Editorial standards

What we publish

Original analysis with deterministic data. Our flagship is the Cost of Inference column — per-model unit-economics calculations across 12 LLMs in our pricing catalog, run against 3 canonical production workloads (RAG, long-context coding assistant, multi-step agent loop). The numbers come from gotcontext.ai/v1/models; we own the math.

Curated developer-community signal. Posts from 8 AI-engineering subreddits (r/MachineLearning, r/OpenAI, r/LocalLLaMA, r/LLMDevs, r/AI_Agents, r/ClaudeCode, r/ClaudeAI, r/GeminiAI) are pulled hourly and pass through a 3-layer quality gate before any LLM touches them: title regex blocklist (no help requests, weekly threads, mod posts), minimum 50 upvotes, minimum 10 comments.

Primary-source releases. Lab and vendor blog posts from OpenAI, Google DeepMind, and Hugging Face. These are PRIMARY sources — they ARE the announcement, not commentary on it — so they bypass the community-endorsement thresholds but still pass the title regex.

What we DON'T publish

• Reddit help requests, weekly meta threads, mod posts. Filtered out at ingest by title regex.
• Cross-posted meme content. Posts with high upvotes and zero comments are usually low-signal re-shares; the AND gate on both ups + comments filters them.
• Controversial flame threads. Posts with high comment count and low upvote count signal disagreement, not consensus on importance.
• Sponsored content or vendor-paid placements. We don't accept any. If we ever do, this page will list a clear "Sponsored" disclosure rule.

Drafting + publishing process

Curated source items enter a draft queue. Anthropic's Claude Haiku writes a 600–900 word structured analysis with a required 5-part structure: lede (subject-verb-object factual statement), statistics (at least one verbatim numeric claim from the source), analysis (cost / infrastructure / agent-tooling implication for engineering teams), forward-looking (next concrete thing to watch), and inline source citations.

Drafts auto-publish 60 minutes after entering the queue unless an editor approves them sooner. The Cost of Inference column is generated weekly from deterministic catalog math — no LLM touches the cost numbers, only the framing prose.

Bylines

All articles are bylined by the gotcontext.ai team. We don't publish personal bylines. Credibility comes from the published methodology + the deterministic data behind any quantitative claim, not from individual reputation. This is the same model used by institutional publications like The Economist and Stratechery's data column.

Source labels

Every article shows its source type on the listing card and article footer:

• Source: r/MachineLearning (or another sub) — community signal. Our analysis is summarization + commentary.
• Source: OpenAI Blog (or DeepMind / Hugging Face) — primary publication. Our analysis is interpretation + implication for engineering teams.
• Source: gotcontext.ai — original column built from our own pricing catalog or benchmark data. No external source.

Corrections

Found a factual error? Email corrections@gotcontext.ai with the article URL and the specific fact you're disputing. We update the article inline with a dated Correction note at the top and bump the updated_at timestamp.

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