8bit.tr Journal
Ugur Yildirim
Computer Programmer
He focuses on building application infrastructures.
View profileArticles by Ugur Yildirim
January 12, 2026
Open-Source Models in Production: System Requirements, Tokens, and Context Windows
A technical, engineering-first guide to hardware sizing for open-source LLMs, including VRAM, RAM, tokens, and context window tradeoffs.
January 11, 2026
Alignment Evaluation and Safety Metrics: Measuring What Users Actually Need
A technical guide to evaluating alignment and safety with measurable metrics, red-teaming, and policy tests.
January 11, 2026
Cost Observability for LLMs: Unit Economics at Token Level
How to track per-token costs, margin, and efficiency across LLM workloads.
January 10, 2026
Adaptive Routing and Model Tiers: Balancing Cost and Quality
A production guide to routing requests across model tiers using quality signals, cost budgets, and latency targets.
January 10, 2026
Dataset Versioning and Rollbacks: Provenance for LLM Training
How to version datasets, track lineage, and roll back safely when training data changes.
January 9, 2026
Evaluation Harness for LLM Products: From Datasets to CI Gates
How to build a reliable evaluation harness for LLM products with datasets, scoring, and automated release gates.
January 9, 2026
Prompt Compiler Patterns: Static Analysis for Prompts
How to analyze and compile prompts with static checks to reduce ambiguity and runtime errors.
January 8, 2026
Chain-of-Thought Privacy: Keeping Reasoning Secure in Production
A production guide to reasoning traces, privacy risks, and safe disclosure patterns for LLM systems.
January 8, 2026
RAG Failure Modes and Mitigation: A Practical Taxonomy
A taxonomy of RAG failures with engineering fixes for retrieval, grounding, and generation errors.
January 7, 2026
Cross-Encoder Reranking: The Missing Layer in High-Precision RAG
How cross-encoders improve retrieval relevance and reduce hallucinations in production RAG systems.
January 7, 2026
Compliance Engineering for LLMs: Audit Trails and Change Control
A practical framework for compliance engineering, audit trails, and controlled model changes.
January 6, 2026
Efficient Context Summarization: Keeping Long Sessions Accurate
Techniques for compressing long context without losing intent, facts, or action items in LLM workflows.
January 6, 2026
Constraint Solving with LLMs: Hybrid Planning Pipelines
How to combine LLMs with constraint solvers for reliable planning and optimization.
January 5, 2026
Test-Time Compute Scaling: Self-Consistency and Reasoning Gains
A technical look at test-time compute strategies that improve reasoning without retraining the model.
January 5, 2026
On-Device LLM Deployment: Quantization, Latency, and Privacy
A practical guide to deploying LLMs on-device with quantization, memory limits, and privacy trade-offs.
January 4, 2026
Continual Learning and Drift: Keeping LLMs Useful Over Time
How to update LLMs safely with new data while avoiding catastrophic forgetting and quality regressions.
January 4, 2026
Multimodal RAG Pipelines: Grounding Answers Across Text and Images
How to build multimodal retrieval pipelines that combine text and visual evidence.
January 3, 2026
Parameter-Efficient Fine-Tuning: LoRA, QLoRA, and Practical Trade-Offs
A hands-on guide to PEFT methods like LoRA and QLoRA, with deployment trade-offs for quality, cost, and speed.
January 3, 2026
Long-Form Reasoning Benchmarks: Beyond Short QA
A guide to evaluating long-form reasoning with multi-step tasks, evidence chains, and consistency checks.
January 2, 2026
Foundation Model Governance: Policy, Risk, and Audit Readiness
A technical and operational guide to governing foundation models across safety, compliance, and auditability.
January 2, 2026
Retrieval Security and Permissioned Indexes: Preventing Data Leakage
How to design retrieval systems with permission-aware indexing and secure access control.
January 1, 2026
LLM Coding Systems and Compilers: From Tokens to Verified Programs
How LLMs are integrated with compilers, static analysis, and verification to produce reliable code.
