Strategy, product, engineering, finance, marketing — one founder, AI as the team.
A complete AI-powered content production pipeline: from keyword research to publication. Prompts, tools, quality metrics, and exact cost figures for each stage.
How to generate production-ready PRDs with LLMs: document structure, prompts for each section, real output examples, and a ready-to-use template.
How to test each of the 9 Business Model Canvas blocks with AI prompts. Common weak spots, analysis examples, and ready-to-use prompts for Claude.
20 standard investor questions with Claude prompts and answer templates. Pitch meeting prep with AI: unit economics, TAM, competitors, go-to-market.
Calculating TAM, SAM, and SOM for a startup with AI: top-down and bottom-up formulas, ready-to-use prompts, a SaaS product example, benchmark tables, and common mistakes.
A checklist for AI code review across 4 categories with prompts for each stage, real-world finding examples, and a CI/CD pipeline integration template.
How to build an event taxonomy for a SaaS product with AI: naming conventions, taxonomy structure, prompts for generating 30 events, and a ready-to-use tracking plan.
A step-by-step process for extracting Jobs-to-be-Done from user reviews using an LLM. Analysis prompts, clustering, output examples, and a ready-to-use workflow.
Methodology for finding a product's magic number: cohort analysis in SQL, AI correlation of user actions with 30-day retention, A/B test validation. Ready-to-use queries and prompts.
How to apply test-driven development with Claude Code: prompts, test-first workflow, approach comparison. A practical guide with code examples.
Generate high-converting ad copy with AI using PAS, AIDA, BAB, FAB, and 4U frameworks. Ready-made prompts and before/after examples included.
Model a cap table with AI: dilution formulas, Pre-Seed to Series A calculations, prompts, and founder dilution analysis across 3 rounds.
Build a 13-week cash flow forecast: table structure, formulas, scenario analysis, and AI prompts for automation. Free template included.
Build an AI-generated 7-email drip sequence for SaaS trial-to-paid conversion. Prompts, timing, templates, and metrics included.
Pitch deck narrative framework: AI prompts for every slide, transition logic, and sample copy. Build a presentation that survives 60 seconds.
How to define your Ideal Customer Profile using AI: analysis prompts, ICP card templates, scoring models, and a step-by-step pipeline from data to segments.
How to build a structured interview kit with AI: competency-based questions, candidate scorecards, and debrief agendas. Prompts, templates, and a step-by-step process.
How to use LLMs to write job descriptions that attract qualified specialists, not keyword-stuffers. Prompts, templates, before/after examples.
How to build a prompt management system: versioning, testing, A/B deployment, regression monitoring. Practical patterns and tools for production.
Multi-agent system architecture for startups: orchestration patterns, task routing, agent specialization, code examples, and configuration.
A slash skill for Claude Code that controls how aggressively the AI challenges your decisions. From silent executor to full devil's advocate.
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 build an AI-powered cold outreach pipeline with automated contact research. Tool stack, prompts, deliverability setup, and real email examples.
Step-by-step SaaS unit economics calculation using Claude: LTV, CAC, Payback Period formulas, benchmarks, sensitivity analysis, and ready-to-use prompts.
How to turn one article into 5 platform-adapted formats in 40 minutes using LLMs. Prompts, n8n + Claude API automation pipeline, and repurposing economics.
How to use LLM-as-Judge for automated LLM output evaluation. Metrics, judge prompts, DeepEval, Langfuse integration, and CI/CD pipeline setup.
How to use LLMs to generate Standard Operating Procedures from screen recordings, chat logs, and config files. Prompts, templates, and a step-by-step process.
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.
Maestro for Flutter apps: bilingual regex matchers, iOS workarounds, performance gates, AI assertions. Patterns and pitfalls from a production project.
Multi-provider LLM architecture with LiteLLM: fallback chains, task-based routing, cost balancing across providers. Circuit breaker patterns, monitoring, configuration examples.
How we built a resilience layer for edge functions: circuit breaker, retry with jitter, and fail-open rate limiting. Real production code, zero dependencies.
How to structure context for LLMs: 6 layers, 4 strategies, persistence, subagents. A practical guide with real-world examples from Claude Code.
How we extracted 7 reusable packages from 76 production Edge Functions: error handling, resilience, auth, testing, and more.
How to run two auth providers in one app for data residency compliance. JWT token chaining, AuthBridge syncing 6 systems, Completer-lock, and SyncRecovery.
Practical guide to Langfuse: LLM call tracing, prompt management, cost tracking, evaluations. Self-hosted in 15 minutes, production patterns.
How to build and run custom MCP servers. Real-world patterns for error handling, fallback chains, monitoring, and security from production experience.
CLI tool to sync MCP server configs across Claude Code, Cursor, Codex, and Gemini. One source of truth, automatic format conversion, backups.
Open-source framework for parallel AI consultations with OpenAI, Gemini, Qwen, and DeepSeek from Claude Code. 3 MCP servers, fallback chains, zero API keys.
Why AI assistants stumble on Flutter. Real experience: build_runner, Riverpod, widget trees, testing. What works, what doesn't.