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- 23articles · 30d
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- Aug 15, 2026earliest in window
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News
Loop Engineering for RAG: The Small Loops Inside Each Step, the Big Loops Across the Pipeline
4+ week, 3+ hour ago (1680+ words) A one-shot pipeline commits to its first try: parse once, retrieve once, generate once, return whatever comes out. When retrieval comes back empty or the answer is half-formed, there is no second chance. A loop gives the pipeline one: notice…...
Context Engineering Is Changing. Here???s What It Means for Data Scientists
2+ week, 18+ hour ago (1470+ words) How to apply the latest context engineering guidelines to your day-to-day data science work There are so many positive sides that come with using systems like Claude; all the repetitive, routine coding gets automated, researching is quicker, and debugging becomes…...
4 Claude Skills Every Data Scientist Needs in 2026
2+ week, 1+ day ago (1306+ words) Blueconic sets this cookie as a unique identifier for the BlueConic profile. Four skills worth adding to your workflow today if you don't want to be left behind A couple months ago I wrote about 3 Claude skills every data scientist…...
Why We Fine-Tuned SigLip (And Why That???s Not Always the Right Call)
3+ week, 2+ day ago (833+ words) LoRA fine-tuning solved our under-labeling problem. Whether it makes sense for you depends on three questions. Image classifiers can be built in many ways. The modern default approach is to run images through a third-party API which internally uses a…...
Estimating from No Data: Deriving a Continuous Score from Categories
3+ week, 2+ day ago (938+ words) A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training To be able to illustrate the work, I developed a toy example, which is a non-linear but deterministic…...