The archive

JourneyBay launched its ChatGPT app — search places, create trips, build day-by-day itineraries, and check visa context right in the chat. Also in other AI clients via MCP.

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.

A complete guide to Langfuse: LLM request tracing, prompt management, evaluations, cost tracking. Self-hosted and cloud. Python examples.

A practical guide to testing AI agents: unit/integration/e2e tests, eval frameworks (DeepEval 4.0, RAGAS, Promptfoo, Braintrust), metrics, CI/CD pipeline. With code examples.

A step-by-step guide to building an MCP server in Python: tools, resources, prompts, authentication, testing, and publishing. Complete working code.

A catalog of the best MCP servers: GitHub, PostgreSQL, Notion, Brave Search, Sentry, and 20 more. Categories, npm packages, setup.

An advanced guide to Claude Code: building skills, subagents, hooks, memory, and dynamic workflows. 5 ready-made skill templates, 3 agents, 2 hooks to copy.

A step-by-step guide: from a 20-line minimal agent to a multi-agent system. Claude Agent SDK, MCP, CrewAI, LangGraph, Google ADK. Full working Python code.

A complete guide to MCP (Model Context Protocol): architecture, connecting it to Claude Code and Cursor, the top 20 servers, and writing your own server in TypeScript and Python.

A comprehensive Claude API tutorial: Messages API, tool use, adaptive thinking, prompt caching, vision, streaming, batches, MCP connector, structured outputs. Examples in Python and TypeScript.

A complete guide to RAG: architecture, chunking, embeddings, vector stores, retrieval, reranking. A hands-on tutorial with pgvector and Python.

A systematic approach to prompt engineering: prompt anatomy, 7 principles, production system prompts, CoT and few-shot techniques, prompt management. With code examples.

A systematic approach to vibe coding for professional developers: architecture, rules-driven development, enforcement, team workflows. Not for beginners.

A deep comparison of context engineering and RAG: when long context replaces retrieval, when you actually need RAG, a decision framework, and the modern 2026 stack.

An exhaustive guide to Supabase: architecture, authentication, RLS, Edge Functions, pgvector, branching. Comparison with Firebase, pricing, and best practices for startups as of mid-2026.

A comprehensive guide to AI agents: architecture, frameworks (LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, Pydantic AI, MCP), practical use cases, and a hands-on tutorial.

How AI is changing finance operations: automated bookkeeping, revenue forecasting, fraud detection, spend management. 25+ tools with prices and implementation cases.

Design work sample tests for hiring: assignment structure, evaluation rubrics, and AI prompts to generate role-specific tests for devs, PMs, and marketers.

Select a North Star Metric with AI: criteria by business model, analysis prompts, unit economics validation. SaaS, marketplace, and e-commerce examples.

Identify PMF from retention curves: SQL for cohort analysis, statistical flattening detection, and AI interpretation prompts. Tutorial with ready-to-use code.

Investor-ready model structure: revenue model, P&L, cash flow, unit economics. AI prompts for Google Sheets formulas, formatting standards, and common mistakes.

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

A 5-component prompt template for building a reusable library. Structure, examples for different tasks, plus organization and versioning of a prompt library.

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

A framework for multiplying free-to-paid conversion via AI analysis of onboarding, activation triggers, and the pricing page. Prompts and metrics.

Anomaly detection, AI prompts for configuring alerts, and tools (Grafana, PostHog, custom). Practical rules and configs for product metrics.

Template for monthly investor updates: prompts to generate them from raw metrics, good vs bad email examples, send timing, and automation with Claude.

JourneyBay 2.0 is live - an AI Travel Engine that edits your trip instead of just answering questions. A trip from one prompt, booking import from PDFs and photos, visa context from official sources, bring your own LLM key, and MCP access for Claude Desktop, Codex, and Cursor.

NDA structure, prompts for generating agreements by jurisdiction (US, UK, EU, Russia), a legal review checklist, and AI limitations for legal documents.

A free stack for competitive intelligence: change monitoring, AI analysis prompts, report templates. Step-by-step guide for solo founders tracking 15 competitors.

A PQL scoring model built on product usage data and LLMs: defining activation events, SQL queries for feature scoring, classification prompts, CRM integration.

Cut Docker images by 93% with multi-stage builds. Before/after Dockerfiles for Node.js and Python, layer caching, and Trivy scanning.

Impact × frequency matrix with AI scoring for backlog prioritization. Prompts, examples, and visualization. Replacing subjective debates with data.

Structured prompts for generating GitHub Actions workflows with AI. Node.js, Python, Docker, multi-stage deploy — working YAML examples and security tips.

Run 10 A/B tests monthly in 3.5 hours: LLM hypothesis generation, experiment templates, PostHog and Statsig setup. Full framework inside.

Designing REST APIs with AI: naming conventions, versioning, error handling, and OpenAPI spec generation. Ready-to-use prompts for every stage.

GDPR checklist for startups with AI audit prompts, common violations and fixes, plus a privacy policy template covering all Article 13 requirements.

AI toolkit for performance marketing on a $500/mo budget: prompts for copy and creatives, Meta vs. Google Ads allocation, metrics thresholds, and a weekly optimization cycle.

AI-powered keyword research pipeline: seed generation via Claude, clustering with prompts, validation in Ahrefs/SEMrush. Prompts, tables, step-by-step process from zero to a ready content plan.

Step-by-step method for crafting an elevator pitch with AI: a 6-block structure, prompts for each block, before/after examples, and adaptations for investors, clients, and partners.

B2B sales objection classification, prompts for generating responses via LLM, a ready-to-use playbook template with examples. A system for preparing to handle any objection.

