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How I Turned 350+ Programming Books Into 24 Learning Roadmaps With AI

A two-pass workflow—draft topic roadmaps first, then review and verify any file changes—can make a large programming library easier to navigate.
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Ariel Bodan says an AI coding agent helped turn a scattered library of more than 350 programming books and resources into 24 topic-based learning roadmaps. The useful idea is not that an agent can decide the one correct curriculum; it is to make a large collection easier to navigate, then check its suggestions before changing files.

The problem: too many resources, no clear next step

Bodan described having more than 350 programming books and resources stored across folders and topics, with duplicates mixed in. The practical question was familiar: what should I study next? The library included material related to areas such as backend engineering, data engineering, advanced Python, C, and technical interviews, but the collection itself did not provide a sequence.

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The workflow used opencode to scan the library recursively, group resources by subject, and propose a roadmap for each topic. Bodan reports that the resulting roadmaps covered 24 learning areas and organized resources into foundations, intermediate, and advanced stages. These are the author’s reported results, not an independent audit of the collection or an assessment of the roadmaps’ accuracy.

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Pass one: create roadmaps before moving files

Ask for topic groupings and learning stages

The first task was classification and planning: scan the folders, identify topic areas, and arrange the resources into staged roadmaps. Bodan’s proposed improved prompt adds useful specifics: include subfolders and PDF and EPUB files, place each resource where it is most useful, explain the goal of each stage, save the output as ROADMAPS_BY_TOPIC.md, and report the percentage of files categorized.

Those are recommendations for a prompt, not a description of verified results from the completed project. The article does not give the full list of 24 topics or a categorization percentage. A roadmap is best treated as a draft index into your own library: it can reduce the effort of choosing a starting point, but it does not establish that every resource was classified correctly or that the sequence is pedagogically optimal.

Review the proposed order

Before using a roadmap as a study plan, inspect whether its stage labels make sense for your goal. A foundations section should give you the prerequisites for later material; intermediate and advanced sections should build on them. Check that a resource has been assigned to a relevant subject and that its placement reflects what you already know, rather than assuming the agent understands your experience or learning priorities.

Pass two: reorganize only after reviewing a change plan

Once Bodan had reviewed the roadmaps, they asked the agent to make the folder structure match. That second pass involved creating folders, moving resources, checking for duplicates by comparing contents rather than filenames, verifying file counts before and after, and updating paths in the roadmaps. Moving or deleting files carries more risk than generating a Markdown plan, so keep those tasks separate.

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  1. Request a preview first. Have the agent list proposed folder creations, moves, and removals in a table. Bodan’s proposed wording is: “Before moving anything, show me the planned file changes in a table.” Review the source and destination for each item before authorizing changes.
  2. Use content comparisons for duplicates. Similar names do not prove that two files contain the same material. Bodan recommends: “Only remove exact duplicates after comparing their contents.” If the comparison is uncertain, keep both files and resolve the question yourself.
  3. Apply the approved moves. Let the agent reorganize only the files and folders in the reviewed plan. Keep a backup or otherwise ensure you can restore the original structure if a move is wrong.
  4. Reconcile the result. Compare the total file count before and after. Any decrease should be explained by exact duplicates you explicitly approved for removal; investigate unexplained differences. Check that roadmap paths point to the resources’ new locations.
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What the reported outcome does—and does not—show

Bodan reports that the process found four exact duplicates and left 348 resources organized across 24 topics, with nothing lost. Those counts are the author’s account; the article does not include a separate inventory or audit trail. It also does not report a measured categorization success rate, disclose all 24 topic names, or establish whether the resulting roadmaps improved learning outcomes.

The transferable lesson is the separation of low-risk planning from higher-risk file operations. Ask the agent to organize and explain its proposed structure first. Then review a concrete change plan, demand content-based duplicate checks, and verify counts and updated paths after any approved moves. This makes the agent a practical assistant for turning a personal archive into a navigable study map, not an authority on what everyone should learn.

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