A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop
The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science.
Structured Language Model Generation with Outlines
Outlines is an open-source library that introduces deterministic certainty into LLMs' output generation process for better, more reliable generation of structured outputs.
Building Models in Two Worlds: From Latent Constructs to Behavioral Signals
My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything around them did.
The post Building Models in Two Worlds: From Latent Constructs to Behavioral Signals appeared first on Towards Data Science.
5 Real-World SQL Projects to Build Your Data Portfolio
Build a stronger data portfolio with these practical SQL projects covering customer churn, data warehousing, sales analysis, banking segmentation, and healthcare analytics.
The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices
A framework for aligning agentic AI with enterprise intent to ensure consistent scenario‑wide autonomous behavior.
The post The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices appeared first on Towards Data Science.
Handling Imbalanced Classification: What Works Better Than SMOTE
Most real-world classification problems are imbalanced. Fraud, disease, churn, and defects are rare by nature. Standard classifiers chase accuracy, so they quietly ignore the very class you care about. For years, SMOTE was the reflex fix that everyone reached for first. But SMOTE often fails on the ...
Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work
LLMs don’t fail because they forget—they fail because they remember too much. As conversations grow, prompts accumulate redundant and low-value tokens, driving up cost and latency while silently degrading output quality. This article introduces a deterministic prompt-pruning layer that reduces token...
I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer
Building a production-ready RSS pipeline with Python, Docker, PostgreSQL, and Kestra
The post I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer appeared first on Towards Data Science.
PySpark for Beginners: Building Intermediate-Level Skills
A practical next step into partitions, shuffles, joins, caching, and execution plans.
The post PySpark for Beginners: Building Intermediate-Level Skills appeared first on Towards Data Science.
Local Video Summarization Pipeline: Processing Frames with SmolVLM2-2.2B
SmolVLM2-2.2B sits at a genuinely useful point on the capability-size trade-off curve; small enough to run on a single consumer GPU, capable enough to produce video summaries that are actually useful for real workflows.
What our over-dependence on external consulting teaches us about delegating our minds to machines
The post The Big Con of Agentic AI appeared first on Towards Data Science.
For twelve days, the best AI models on the planet existed and almost nobody could touch them. That ends now! GPT-5.6 Sol, Terra, and Luna go public today! The models are accessible by all users (no subscription required) This is the full breakdown of what’s on offer: three models, four prices, one p...
Loop Engineering for AI Agents: How /loop is Changing AI Workflows
AI agents are moving from one-time assistants to persistent workers that can repeat tasks, monitor changes, run checks, update workflows, and return with results. Instead of prompting an LLM once and deciding every next step manually, teams can now use AI agents that keep working (on a Loop) until a...
This article covers the full path from zero to a running private research assistant on Telegram, including configuring the context length correctly, connecting the channel, enabling web search, and deploying it headlessly in Docker.
DeepSeek DSpark: The Speculative Decoding Trick Behind 400% Faster LLM
DeepSeek’s new DSpark module brings speculative decoding to DeepSeek-V4. It might look like a niche inference tweak, but in production it boosted per-user generation speed by 60 to 85 percent with no drop in model quality. What sets DSpark apart is that it tackles two longstanding problems at once, ...
Map AI value, design workflows, redefine talent, upgrade the executive team, and measure the business impact.
The post Redesign Work Before You Add More AI Agents appeared first on Towards Data Science.
How to decide when an AI agent should act on its own by using cost asymmetry instead of a fixed confidence cutoff
The post The Threshold Is a Price, Not a Percentage appeared first on Towards Data Science.
Measuring Structure Stability of Econometric Models
The simplest most important idea for time series forecasting
The post Measuring Structure Stability of Econometric Models appeared first on Towards Data Science.
Proxy-Pointer RAG: Temporal Reasoning Without Semantic Precompilation
A technical comparison of Proxy-Pointer and LLM-Wiki
The post Proxy-Pointer RAG: Temporal Reasoning Without Semantic Precompilation appeared first on Towards Data Science.