<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Samuel Olubukun&apos;s Blog</title><description>Thoughts, learnings, and insights from my journey in AI engineering and software development</description><link>https://samuelolubukun.com/</link><language>en-us</language><lastBuildDate>Sun, 16 Aug 2026 22:08:22 GMT</lastBuildDate><image><url>https://samuelolubukun.com/favicon.svg</url><title>Samuel Olubukun&apos;s Blog</title><link>https://samuelolubukun.com</link></image><item><title>AI Security &amp; Governance: The Enterprise Field Guide</title><link>https://samuelolubukun.com/blogs/ai-security-and-governance-field-guide/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-security-and-governance-field-guide/</guid><description>A comprehensive enterprise field guide distilled from Securiti&apos;s AI Security &amp; Governance certification. Covers AI security, model discovery, NIST AI RMF, Gartner TRiSM, OWASP Top 10 LLM Risks, LLM Firewalls, and global regulations like the EU AI Act.</description><pubDate>Tue, 28 Jul 2026 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1550751827-4bd374c3f58b?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Security &amp; Governance: The Enterprise Field Guide&quot; /&gt;&lt;p&gt;A comprehensive enterprise field guide distilled from Securiti&apos;s AI Security &amp; Governance certification. Covers AI security, model discovery, NIST AI RMF, Gartner TRiSM, OWASP Top 10 LLM Risks, LLM Firewalls, and global regulations like the EU AI Act.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-security-and-governance-field-guide&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Security</category><category>AI Governance</category><category>Securiti</category><category>LLM Security</category><category>Enterprise AI</category><category>Compliance</category><category>NIST AI RMF</category><category>EU AI Act</category></item><item><title>AI Engineering Part 5: Production Deployment, Evals &amp; Monitoring</title><link>https://samuelolubukun.com/blogs/ai-engineering-part-5-production-evaluation/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-engineering-part-5-production-evaluation/</guid><description>The grand finale of our AI Engineering masterclass series. Master LLM Evaluation Suites (Evals), LLM-as-a-Judge, Latency Optimization (TTFT, TBT, vLLM), Semantic Caching, and Observability.</description><pubDate>Mon, 14 Jul 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1451187580459-43490279c0fa?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Engineering Part 5: Production Deployment, Evals &amp; Monitoring&quot; /&gt;&lt;p&gt;The grand finale of our AI Engineering masterclass series. Master LLM Evaluation Suites (Evals), LLM-as-a-Judge, Latency Optimization (TTFT, TBT, vLLM), Semantic Caching, and Observability.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-engineering-part-5-production-evaluation&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Engineering</category><category>LLMops</category><category>Evals</category><category>Production</category><category>Observability</category></item><item><title>AI Engineering Part 4: Agents, Tool Use &amp; Autonomous Systems</title><link>https://samuelolubukun.com/blogs/ai-engineering-part-4-agents-autonomous/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-engineering-part-4-agents-autonomous/</guid><description>Part 4 of our AI Engineering masterclass series. Explore autonomous AI Agents: ReAct execution loops, Function Calling mechanics, Multi-Agent Orchestration, E2B Sandboxing, and Prompt Injection defenses.</description><pubDate>Tue, 08 Jul 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1531482615713-2afd69097998?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Engineering Part 4: Agents, Tool Use &amp; Autonomous Systems&quot; /&gt;&lt;p&gt;Part 4 of our AI Engineering masterclass series. Explore autonomous AI Agents: ReAct execution loops, Function Calling mechanics, Multi-Agent Orchestration, E2B Sandboxing, and Prompt Injection defenses.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-engineering-part-4-agents-autonomous&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Engineering</category><category>AI Agents</category><category>Tool Use</category><category>Function Calling</category><category>Autonomy</category></item><item><title>AI Engineering Part 3: RAG Pipelines &amp; Vector Databases</title><link>https://samuelolubukun.com/blogs/ai-engineering-part-3-rag-pipelines/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-engineering-part-3-rag-pipelines/</guid><description>Part 3 of our AI Engineering masterclass series. Dive deep into Retrieval-Augmented Generation: Chunking algorithms, Vector Embeddings, HNSW vs IVF indexing, Hybrid Search (BM25 + Dense), RRF, and Cross-Encoder Reranking.</description><pubDate>Thu, 03 Jul 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1558494949-ef010cbdcc31?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Engineering Part 3: RAG Pipelines &amp; Vector Databases&quot; /&gt;&lt;p&gt;Part 3 of our AI Engineering masterclass series. Dive deep into Retrieval-Augmented Generation: Chunking algorithms, Vector Embeddings, HNSW vs IVF indexing, Hybrid Search (BM25 + Dense), RRF, and Cross-Encoder Reranking.