https://sourcescore.org/blog/ Posts on AI-citation quality, LLM grounding, and the SourceScore methodology. en-US Tue, 02 Jun 2026 16:31:53 GMT scripts/generate-rss.mjs https://sourcescore.org/blog/how-to-find-reliable-sources/ https://sourcescore.org/blog/how-to-find-reliable-sources/ Mon, 01 Jun 2026 00:00:00 GMT Start from source types that are reliable by construction — primary, peer-reviewed, official — search inside them, then verify each candidate on three signals before you cite. A faster way to find credible sources than trusting search rankings. find-reliable-sources, credible-sources, research-paper, academic, citation, guide https://sourcescore.org/blog/can-you-cite-chatgpt-ai-as-a-source/ https://sourcescore.org/blog/can-you-cite-chatgpt-ai-as-a-source/ Sun, 31 May 2026 00:00:00 GMT Short answer: cite the source, not the AI. You can disclose ChatGPT as a tool you used, but never as the source of a fact — it fabricates. How to reference and verify AI properly, with APA/MLA notes. cite-chatgpt, citing-ai, academic, apa, mla, ai-hallucination, guide https://sourcescore.org/blog/how-to-tell-if-a-source-is-reliable/ https://sourcescore.org/blog/how-to-tell-if-a-source-is-reliable/ Sun, 31 May 2026 00:00:00 GMT A practical way to judge any source — does credible work cite it, does it stay current and correct itself, and are people citing it now — plus how to check 130+ sources instantly on the SourceScore Index. source-reliability, credibility, evaluating-sources, citation, guide, fact-checking https://sourcescore.org/blog/multi-llm-grounding-2026/ https://sourcescore.org/blog/multi-llm-grounding-2026/ Sun, 17 May 2026 00:00:00 GMT Single-provider lock-in is fragile in 2026. Pricing shifts, capability changes, and outages all argue for portability. The architecture pattern that keeps your grounding layer LLM-agnostic — same verification, citation, and source-quality across every provider. multi-llm, architecture, portability, router, adapter, grounding https://sourcescore.org/blog/llm-grounding-strategies-2026/ https://sourcescore.org/blog/llm-grounding-strategies-2026/ Sun, 17 May 2026 00:00:00 GMT Prompt engineering buys 10-30%. Retrieval-augmented generation buys another 20-40%. Signed-claim verification closes the long tail. Six strategies, their measured impact, and when to combine. grounding, hallucination, rag, verification, production, patterns https://sourcescore.org/blog/llm-framework-comparison-2026/ https://sourcescore.org/blog/llm-framework-comparison-2026/ Sat, 16 May 2026 00:00:00 GMT Seven LLM frameworks own most of 2026 dev mindshare. They optimize for different things — orchestration, retrieval, type-safety, vendor-native, deployment ergonomics. Pick by archetype + audience + commitment. framework, comparison, langchain, llamaindex, openai, anthropic, dspy, pydantic-ai, vercel-ai-sdk https://sourcescore.org/blog/why-no-performance-claims/ https://sourcescore.org/blog/why-no-performance-claims/ Sat, 16 May 2026 00:00:00 GMT Benchmark numbers vary by prompt format, model version, shot count, and evaluation harness. Shipping them as 'verified claims' is the surest way to make the catalog wrong by Thursday. Here's the alternative. methodology, trust, benchmarks, veritas https://sourcescore.org/blog/verify-ai-facts-five-lines-python/ https://sourcescore.org/blog/verify-ai-facts-five-lines-python/ Sat, 16 May 2026 00:00:00 GMT Drop SourceScore VERITAS into your LLM pipeline as a post-generation check. Every claim the model emits gets a confidence score + canonical citation before the user sees it. tutorial, python, veritas, hallucination https://sourcescore.org/blog/launching-veritas/ https://sourcescore.org/blog/launching-veritas/ Sat, 16 May 2026 00:00:00 GMT VERITAS is a free-tier-friendly API that returns hand-verified AI/ML claims with their primary sources, an HMAC-SHA256 signature, and a ready-to-paste citation. launch, veritas, api, llm-grounding