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LAUNCH ETA: 2026 May

  • Re-evaluating Ollama's LLM Performance on Apple Silicon

    ·5 min read

    Ollama’s local LLM performance on Apple Silicon reveals that only a subset of models delivers practical latency for short-response tasks. The results highlight execution …

  • Cheap Local, Expensive Global Correctness

    ·9 min read

    LLMs reduce the cost of producing plausible code, but they do not reduce the cost of understanding system invariants. Engineering teams need deliberate friction where correctness …

  • Trendslop: Why LLMs Struggle with Strategy

    ·6 min read

    A recent study reveals that large language models, when tasked with generating strategic advice, tend to produce generic, consensus-aligned recommendations rather than …

  • Embedding Models on Affordable Cloud VMs and Apple Silicon

    ·13 min read

    A benchmark of CPU-only embedding inference from low cost DigitalOcean droplets to Apple Silicon, focusing on runtime overhead, CPU tier effects, and scaling limits.

  • Security Gating as a Control Problem

    ·10 min read

    A practical approach to securing LLM agents by treating tool invocation as a control boundary. Why fail-closed gates, monotonic risk checks, and adversarial benchmarks are more …

  • GPT-OSS-20B Sampling & Prompting for Style Control

    ·9 min read

    Best practices for sampling parameters and system prompt design to optimize style compliance and throughput with local LLMs like GPT-OSS-20B.

  • Execution Is Cheaper, Comprehension Is Not

    ·7 min read

    LLMs have collapsed the cost of execution, but verification, comprehension, and ownership remain the binding constraints in software engineering and adjacent knowledge work.

  • LLM Fingerprints v1.5: Redistribution with 4chan Data

    ·8 min read

    The latest nullbench run shows no step-function gains in base model capability. Instead, fine-tuning, abliteration, and long-context extensions primarily redistribute behavior …

  • Agentic AI Raises The Floor More Than The Ceiling

    ·9 min read

    AI agents make easy software tasks cheaper but don’t automate hard engineering. This post tries to explain why autonomy claims overreach and where AI actually helps.

  • 2025 Learnings on LLMs and Software Work

    ·3 min read

    2025 suggests that the gap between expectations and measured outcomes around LLMs in software engineering is no longer subtle. Large investments and confident narratives imply …