January 1, 2026
Tool Reliability Engineering: Retries, Idempotency, and Failure Taxonomies
A practical guide to making tool calls reliable in LLM workflows with retries, idempotency, and error handling.
December 31, 2025
Mixture of Attention Routing: Smarter Context Allocation at Scale
A technical exploration of attention routing strategies that allocate context budget to the most relevant tokens.
December 31, 2025
Guarded Memory and Session Isolation: Protecting User State
How to design memory layers that isolate user state, prevent leakage, and enforce policy boundaries.
December 30, 2025
Prompt Injection Defense Architecture: Practical Security Layers
A security-first blueprint for protecting LLM systems from prompt injection and data exfiltration.
December 30, 2025
Secure Prompt Routing: Keeping Sensitive Inputs Isolated
How to route prompts securely across models and tools without leaking sensitive data.
December 29, 2025
Neural-Symbolic Systems: Combining LLMs With Formal Reasoning
How neural-symbolic architectures merge LLM flexibility with rule-based precision for high-stakes domains.
December 29, 2025
Model Cards and Transparency: Communicating Capabilities and Limits
A practical guide to writing model cards that communicate capabilities, limitations, and safe usage.
December 28, 2025
State Space Models and Mamba: A New Path Beyond Transformers
An engineering-focused look at state space models, Mamba, and where they outperform attention-based architectures.
December 28, 2025
RAG End-to-End Latency Budgeting: Where the Milliseconds Go
A technical guide to budgeting latency across retrieval, reranking, prompting, and generation stages.
December 27, 2025
Model Compression and Distillation: Smaller Models, Real Gains
A practical guide to compressing LLMs with quantization, pruning, and distillation while preserving quality.
December 27, 2025
Prompt Structure and Context Control: Engineering Predictable Behavior
Designing prompts with strict structure and context controls to reduce variance and improve reliability.
December 26, 2025
Retrieval Evaluation and Grounding: Measuring What Actually Matters
How to evaluate retrieval systems and grounding quality in RAG pipelines with practical metrics and workflows.
December 26, 2025
LLM Regression Testing: Preventing Silent Quality Drops
How to build regression suites that catch quality drops across prompts, models, and retrieval systems.
December 25, 2025
Sequence Parallelism: Scaling Context Without Breaking Training
A technical guide to sequence parallelism and how it improves training efficiency for long-context models.
December 25, 2025
Safety Policy Orchestration: Enforcing Rules Across LLM Pipelines
A practical architecture for enforcing safety policies across prompts, tools, and output layers.
December 24, 2025
Hallucination Mitigation Systems: Engineering for Factuality
A systems-level approach to reducing hallucinations using retrieval, verification, and structured generation.
December 24, 2025
Governed Knowledge Bases: Trust, Versioning, and Access Control
A framework for building governed knowledge bases with provenance, versioning, and access control.
December 23, 2025
Synthetic Data for LLMs: Quality, Diversity, and Safety
How to generate synthetic data that improves model performance without amplifying bias or noise.
December 23, 2025
LLM Latency Profiling and Optimization: Finding the Real Bottlenecks
How to profile LLM latency end-to-end and optimize the slowest paths in production.
December 22, 2025
KV Cache and Attention Optimization: The Hidden Performance Layer
A deep technical guide to KV caching, attention optimization, and memory-aware serving for LLMs.
December 22, 2025
Hierarchical Retrieval and Chunking: Scaling Knowledge Without Noise
A technical guide to hierarchical retrieval, chunking strategies, and multi-stage evidence selection.
December 21, 2025
LLM Data Pipeline Design: From Collection to Continuous Refresh
Engineering a reliable data pipeline for LLMs, including sourcing, filtering, deduplication, and ongoing refresh strategies.
December 21, 2025
Context Window Allocation: Budgeting Tokens for Maximum Signal
How to allocate context windows across system prompts, memory, and retrieval to maximize model performance.
