Cases & Practice

A practical playbook for AI startups: tech stack, unit economics, a 4-week MVP, and the mistakes that reliably kill them. Concrete numbers and recommendations.

SaaS ToS structure, LLM prompts for each section, typical lawyer edits by section, and a pre-publication checklist.

Five techniques to cut LLM API costs: prompt caching, smart routing, Batch API, semantic caching, model downsizing. Before/after tables, prompts, and configs.

How I built an ambient AI agent for macOS with Tauri 2.0, Swift, and a local LLM. Architecture deep dive, real data from 5 days of usage, and why it became open source.

How to automate the research step of cold outreach (20-40 min/lead) with AI: tool stack, two-step prompts, deliverability setup, and email examples.

4 patterns of AI slop with real production examples, a 10-point checklist, and automation tools for reviewing AI-generated code.

VLESS-based VPN through CDN, plus Telegram and WhatsApp proxies. Subscription management, payments, setup - all inside Telegram. Servers in Amsterdam and Saint Petersburg.

Over 76% of developers hit high AI hallucination rates. We break down action hallucinations in Claude Code and Gemini CLI - and how to catch them.

How we extracted 7 reusable packages from 76 production Edge Functions: error handling, resilience, auth, testing, and more.

Where AI breaks on Flutter: build_runner, Riverpod, widget trees, Maestro tests. Production lessons after 6 months on JourneyBay.