A Day in the Life of a Data Scientist in 2026
, My Day Looked Completely Different Believe it or not, two years ago, I was still writing and debugging code daily. Line by line. Practically slamming my head against the…
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MiniCPM-o 4.5: A 9B Model That Can See, Hear, and Speak at the Same Time
Most multimodal AI models today work in turns. You feed them a video, wait for them to process it, and then get a response. While this works well for traditional…
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Prompt Engineering Is Solved—Prompt Management Isn’t
TL;DR variable rename passes Git, greenlights your mocked test suite, and gets approved in code review—right up until it crashes every real production call the moment it executes. This failure…
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Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It
and expensive. The fast parser misses the table the answer lives in. Run the heavy one on every page of a 200-page report and you pay for 200 pages to…
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How to Work Effectively with GPT-5.6
, I will give my first impressions of the newest OpenAI model, GPT-5.6. The model was released a few days ago, and I’ve gotten the chance to test it extensively…
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Context Engineering Isn’t Enough — A Loop Engineering Experiment With No LLM Inside the Loop
The Scope: This isn’t a benchmark pitting agent frameworks against each other, nor does it claim this controller is “smarter.” It claims something narrower and much more defensible: that failure…
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Context Engineering for RAG Question Parsing: From a Raw Question to Typed Fields That Steer Retrieval and Generation
talk about context engineering today, they usually mean retrieving the right context from a document: chunk selection, hybrid search, reranking, TOC-aware retrieval. That is one half of the story. The…
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How Much Does It Actually Cost to Run a Local LLM? (Euros per Million Tokens, Measured)
, so it’s basically free.” I’ve said that, you’ve probably said that, and it’s the kind of claim that sounds true until someone measures it. So I measured it. The…
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Agentic RAG: Let the Agent Search
application we build is a RAG app. The recipe is simple: chunk, embed, retrieve, then answer. It looks clean on paper. But once you use it on real cases, things…
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Long Context Isn’t Free — I Built a Safe Prompt-Pruning Layer That Makes LLM Systems Work
I’ve worked on, conversation state tends to grow quickly over time. It’s common to resend large portions of the history on each turn—including older tool outputs, repeated RAG retrievals, and…
