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Parsing JSON from Thinking-Model APIs

When you request structured data from a reasoning model using a JSON mime type, the response often arrives split across several content parts rather than sitting neatly in a single text block. This breaks standard assumptions in ingestion pipelines. Developers usually expect the model to return a single text payload starting with an opening brace. Reasoning models, however, routinely prepend…

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Chalkboard and avatar for ai agents

Because I find it difficult to read the textual output of agents after each modification or planning, and relate everything to the big picture, I built this simple application (with the help of Claude…

Run DeepSeek V4 on Your Own Hardware With DwarfStar, the Redis Creator's New Inference Engine

The creator of Redis thinks your old GPU is not obsolete. Salvatore Sanfilippo, better known as antirez, published a project called DwarfStar (the repo is antirez/ds4 ) that runs DeepSeek V4 Flash…

  • DeepSeek V4 now runnable on consumer hardware via DwarfStar inference engine.
  • Created by Redis inventor antirez, DwarfStar is a native C program with no GGML dependency.
  • Supports Metal, CUDA, and ROCm backends for optimal performance on various hardware.

Founder video: a discovery lesson

A founder lesson from discovery calls. Early on, I assumed the bottleneck was the agent. Smarter models, better prompting, better tools — that was the plan everyone was chasing.

  • Founder's perspective reveals AI agents' compatibility issue with software interfaces.
  • Developers report challenges integrating AI agents with existing software user interfaces.
  • Strategy pivots to constructing seamless interface bridging software and agents.

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