. Learn how to build systems that treat pixels, decibels, and tokens as first-class citizens in a single inference pipeline.

May 16, 20265 min read
Context is Everything: Engineering Persistent Memory for LLM Agents
AI/ML

Context is Everything: Engineering Persistent Memory for LLM Agents

Forget basic chat history. Scaling conversational AI in 2026 requires semantic retrieval, windowed summaries, and stateful graph management. Here is how I built a production-grade memory system using LangGraph and vector compaction.

May 12, 20266 min read
Beyond Static Thresholds: Real-Time Anomaly Detection with Streaming ML
AI/ML

Beyond Static Thresholds: Real-Time Anomaly Detection with Streaming ML

Static alerts are where reliability goes to die. Learn how to implement online learning models using River and Bytewax to detect infrastructure and business anomalies in sub-100ms windows.

May 8, 20265 min read
Building Production-Grade Computer Vision Pipelines for Manufacturing in 2026
AI/ML

Building Production-Grade Computer Vision Pipelines for Manufacturing in 2026

Stop wasting money on generic vision sensors. Learn how to build high-throughput, edge-deployed quality control systems using YOLOv11, TensorRT, and specialized lighting setups that actually survive the factory floor.

May 4, 20265 min read
Scaling Engineering Velocity: Building Autonomous Code Review Pipelines in 2026
AI/ML

Scaling Engineering Velocity: Building Autonomous Code Review Pipelines in 2026

Stop wasting senior engineering hours on syntax and basic logic. I'll show you how we integrated GPT-5 and Llama 4 into our CI/CD to automate 80% of code reviews and unit test generation.

April 30, 20266 min read
Vector Database Comparison: Pinecone vs Weaviate vs Qdrant for Real Workloads
AI/ML

Vector Database Comparison: Pinecone vs Weaviate vs Qdrant for Real Workloads

I spent 48 hours debugging a production latency spike in our recommendation engine because our vector database couldn't handle a write-heavy surge. Here is the 2026 guide to choosing between Pinecone, Weaviate, and Qdrant based on actual performance data and architectural trade-offs.

April 18, 20266 min read
Engineering Reliable AI Agents: A Practical Guide to Tool Use and Function Calling
AI/ML

Engineering Reliable AI Agents: A Practical Guide to Tool Use and Function Calling

Stop treating AI agents like chat bots and start treating them like distributed systems. Here is how to implement tool-calling that actually works in production without the hallucinations.

March 29, 20266 min read
Building Production-Grade Knowledge Graphs: Beyond the LLM Extraction Hype
AI/ML

Building Production-Grade Knowledge Graphs: Beyond the LLM Extraction Hype

Stop building flat RAG systems. Learn how to extract high-fidelity entities and relationships from unstructured text using Pydantic, DSPy, and Neo4j to build a graph-augmented LLM stack that actually scales.

March 17, 20266 min read
Responsible AI: Building Bias Detection and Mitigation into ML Pipelines
AI/ML

Responsible AI: Building Bias Detection and Mitigation into ML Pipelines

Stop treating fairness as a post-launch checklist item. Here is how I integrate bias detection and mitigation directly into CI/CD pipelines using Fairlearn 0.12 and custom Great Expectations suites.

March 13, 20266 min read
Building Evaluation Frameworks for LLM Applications: Beyond the Vibe Check
AI/ML

Building Evaluation Frameworks for LLM Applications: Beyond the Vibe Check

Stop guessing if your prompt changes are working. Learn how to build a production-grade evaluation pipeline using LLM-as-a-judge, synthetic data, and automated regression testing.

March 9, 20265 min read
Beyond ChatOps: Building Proactive Incident Response Bots in 2026
Automation

Beyond ChatOps: Building Proactive Incident Response Bots in 2026

Stop manual context switching during outages. Learn how we built a Slack-native incident response system that reduced MTTR by 40% using Bolt, LLMs, and automated log retrieval.

March 2, 20267 min read