Quietly Guides
Long-form guides on AI data privacy, enterprise security, and Linux-first workflows. We publish here occasionally— for the latest product details, see Download and Solutions.
Awareness · 11 min
A practical ChatGPT offline alternative for students, writers, and professionals: private on-device chat without coding, what hardware you need, and how Quietly Chat keeps prompts off the cloud.
Aug 24, 2026 · 11 min read
Awareness · 12 min
How local RAG gives an offline AI IDE surgical repo context without uploading code: indexing under .quietly/, .gitignore/.quietignore, cursor-aware retrieval, and a privacy checklist for teams.
Aug 23, 2026 · 12 min read
Comparison · 13 min
A hardware-honest shortlist of open coding LLMs for offline IDEs: which model classes win for 8GB, 16GB, and 24GB, how to judge agent readiness, and how to load them in Quietly without cloud APIs.
Aug 22, 2026 · 13 min read
A practical VRAM budget for offline AI coding: which GGUF model sizes fit 8GB, 16GB, and 24GB GPUs, how KV cache eats memory, and how to pick a Quietly-ready stack that stays fast.
Aug 21, 2026 · 12 min read
What offline AI chat is, why people switch from cloud ChatGPT-style bots, and how Quietly runs private on-device conversations on Windows, macOS, and Linux.
Aug 20, 2026 · 11 min read
Awareness · 9 min
CTO-grade threat modeling for AI coding tools: what can leak, why it leaks, and how local AI changes the security boundary for proprietary code.
May 06, 2026 · 9 min read
Awareness · 8 min
A cost-intent breakdown for developers and teams: subscriptions, latency tax, data risk, and why local execution can be the best value AI IDE.
May 06, 2026 · 8 min read
Comparison · 10 min
A practical shortlist for privacy-first developers: compare RAM needs, latency, and offline guarantees for popular local AI coding workflows (including Quietly).
May 06, 2026 · 10 min read
Comparison · 9 min
A personal, technical migration story: why Arch Linux + a local-first AI workflow feels faster, calmer, and more private for day-to-day development.
A step-by-step, Linux-first workflow for local AI coding: offline defaults, network boundaries, model runtimes, and a practical setup checklist for GNOME + Arch.
May 06, 2026 · 11 min read