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-engineering-part-3-rag-pipelines&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Engineering</category><category>RAG</category><category>Vector Databases</category><category>Embeddings</category><category>Search</category></item><item><title>AI Engineering Part 2: Prompt Engineering, Context Windows &amp; Structured Outputs</title><link>https://samuelolubukun.com/blogs/ai-engineering-part-2-llm-prompts/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-engineering-part-2-llm-prompts/</guid><description>Part 2 of our AI Engineering masterclass series. Explore advanced Prompt Engineering (CoT, Tree-of-Thoughts), Tokenizer mechanics, Context Window dynamics, and guaranteed Structured JSON Outputs with Zod and Pydantic.</description><pubDate>Sun, 29 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1555066931-4365d14bab8c?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Engineering Part 2: Prompt Engineering, Context Windows &amp; Structured Outputs&quot; /&gt;&lt;p&gt;Part 2 of our AI Engineering masterclass series. Explore advanced Prompt Engineering (CoT, Tree-of-Thoughts), Tokenizer mechanics, Context Window dynamics, and guaranteed Structured JSON Outputs with Zod and Pydantic.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-engineering-part-2-llm-prompts&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Engineering</category><category>LLMs</category><category>Prompt Engineering</category><category>JSON</category><category>Structured Output</category></item><item><title>AI Engineering Part 1: Fundamentals of Foundation Models</title><link>https://samuelolubukun.com/blogs/ai-engineering-part-1-fundamentals/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ai-engineering-part-1-fundamentals/</guid><description>The first in a 5-part masterclass series on AI Engineering. Deep dive into Foundation Model architectures, Pre-training vs SFT vs RLHF/DPO, GPU VRAM calculations, Quantization (GGUF, AWQ), and Build vs Buy.</description><pubDate>Wed, 25 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1620712943543-bcc4688e7485?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;AI Engineering Part 1: Fundamentals of Foundation Models&quot; /&gt;&lt;p&gt;The first in a 5-part masterclass series on AI Engineering. Deep dive into Foundation Model architectures, Pre-training vs SFT vs RLHF/DPO, GPU VRAM calculations, Quantization (GGUF, AWQ), and Build vs Buy.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ai-engineering-part-1-fundamentals&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI Engineering</category><category>LLMs</category><category>Machine Learning</category><category>Foundation Models</category></item><item><title>Designing Data-Intensive Applications Part 5: The Future of Data Systems</title><link>https://samuelolubukun.com/blogs/ddia-part-5-future-data-systems/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ddia-part-5-future-data-systems/</guid><description>The grand finale of our DDIA masterclass series. We synthesize the entire book to explore Unbundling the Database, Derived Data vs Source of Truth, Lambda/Kappa architectures, End-to-End Correctness, and Data Ethics.</description><pubDate>Sat, 21 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1451187580459-43490279c0fa?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Designing Data-Intensive Applications Part 5: The Future of Data Systems&quot; /&gt;&lt;p&gt;The grand finale of our DDIA masterclass series. We synthesize the entire book to explore Unbundling the Database, Derived Data vs Source of Truth, Lambda/Kappa architectures, End-to-End Correctness, and Data Ethics.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ddia-part-5-future-data-systems&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>System Design</category><category>Databases</category><category>Data Engineering</category><category>Architecture</category><category>Future</category></item><item><title>Designing Data-Intensive Applications Part 4: Batch &amp; Stream Processing</title><link>https://samuelolubukun.com/blogs/ddia-part-4-batch-stream-processing/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ddia-part-4-batch-stream-processing/</guid><description>Part 4 of our DDIA masterclass series. Explore MapReduce, Spark, Distributed Join Algorithms, Log-Based Stream Processing (Apache Kafka), Event Sourcing, and Change Data Capture (CDC).</description><pubDate>Tue, 17 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1551288049-bebda4e38f71?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Designing Data-Intensive Applications Part 4: Batch &amp; Stream Processing&quot; /&gt;&lt;p&gt;Part 4 of our DDIA masterclass series. Explore MapReduce, Spark, Distributed Join Algorithms, Log-Based Stream Processing (Apache Kafka), Event Sourcing, and Change Data Capture (CDC).