Background

Found on theregister.com Test driven development (TDD) produces much better results with AI coding assistants: TDD prevents a failure mode where agents write tests that verify broken behavior. When the tests exist before the code, agents cannot cheat by writing a test that simply confirms whatever

Found on theregister.com A feature regarding Geoff Huntley, his invention of the Ralph Wiggum Loop and the state of coding and agile: Developers, he argues, should now spend more time thinking about writing loops that drive coding assistants to produce better output, rather than persisting with code reviews.

Found on Daniel Lemures Blog linked by Simon Wilson At the beginning of December 2025 I found on Simon Wilsons blog a link to an interesting post of Daniel Lemure, where he describes why speed matters in science. I fully go with his arguments A common mistake is to spend a lot of time—too much

Gefunden auf heise.de: Klassisches oder agiles Prjektmanagement: Welche Faktoren führen zu Problemen? Unklare Anforderungen Unrealistische Deadlines Unkontrolliert eskalierende technische Schulden Politik und Machtkämpfe Ich finde, man sollte noch den nachfolgenden Punkt mit hinzufügen, weil er ebenfalls eine häufige Ursache von Problemen ist:

Gefunden auf heise.de. Irgendwie kann ich mich nicht dem Eindruck erwehren, dass Prof. Dr. Michael Stal diesen Sommer einiges zum Thema PyTorch gelesen hat... Zumindest hat er mit seiner Serie von Blog-Artikeln Künstliche neuronale Netze im Überblick eine lesenswerte Einführung in die Erstellung von künstliche neuronale Netze mit PyTorch gepostet:

Seit 2 August 2025 sind im Rahmen des EU AI Act die Transparenz- und Sorgfaltspflichten für generell einsetzbare KI in kraft getreten. Das ist ein guter Anlass mein englisches Blog-Posting Is it legal for AI to scrape licensed material and reproduce it in the generated output? ins deutsche zu Übersetzen und zu ergänzen. In Bezug auf KI gibt es einige wichtige rechtliche Fragestellungen, welche aktuell nahezu jeden Content-Ersteller und/oder Content-Provider betreffen:

Found on arstechnica.com How a big shift in training - from imitation learning towards reinforcement learning - led to a capability explosion of LLMs, especially with extended context and in agentic setups. It was very nice of arstechnica.com to reprint this original Timothy B. Lee posting in his

Found on blog.nilenso.com AI is a multiplier. If you are a small coefficient, you won’t see much gain. If you are a negative coefficient, expect negative gains. To make AI good, get good yourself. Found on heise.de AI revolutionizes the software development. The ones, who do not understand this

Found on theregister.com In the past few weeks in May and June 2025 Snowflake and Databricks with their acquisions of Neon and Crunchy Data followed Microsoft with their acquisition of Citus Data in 2019. Immediately after that on their Data+AI Summit Databricks launched the Lakebase transactional database service which was developed by Neom and is based on the PostgreSQL open source DBMS technology and stores all of the data on cloud blob storage:

Found on thegerister.com. DuckDB proposed DuckLake as a standard for metadata and catalogs, claims it simplifies lakehouses by using a standard SQL database for all metadata, instead of complex file-based systems, while still storing data in open formats like Parquet. It will be seen, if this makes them more reliable, faster, and easier to manage. The corresponding blog post is worth reading, because it gives a systematic view on the high level data architectures of DuckLake, Databricks, IceBerg, BigQuery and Snowflake.