Indie Development

Until 2025, "edit in Cursor/Claude Code → switch to terminal git push → switch to browser to check Vercel" cost dozens of context switches a day. As of May 2026, Vercel Agent Skills (via MCP), the Claude Code Plugin, and Claude Code GitHub Actions v1.0 collapse "code → build → deploy → preview URL → env management → rollback" into one in-agent flow. This article walks through three implementation approaches: ① git push (5-min setup, 60–90s deploy), ② MCP-Direct (.cursor/mcp.json + slash commands like /deploy, /env, /rollback), ③ GitHub Actions (mention @claude in a PR for auto-fix + preview deploy). It then covers the three preview-environment patterns (A/B compare, permanent staging, password-protected client review) and the four operational pitfalls (env leakage, cost explosion, PR conflicts, missed rollback) — all with working code, grounded in May 2026.

Type "build me a Todo app" and 10 minutes later you have a live URL and a GitHub repo — that's "vibe coding," and the 2026 top three are Vercel's v0, StackBlitz's Bolt.new, and Lovable. Lovable hit $20M ARR in two months (fastest in European startup history); Bolt reached $40M ARR in six months; v0 added Git, DB connectivity, and agentic workflows in February 2026. This article maps the essence of each (v0 = designer, Bolt = developer, Lovable = founder), runs a detailed feature/pricing/framework comparison, gives the right pick for six use cases, presents results from running the same prompt through all three, walks through the three production pitfalls (token burn, security holes, lock-in), and closes with a 5-minute decision flow — all grounded in May 2026 facts. Companion to the AI Recommends series.

You shipped on the OpenAI API and now want to try Claude and Gemini — and you've burned two hours rewriting against three different SDKs. The Vercel AI SDK (just "AI SDK" since 2026) collapses that into "one import, one function, every provider," with 20M+ monthly downloads and AI SDK 6 shipping Agents, MCP, tool approval, and DevTools — the de facto standard for unified LLM interfaces in 2026. This article covers what the AI SDK is, three practical reasons to use it (free switching, 1/3 the implementation, type safety), a 5-minute quickstart from generateText to streamText, type-safe structured output via generateObject and Zod, tool calling and agent loops, a 10-line React chat UI with useChat, switching between Claude/GPT/Gemini in 3 lines, and the three production pitfalls (provider feature gaps, stream-abort billing, type-inference overload) — all with working code grounded in AI SDK 6 as of May 2026.

Google AI Overviews rewrote the search rules. Seer's 2026 study (53 brands, 5.47M queries) found organic CTR on AIO-present queries dropping 61%, the top-10 citation rate falling from 76% to 38%, yet cited brands earning 120% more clicks — the shift from "rank #1 to win" to "be the page that gets cited" is largely complete. This article maps SEO vs AEO vs LLMO vs GEO in 30 seconds, explains AI Overviews trigger conditions, lays out the seven citation factors (passage completeness, original data, E-E-A-T, structured data, entity density, multimodal content, technical accessibility), separates SEO that still works from SEO that no longer does, defines the new KPI stack (citation × CVR × share of voice), and closes with three risks — hallucinations, citation concentration, channel dependence — all backed by 2026 data.

A $20/mo ChatGPT Plus subscription can drop to $2/mo on the API — or it can shoot up to $200 in the other direction. The AI API is a "pay-as-you-go" world. This article walks through the five fundamental differences between Web chat and API, what tokens are and how pricing is calculated, May 2026 pricing for the major models (Claude Opus / Sonnet / Haiku, GPT-5.5/5.4, Gemini 3.1 Pro / Flash-Lite, DeepSeek V4-Pro), a 4-type model selection map, the three pitfalls every beginner falls into (conversation history accumulation, oversized system prompts, missing spending limits), and the 5-minute first call with curl plus Python — all from a beginner's viewpoint.

Vibe coding, coined by Andrej Karpathy in February 2025, is a development style where you tell an AI what you want in natural language and ship without reading the generated code. A year on, in 2026, Karpathy himself has proposed renaming it to "agentic engineering," while enterprises are seeing AI-derived CVEs grow 6x in three months, SSRF detection at 100% across the major agents, and a 40-62% vulnerability rate. Even so, it has become standard for indie dev, startups, and internal tools. This article covers the definition, the workflow, how Karpathy's position evolved, the leading tools (Claude Code, Cursor, Codex, Lovable, v0, Bolt.new, Devin), the security reality, the "Vibe & Verify" operational playbook, and who should vibe code on what — all grounded in the latest data.

You want ChatGPT to read your internal docs and answer questions about them --- that is exactly what RAG (Retrieval-Augmented Generation) is built for. This article walks through how RAG works in three steps, covers vector databases, a LangChain implementation, and when to pick RAG over fine-tuning. We also showcase real use cases including internal Q&A, customer support, and legal/medical knowledge work.

Think programming is beyond you? In 2026, AI coding tools like Claude Code let anyone — even with zero IT knowledge — build and launch a web service. This guide breaks down IT fundamentals (apps, databases, servers), the difference between shared hosting, VPS, and cloud, and walks you through the entire AI-powered development workflow from planning to deployment.

"You can build apps without coding thanks to generative AI" — but is that really true? In 2026, generative AI coding tools have come a long way, but can a complete beginner really finish an app with generative AI alone? This guide honestly covers what you can build, what you can't, and where beginners stumble.

"How do I actually make money with generative AI? Where do I start?" — This guide breaks down how to use tools like ChatGPT and Midjourney to build a real side income, organized by category with specific tool recommendations.

Generative AI coding tool performance varies dramatically depending on your framework choice. We rank major frameworks across training data volume, convention clarity, and type safety, then reveal the optimal 2026 generative AI development stack.