December 20, 2025
RLHF and Preference Optimization: Aligning LLMs With Real Users
A deep dive into RLHF pipelines, preference data, and practical alignment strategies for production LLMs.
December 20, 2025
LLM Observability and Tracing: Seeing What the Model Actually Did
A practical guide to tracing, logging, and debugging LLM workflows in production systems.
December 19, 2025
Causal Reasoning for LLM Systems: From Correlation to Control
A technical guide to causal reasoning in AI systems, with practical patterns for reducing spurious correlations in LLM workflows.
December 19, 2025
Hybrid Search and Metadata Filters: Precision at Scale
How to combine dense vectors, keyword search, and metadata filters for high-precision retrieval systems.
December 18, 2025
Model Serving Architecture: From Single GPU to Global Fleet
Design patterns for serving AI models at scale: routing, caching, fallback tiers, and regional deployment.
December 18, 2025
Factuality Evaluation and Citation Quality: Proving Grounded Answers
How to evaluate factuality and citation quality for LLM answers in high-stakes environments.
December 17, 2025
Agentic Workflows and Tool Use: Building Reliable AI Operators
A practical blueprint for agentic systems: tool selection, planning loops, memory, and guardrails that keep agents reliable.
December 17, 2025
Model Risk Management: Quantifying and Controlling LLM Risk
A practical framework for identifying, scoring, and mitigating risks in LLM-powered products.
December 16, 2025
Speculative Decoding and Fast Inference: Making LLMs Feel Instant
A technical guide to speculative decoding, draft models, and system tricks that cut latency without sacrificing quality.
December 16, 2025
Long-Context Benchmarking: Measuring What Actually Scales
How to benchmark long-context LLMs with realistic tasks, latency constraints, and retrieval-aware metrics.
December 15, 2025
Distributed Training at Scale: Data, Parallelism, and Stability
A technical guide to scaling model training with data, tensor, and pipeline parallelism while keeping runs stable.
December 15, 2025
Energy Efficiency and Carbon-Aware AI: Sustainable LLM Operations
A technical guide to reducing energy use and carbon impact in LLM training and inference.
December 14, 2025
Multimodal Model Architecture: Unifying Text, Images, and Beyond
How multimodal models combine vision and language, plus the engineering decisions that make them reliable in production.
December 14, 2025
Multi-Agent Coordination Architecture: Designing Reliable Agent Teams
How to build multi-agent systems with clear roles, coordination protocols, and failure isolation.
December 13, 2025
LLM Memory, Context Windows, and Long-Context Design
A deep dive into context windows, memory strategies, and the engineering trade-offs behind long-context LLMs.
December 13, 2025
Retrieval Caching and Freshness: Faster Answers Without Stale Facts
A deep dive into caching strategies for retrieval systems that preserve speed without sacrificing freshness.
December 12, 2025
AI Inference Optimization Stack: Latency, Cost, and Quality
A production-focused guide to optimizing AI inference with batching, caching, quantization, and routing strategies.
December 12, 2025
Data-Centric LLM Iteration: Improving Models Without Bigger Architectures
Why high-quality data, labeling strategy, and error analysis often beat model scaling in production.
December 11, 2025
Fine-Tuning vs. Instruction Tuning: What Actually Improves LLMs
A clear comparison of fine-tuning, instruction tuning, and alignment, with guidance on when each approach makes sense.
December 11, 2025
Knowledge Distillation for Inference: Smaller Models, Real Speed
A deep dive into distillation pipelines that preserve quality while cutting inference cost.
December 10, 2025
Vector Databases and Embeddings: A Practical Engineering Guide
How embeddings are created, stored, and retrieved in vector databases, with real-world design choices for speed and relevance.
December 10, 2025
Structured Output and Schema Guards: Making LLMs Deterministic
How to enforce structured outputs with schemas, validators, and constrained decoding for production reliability.
