Towards Data Science

Turning a demo agent into something that can keep real booking data The post Building a Proper Backend for My LangGraph AI Agent appeared first on Towards Data Science .

Enterprise Document Intelligence [Vol.1 #14B] - No shared fields means no index to build. One summary line per file plus each file’s own table of contents, and retrieval routes down two levels The post Multi-Document RAG: A Folder of Unrelated PDFs Is One Long Document with a Nested Outline appeared first on Towards Data Science .

LoRA fine-tuning solved our under-labeling problem. Whether it makes sense for you depends on three questions. The post Why We Fine-Tuned SigLip (And Why That’s Not Always the Right Call) appeared first on Towards Data Science .

Turning Codex from an interactive assistant into a programmable automation component The post Running Codex as a Headless Agent appeared first on Towards Data Science .

A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training The post Estimating from No Data: Deriving a Continuous Score from Categories appeared first on Towards Data Science .

Enterprise Document Intelligence [Vol.1 #7sexies] - The unit of retrieval doesn’t have to be a page or a paragraph. When the corpus carries tables, each body row with its column headers is a chunk in its own right, and it’s often the one row the reader asked about The post Retrieve One Row from a Table, Not the Whole Table: Row-Level Chunks for RAG appeared first on Towards Data Science .

Dimensions are one of the two main object types in dimensional modelling. But what are the different types of dimensions? And how can you use them? The post The Types of Dimensions in a Star Schema, and How to Use Them appeared first on Towards Data Science .

AI systems should not automate a decision simply because they can provide a prediction. A decision system should consider how uncertain the prediction is and defer if a mistake would be costly. The post Bayesian Guardrails for AI Decisions: Measuring Uncertainty Before Automating Decisions appeared first on Towards Data Science .

Learning about Farkas' lemma and how it can inform Benders decomposition to learn from infeasibility, applied to the capacitated facility location problem. The post How Benders Decomposition Works, Part II: Feasibility Cuts appeared first on Towards Data Science .

Improve your proficiency with Claude Code. The post How to Effectively Align Your Intent with Claude Code appeared first on Towards Data Science .

What a production incident taught me about trusting a model to judge another model's work The post The LLM Judge That Kept Agreeing With Itself appeared first on Towards Data Science .

Enterprise Document Intelligence [Vol.1 #14A] - Three questions tell you which shape a document collection has, and each shape wants a different architecture The post Three Kinds of RAG Corpus, and What It Costs to Build for the Wrong One appeared first on Towards Data Science .

A hands-on guide to fine-tuning LLMs for the real world The post How to Fine-Tune an LLM: An End-to-End Guide appeared first on Towards Data Science .

Why retrieval quality should be a property of the system, not of the question's wording? Rebuilding knowledge layer with graph traversal on every query, bitemporal edges, and two-threshold entity resolution. The post Making the Knowledge Layer a Graph You Actually Traverse appeared first on Towards Data Science .

A production account of scaling an enterprise integration pipeline from 500 to 8,000 events per second, and the two correctness guarantees the throughput work was never allowed to trade away. The post How to Scale an Integration Pipeline Without Breaking Correctness appeared first on Towards Data Science .

A controlled comparison of a top-5 RAG pipeline and a full 127,000 token prompt on the same 12 questions, same system prompt and same model. Graded blind on correctness, completeness and grounding. The post Kimi K3’s 1M Token Context Window vs. RAG: Cost, Latency and Answer Quality appeared first on Towards Data Science .

People can accept tradeoffs when they see value — but if they don’t, what happens? The post Understanding Anti-AI Public Opinion appeared first on Towards Data Science .

Conceptual overview and walkthrough of a solution approach in Python The post Jigsaw Jeeves: Building a Puzzle Assistant using Computer Vision appeared first on Towards Data Science .

Building the Responsible AI, security, and governance layers required for enterprise-ready agents The post From Prototype to Production: The Architecture Behind Secure & Governed AI Agents appeared first on Towards Data Science .

5 principles that determine whether an agent system succeeds in production, explained through one I built for a $100M+ company. The post Building Enterprise Agent Systems that People can Trust, Verify and Improve appeared first on Towards Data Science .