AI memory explained: what Perplexity, ChatGPT, Pieces, and Claude remember (and forget)
Discover the different types of AI memory, how they work, key use cases, and the best prompting approaches to get accurate, contextaware responses
Stay updated with the latest developments in Artificial Intelligence
Discover the different types of AI memory, how they work, key use cases, and the best prompting approaches to get accurate, contextaware responses
iscover how Pieces helps developers carry context seamlessly across browser, IDE, CLI, and desktop. From snippet capture to Copilotpowered reuse, learn how to eliminate lost time, preserve continuity, and stay in flow throughout your workflow.
Tired of losing focus while coding? Discover how Pieces helps you stay in flow, remember what matters, and move faster from idea to execution.
Explore the best AI code completion tools of 2025. Honest reviews of Pieces, Codeium, Copilot, Windsurf, ProxyAI, and Augment for real workflows.
AI isn’t a specialty anymore, it’s the foundation of modern software. In this guide, Ali breaks down the best programming languages for AI in 2025 and how your choice can make or break speed, workflow, and realworld result
Discover 10 questions no other AI can answer because only Pieces layers true memory and context across your work. OnlyInPieces
Why traditional documentation breaks down and how long term memory systems are changing how we preserve and transfer engineering knowledge.
Seed Diffusion explores how we’re pushing large language models toward a parallel future where AI learns faster, works smarter, and opens doors to entirely new possibilities
Inside our ML team’s weeklong debate on OpenAI’s newly opensourced GPTOSS models versus Google’s Gemma3N architecture, from kernels and quantization tricks to efficiency, multimodality, and the quiet arrival of local AI’s future.
We put the top AI tools for Python coding to the test, not just to see which writes code the fastest, but which actually feels good to use, fits into your workflow, and makes building in Python more enjoyable.
We’ve all heard it — “the future of AI is in the cloud.” But the real story is that the future might be smaller, closer, and more personal. From Small Language Models (SLMs) to localfirst AI, agentic constellations, and even bioinspired designs, the next big leap in AI isn’t about scale.
Local AI isn’t a distant dream, it’s already here. From nanomodels running offline to industrywide shifts toward privacyfirst architecture, discover why real breakthroughs are happening ondevice, not in the cloud.
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