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Testing Image Grounding Capabilities of Qwen3.8-Max
Qwen3.8-Max arrived with strong multimodal results, so I wanted to try something more concrete than visual Q&A: give it an image, ask for structured bounding boxes, and draw the answer back onto the pixels.
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Token Capital Efficiency
Satya Nadella recently published an excellent article on what a future firm looks like in an AI-driven economy.
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A Data Scientist RLM That Lives in Your Program
… or how to process DataFrames with RLMs and DSPy Background: Recursive Language Models After experimenting with Recursive Language Models (RLMs) since their publication, I’ve been continually impressed by the powerful simplicity of the approach.
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Auditing a Codebase for 87 cents in 50 lines of code using RLMs
Before we begin: Of course this doesn’t replace a proper (human) audit or security testing process, nor should it.
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AI’s Hedonic Treadmill vs. Task Horizon Exponentials
Originally written September 2025 - a lot has changed between now and December when I’m posting this!
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Achieving 20 percentage-point improvement in structured extraction tasks using DSPy and GEPA
There’s been lots of discussion recently on DSPy and the GEPA optimizer.
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Using DSPy to Detect Document Boundaries
DSPy is becoming increasingly popular (at least in my bubble on X) - and, in my opinion, for good reason!
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Acceleration: Notes on ‘Measuring AI Ability to Complete Long Tasks’
Link to Paper A paper released in March 2025 by researchers at Model Evaluation & Threat Research (METR) evaluated the ability of AI models to complete long-horizon tasks.
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Summarizing video transcripts with an LLM
Tools Used: bat ffmpeg llm* mlx_whisper pdftotext shot-scraper* uvx *Big thanks to @simonw for an unending flow of useful tools which makes life easier every day.
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Measuring LLM Confidence
Large Language Models (LLMs) have burst into the conversation and have already proven incredibly powerful in accelerating all sorts of knowledge work.