PTP/1.0 — Prompt Transport Protocol
A playful mock protocol imagines prompts as transport packets, turning generative reconstruction into a deadpan internet standard.
24 posts
A playful mock protocol imagines prompts as transport packets, turning generative reconstruction into a deadpan internet standard.
Google Stitch is powerful, but the post argues that faster UI generation changes design work rather than eliminating design judgment.
Continuous Autoregressive Language Models challenge the token-by-token bottleneck and hint at a different future for language generation.
AI-generated tests can look reassuring while proving very little, exposing a dangerous gap between green checkmarks and real verification.
Apple Silicon's reverse-engineered Neural Engine revives the old personal-computing spirit of manuals, memory maps, and productive trespass.
COBOL modernization is not just a technical story; it threatens the consulting toll booths built around legacy systems.
Prompting is outgrowing folklore and becoming infrastructure: specifications, patterns, evaluation, and operational discipline.
PageIndex.ai makes the case for document-aware retrieval that respects pages, structure, and references instead of blindly chunking PDFs.
Meta-prompting treats the prompt itself as a draft to debug, producing clearer goals and fewer disappointing model outputs.
As AI writes more code, naming becomes even more central: the human craft shifts toward concepts, boundaries, and meaning.
Context engineering and requirements engineering converge, suggesting better ways to specify AI-assisted software before code is written.
Prompt packs can make general models behave like specialists, but the post asks where scaffolding ends and real specialization begins.
Google's DORA findings suggest AI amplifies team quality: strong practices get stronger, broken processes get louder.
Neural texture compression promises richer game graphics with lower memory costs, changing the pipeline for artists and developers.
A developer-focused guide to choosing between OpenAI's Chat Completions, Responses, and Assistants APIs in 2025.
From Cray supercomputers to Mac Studio clusters, the post traces the strange continuity of DIY AI horsepower.
A bridge between RAG, OpenAI tools, Anthropic MCP, and local Ollama models for more grounded AI systems.
DeepSeek's mathematical optimizations show how model design and NVIDIA communication infrastructure meet inside efficient training.
Project Strawberry and the physical weight of the internet meet in a playful reflection on knowledge, storage, and scale.
OpenAI's Strawberry rumors are mapped onto staged AGI levels, asking what real reasoning progress would look like.
THERMOMETER targets overconfident language models, offering a way to calibrate systems that bluff too easily.
A practical introduction to KNIME and the shift from fragile spreadsheet work toward reproducible data workflows.
A practical guide to prompt engineering techniques for getting more reliable, useful behavior from large language models.
Mojo is presented as a promising language for AI and machine learning, blending Python-like usability with systems-level speed.