Worklog for task "Format content"
Complete AI Pass on the Resource Corpus and Processing Economics
Following the initial pass over the topics, processing was expanded to the entire resource corpus: topics, comments, blogs, and other entities inherited from the general Resource model (historically from MODX site_content).
According to OpenRouter, the final batch amounted to approximately 12,000 AI requests, 14.1 million tokens, and around $7.99 in expenses. Almost all bulk processing was performed using Gemini 3.5 Flash Lite.
This practically matches the scale of the current archive: Topic + Comment alone yield 11,890 entities (1,349 topics and 10,541 comments), and with blogs and other types, the total volume naturally reaches about 12,000 resources.
The practical conclusion turned out to be more important than the Markdown migration itself: a full managed AI pass over a multi-year public archive costs single-digit dollars. Initially, around 8.
This changes content economics. Now, instead of limiting ourselves to a one-time migration, we can run specialized repeated passes across the entire corpus: normalization, classification, entity and assertion extraction, relationship building, tracking position changes, thematic retrospectives, provenance, and preparation of new publications. The cost of a full machine reading of the corpus becomes comparable to a routine technical operation rather than editorial work.
At the distribution model level, this yields another conclusion: a human can hand over the core idea to an AI, the AI can google and gather context, and then publish a managed set of materials on one or several websites. Afterwards, these materials become accessible to other AI agents and can be included in their responses via GEO/AI-search. In other words, cheap mass generation here is used not for spam, but as managed publishing infrastructure for distributing verifiable ideas and expertise.