A template for a 90-day new employee onboarding plan generated with an LLM. Prompts, week-by-week checklists, and probationary period success criteria.

Rubric-based resume screening with LLMs: prompts, calibration, bias mitigation, and a step-by-step process from 100 resumes to a shortlist in 30 minutes.

KAOS — a self-hosted Python runtime for long-running AI agents with five-layer memory, multi-agent coordination, built-in automations, and defense-in-depth security. An open source alternative to Hermes Agent and OpenClaw.

A step-by-step pipeline from exporting Figma mockups to a working prototype using v0, Bolt, and Claude Artifacts. Concrete steps, prompts, and common mistakes.

A TCO model for three startup architectures: monolith, microservices, serverless. AI-assisted calculation prompts, comparison tables, and a decision framework with concrete numbers.

RICE framework with AI automation: prompts for scoring Reach, Impact, Confidence, and Effort. A sample backlog with 10 features, templates, and LLM-based automation.

A step-by-step process for turning a PRD into a PostgreSQL schema in 30 minutes with AI. Extract entities, build relationships, generate migrations.

Build a positioning statement with AI in 30 minutes. A 4-step framework with prompts for audience, category, differentiator, and proof points. Before/after examples included.

A methodology for value-based pricing using AI: the Van Westendorp model, value analysis through prompts, finding price points from competitor data and user behavior.

HCP - open-source control plane for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot. Auto-discovery, symlinks, drift detection.

A practical guide to dashboard design for startups: executive, product, and engineering. Concrete metrics, SQL queries, and prompts for generating dashboards in Metabase and Grafana.

7 SQL queries for cohort analysis: retention, revenue cohorts, activation, churn prediction. Ready-made prompts for AI generation. Copy and run.

Claude Code: complete guide to Anthropic's agentic CLI. Installation, CLAUDE.md, MCP servers, subagents, skills, hooks, and best practices for developers.

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 framework for deciding between bootstrapping and fundraising: financial models for both scenarios, Claude prompts, comparison tables, sensitivity analysis, and clear selection criteria.

20 standard investor questions with Claude prompts and answer templates. Pitch meeting prep with AI: unit economics, TAM, competitors, go-to-market.

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.

A checklist of 15 common production code vulnerabilities with before/after examples and prompts for AI-assisted auditing. SQL injection, SSRF, path traversal, JWT, race conditions, and more.

Sensitivity analysis for SaaS startups using AI: formulas, prompts for modeling, scenario tables, tornado diagrams. Churn vs CAC - which parameter has a bigger impact on runway.

How to apply test-driven development with Claude Code: prompts, test-first workflow, approach comparison. A practical guide with code examples.

How to generate production-ready PRDs with LLMs: document structure, prompts for each section, real output examples, and a ready-to-use template.

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 build a quarterly content plan with an LLM: topic clusters, format distribution, prompts for topic generation, and a ready-made calendar template.

Build an AI-generated 7-email drip sequence for SaaS trial-to-paid conversion. Prompts, timing, templates, and metrics included.

How to use an LLM to generate OKRs: prompts, templates, examples of good and bad Key Results. A full process from strategic priorities to a finished OKR set in one session.

A decision-making framework for HITL in AI products: confidence thresholds, risk matrix, escalation patterns. Production-ready implementation examples with code.

Methodology for A/B testing prompts: quality metrics, statistical significance, tools (Langfuse, DeepEval). Step-by-step guide from hypothesis to production decision.

Generate Architecture Decision Records with AI: template, prompt library, CI automation, full Claude Code workflow from decision to docs.

A complete AI-powered content production pipeline: from keyword research to publication. Prompts, tools, quality metrics, and exact cost figures for each stage.

Build a 13-week cash flow forecast: table structure, formulas, scenario analysis, and AI prompts for automation. Free template included.

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.

Model a cap table with AI: dilution formulas, Pre-Seed to Series A calculations, prompts, and founder dilution analysis across 3 rounds.

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.

Battle-tested checklist for AI code review: Correctness → Security → Performance → Readability. Prompts per stage, real findings, CI/CD template.

Pitch deck narrative framework: AI prompts for every slide, transition logic, and sample copy. Build a presentation that survives 60 seconds.

Generate high-converting ad copy with AI using PAS, AIDA, BAB, FAB, and 4U frameworks. Ready-made prompts and before/after examples included.

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 patterns for production: Sequential Pipeline, Parallel Fan-Out, Classifier+Router orchestration, task routing, agent specialization with code examples.

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 automate the research step of cold outreach (20-40 min/lead) with AI: tool stack, two-step prompts, deliverability setup, and 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 proxy: automatic failover, LLM fallback chains, task-based routing, cost balancing. Circuit breaker patterns and production configuration.

How we built a resilience layer for edge functions: circuit breaker, retry with jitter, and fail-open rate limiting. Real production code, zero dependencies.

What is context engineering and how to apply it: 6-layer context structure, 4 management strategies, persistence patterns, subagent isolation. Practical guide with Claude Code examples.

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.

Step-by-step Langfuse tutorial: LLM call tracing, prompt versioning, cost tracking, output evaluations. Self-hosted setup in 15 minutes with Docker Compose.

Build your own MCP server from scratch and run it in production. Error handling, fallback chains, circuit breakers, monitoring, and security patterns from real-world experience.

Sync MCP server configs across Claude Code, Cursor, Codex, and Gemini with one command. AgentSync CLI: single source of truth, JSON/TOML/MDC format conversion, deduplication, backups.

Open-source MCP framework: parallel consultations with OpenAI, Gemini, Qwen, DeepSeek. Fallback chains, no extra API keys, production-tested.

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