&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ddia-part-4-batch-stream-processing&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>System Design</category><category>Databases</category><category>Data Engineering</category><category>Stream Processing</category><category>Kafka</category></item><item><title>Designing Data-Intensive Applications Part 3: Transactions &amp; Consistency</title><link>https://samuelolubukun.com/blogs/ddia-part-3-transactions/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ddia-part-3-transactions/</guid><description>Part 3 of our DDIA masterclass series. Delve into ACID properties, MVCC, Weak Isolation Levels, Concurrency Bugs (Write Skew, Phantoms), Two-Phase Commit (2PC), and Distributed Consensus.</description><pubDate>Fri, 13 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1526374965328-7f61d4dc18c5?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Designing Data-Intensive Applications Part 3: Transactions &amp; Consistency&quot; /&gt;&lt;p&gt;Part 3 of our DDIA masterclass series. Delve into ACID properties, MVCC, Weak Isolation Levels, Concurrency Bugs (Write Skew, Phantoms), Two-Phase Commit (2PC), and Distributed Consensus.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ddia-part-3-transactions&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>System Design</category><category>Databases</category><category>Data Engineering</category><category>Transactions</category></item><item><title>Designing Data-Intensive Applications Part 2: Distributed Data</title><link>https://samuelolubukun.com/blogs/ddia-part-2-distributed-data/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ddia-part-2-distributed-data/</guid><description>Part 2 of our DDIA masterclass series. Explore the deep mechanics of Distributed Data: Single-Leader, Multi-Leader, Leaderless Replication, Quorum Math, Replication Lag anomalies, and Partitioning.</description><pubDate>Mon, 09 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1544197150-b99a580bb7a8?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Designing Data-Intensive Applications Part 2: Distributed Data&quot; /&gt;&lt;p&gt;Part 2 of our DDIA masterclass series. Explore the deep mechanics of Distributed Data: Single-Leader, Multi-Leader, Leaderless Replication, Quorum Math, Replication Lag anomalies, and Partitioning.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ddia-part-2-distributed-data&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>System Design</category><category>Databases</category><category>Data Engineering</category><category>Distributed Systems</category></item><item><title>Designing Data-Intensive Applications Part 1: Foundations of Data Systems</title><link>https://samuelolubukun.com/blogs/ddia-part-1-foundations/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/ddia-part-1-foundations/</guid><description>The first in a 5-part masterclass series on Designing Data-Intensive Applications. Deep dive into Reliability, Scalability, Maintainability, Data Models (Relational, Document, Graph), and Storage Engines (LSM-trees vs B-trees).</description><pubDate>Thu, 05 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1558494949-ef010cbdcc31?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Designing Data-Intensive Applications Part 1: Foundations of Data Systems&quot; /&gt;&lt;p&gt;The first in a 5-part masterclass series on Designing Data-Intensive Applications. Deep dive into Reliability, Scalability, Maintainability, Data Models (Relational, Document, Graph), and Storage Engines (LSM-trees vs B-trees).&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/ddia-part-1-foundations&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>System Design</category><category>Databases</category><category>Data Engineering</category><category>Architecture</category></item><item><title>Decoding &apos;Attention Is All You Need&apos;: The Paper That Changed AI Forever</title><link>https://samuelolubukun.com/blogs/attention-is-all-you-need-explained/</link><guid isPermaLink="true">https://samuelolubukun.com/blogs/attention-is-all-you-need-explained/</guid><description>A comprehensive deep dive into the Transformer architecture from the groundbreaking &apos;Attention Is All You Need&apos; paper. Learn about Self-Attention, Multi-Head Attention, Positional Encoding, and why Transformers revolutionized NLP.</description><pubDate>Sun, 01 Jun 2025 00:00:00 GMT</pubDate><content:encoded>&lt;img src=&quot;https://images.unsplash.com/photo-1620712943543-bcc4688e7485?q=80&amp;w=2000&amp;auto=format&amp;fit=crop&quot; alt=&quot;Decoding &apos;Attention Is All You Need&apos;: The Paper That Changed AI Forever&quot; /&gt;&lt;p&gt;A comprehensive deep dive into the Transformer architecture from the groundbreaking &apos;Attention Is All You Need&apos; paper. Learn about Self-Attention, Multi-Head Attention, Positional Encoding, and why Transformers revolutionized NLP.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;https://samuelolubukun.com/blogs/attention-is-all-you-need-explained&quot;&gt;Read more&lt;/a&gt;&lt;/p&gt;</content:encoded><category>AI</category><category>Machine Learning</category><category>Transformers</category><category>NLP</category><category>Deep Learning</category></item></channel></rss>