December 9, 2025
LLM Guardrails and Safety Layers: Practical Patterns for Real Products
A hands-on guide to building guardrails, moderation layers, and policy enforcement for LLM-powered applications.
December 9, 2025
Temporal Reasoning and Time Awareness in LLM Systems
How to design LLM systems that reason over time, handle recency, and avoid stale conclusions.
December 8, 2025
Prompt Systems, Not Prompt Tricks: A Production-Ready Approach
How to move from ad-hoc prompts to robust prompt systems with templates, guardrails, and evaluation loops.
December 8, 2025
Prompt Robustness and Adversarial Testing: Hardening LLM Interfaces
A deep dive into adversarial prompt testing, robustness metrics, and systematic hardening of LLM inputs.
December 7, 2025
Transformers vs. Mixture of Experts: When to Use Each Architecture
A practical comparison of dense transformers and MoE models, focusing on cost, latency, and real-world deployment trade-offs.
December 7, 2025
Distributed Inference and Load Balancing: Serving LLMs at Planet Scale
A systems-level guide to distributed inference, load balancing, and traffic shaping for large-scale LLM services.
December 6, 2025
AI Model Evaluation Playbook: Metrics, Benchmarks, and Reality Checks
How to evaluate AI models with the right metrics, human review loops, and production-grade benchmarks.
December 6, 2025
Benchmark Leakage and Contamination: Keeping Evaluation Honest
How to detect benchmark leakage, prevent contamination, and build reliable evaluation pipelines.
December 5, 2025
Retrieval-Augmented Generation (RAG): Architecture, Pitfalls, and Best Practices
A practical guide to building RAG systems that are accurate, fast, and easy to maintain in production.
December 5, 2025
Kernel Fusion and Inference Kernels: Squeezing Latency Out of GPUs
A deep dive into kernel fusion, custom kernels, and GPU-level optimizations for fast LLM inference.
December 4, 2025
LLM Architecture From Scratch: The Building Blocks That Matter
A clear, technical walk-through of modern LLM architecture, from tokenization and attention to training loops and inference trade-offs.
December 4, 2025
Differential Privacy for LLM Training: Protecting Data at Scale
A practical guide to applying differential privacy in LLM training without destroying model utility.
December 4, 2025
C and C++ in AI Systems: The Performance Layer Behind Modern ML
A professional deep dive into how C and C++ power AI systems under Python, from kernels and runtimes to deployment at scale.
December 3, 2025
Shipping Fast Without Burning Out: A Sustainable Release Rhythm
A sustainable release rhythm for small teams: weekly cadence, focus rituals, quality systems, and energy-aware planning.
December 3, 2025
Multi-Tenant Token Budgeting: Fairness, Cost, and Performance
Designing token budgets for multi-tenant LLM systems while preserving fairness and latency targets.
December 3, 2025
Model Ensemble Strategies: Aggregating Confidence for Better Answers
How to use model ensembles to improve accuracy, confidence, and robustness in LLM systems.
December 2, 2025
AI Product Design Checklist for 2026
A practical AI product design checklist covering trust boundaries, feedback loops, reliability, and launch operations.
December 2, 2025
Uncertainty and Calibration for LLMs: Knowing When to Abstain
How to estimate confidence, calibrate outputs, and design abstention policies for safer AI systems.
December 2, 2025
Safe Autocomplete and Guardrails: Preventing Risky Suggestions
How to design autocomplete systems that avoid unsafe or non-compliant suggestions.
December 1, 2025
What Is an MVP? A Practical Guide for 2026 Product Teams
Learn what an MVP is, how to define the smallest valuable product, and validate demand fast with real metrics and a 90-day playbook.
December 1, 2025
Function Calling and Toolformer Patterns: Reliable Tool Use at Scale
A systems-level guide to function calling, tool routing, and safe execution for LLM-driven workflows.
December 1, 2025
LLM SLO Engineering: Defining Reliability for AI Systems
How to define SLOs for latency, accuracy, and safety in LLM-powered products.