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Received β€” 17 August 2026 ⏭ Towards Data Science

Webwright: Why AI Web Agents Should Write Code, Not Click

17 August 2026 at 16:30

For years, web agents have worked one click at a timeβ€”and often fallen apart on long tasks. Microsoft Research’s Webwright makes a different bet: give the model a terminal and let it write the program instead. On long-horizon tasks, the same GPT-5.4 model jumps from 33.5% to 60.1% success. And instead of leaving behind a click trace, it leaves something you can actually use again: a command-line tool.

The post Webwright: Why AI Web Agents Should Write Code, Not Click appeared first on Towards Data Science.

Loop Engineering for RAG: The Small Loops Inside Each Step, the Big Loops Across the Pipeline

17 August 2026 at 12:00

Enterprise Document Intelligence [Vol.1 #13bis] - The four bricks return useful results most of the time. Loop engineering is what the system does the rest of the time: when retrieval misses, when generation fails the schema, when the listing comes back incomplete, when an API call times out. Three control surfaces (trigger, termination, recovery) and one rule that separates a useful loop from a spinning one

The post Loop Engineering for RAG: The Small Loops Inside Each Step, the Big Loops Across the Pipeline appeared first on Towards Data Science.

Received β€” 16 August 2026 ⏭ Towards Data Science

Designing a Persistent Knowledge Layer That Refuses to Guess

16 August 2026 at 15:00

RAG Retrieves, It Never Remembers. A vendor-neutral blueprint for applications that accumulate understanding. Includes a complete Azure-native implementation (Microsoft Foundry, Azure AI Search, Cosmos DB,Β FastAPI) mapped to a property-insurance corpus.Β 

The post Designing a Persistent Knowledge Layer That Refuses to Guess appeared first on Towards Data Science.

Received β€” 15 August 2026 ⏭ Towards Data Science
Received β€” 14 August 2026 ⏭ Towards Data Science

My Model Was Cheating on Its Own Test

14 August 2026 at 13:30

A preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points of R squared it cheated its way to

The post My Model Was Cheating on Its Own Test appeared first on Towards Data Science.

Received β€” 13 August 2026 ⏭ Towards Data Science

How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs

13 August 2026 at 16:30

Google's Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses that skeleton for a very specific job β€” an agent-to-agent hand-off of pre-tokenized integer arrays between three Qwen2.5-Coder models (7B, 3B, 1.5B) β€” and shows the 28–37% TTFT reduction plus the one full-vocabulary equivalence check that keeps the whole thing safe.

The post How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs appeared first on Towards Data Science.

Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model

13 August 2026 at 15:00

Enterprise Document Intelligence [Vol.1 #9ter] - The pipeline from Article 9 calls a model at several steps to be sure it is right. On easy questions that is needless latency. A per-question signal routes them past the model, about two seconds saved for a keyword match.

The post Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model appeared first on Towards Data Science.

Received β€” 12 August 2026 ⏭ Towards Data Science

Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From

12 August 2026 at 16:30

Enterprise Document Intelligence [Vol.1 #5nonies] - Nature, plan, execute, synthesize: closing brick 1 with a dispatcher that reads each PDF’s nature and picks the method that fits, fitz, Docling, PaddleOCR, EasyOCR, MinerU or Surya, then folds the outputs into one corpus

The post Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From appeared first on Towards Data Science.

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