Nobody uses one AI model anymore. This piece maps a working seven-tool stack built around a single discipline: matching tool to job, not picking a winner. The author started in print design running Photoshop, Illustrator, and QuarkXPress simultaneously, and treats AI the same way. Each tool in this stack was built for a different intent, a different user, a different definition of done. The list includes NotebookLM, Claude, Claude Code, and four others, each assigned to a specific job with notes on where the alternatives break.
The method is worth more than the list. NotebookLM handles document-grounded research, capped at 50 sources of 500,000 words each, and gets sharper when you remove sources, not add them. Claude handles drafting and editing against a reusable voice prompt, then produces LinkedIn, Substack, Threads, and X versions in one pass. Claude Code stores reusable instruction files in CARE format: Context, Ask, Rules, Examples, so the same capability does not have to be re-explained every session. The author moved off Perplexity, Lovable, OpenAI, and Google Search this year. The tools shifted. The routing logic did not.
Read the full piece for the decision framework at the end, which is the part the list is scaffolding toward. The author promises a method for choosing tools that does not reduce to personal taste, and the tool-by-tool sections are the evidence base for it. If you are still asking which AI tool to use, this is the answer to the wrong question.
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