No thought leadership. No "state of AI" post. Essays with code, benchmarks, and repro steps. If the post has a number in the title, the number is in the post.
We built Wauldo Deploy: open standards (AGENTS.md, Skills, mcp.json, Agent Protocol) + verified execution. Every agent response grounded with a support score.
We built Wauldo Deploy: open standards (AGENTS.md, Skills, mcp.json, Agent Protocol) + verified execution. Every agent response grounded with a support score.
Read post → 2026-04-17 · benchmarkWe tested 14 LLMs on 61 adversarial tasks. Every model hallucinated. The cheaper model with verification beat the premium model without. Here's the data.
Read post → 2026-04-10 · verificationAblation study on 70 adversarial tests: LangChain + Wauldo Guard scored 45/70. Bare LangChain scored 46/70. Post-hoc verification doesn't close the gap. Robustness is system-level.
Read post → 2026-03-25 · positioningUsers trust AI that sounds confident, even when it is wrong 8% of the time. Users don't report them. They trust them. Do the math for your own AI.
Read post → 2026-03-20 · businessOne wrong AI answer triggers churn, support tickets, and compliance risk. Here's how to quantify the cost — and fix it with verification.
Read post → 2026-03-15 · verificationA developer's guide to adding automated verification to your LLM pipeline — token overlap, semantic similarity, hybrid, numerical mismatch detection.
Read post → 2026-03-10 · langchainLangChain retrieves context but doesn't verify answers. Here's why RAG hallucinations persist and how to add a verification layer that actually works.
Read post → 2026-03-05 · productionMost LLM apps ship unverified answers to users. Here's how to audit your AI outputs, measure hallucination rates, and catch wrong answers before users do.
Read post → 2026-03-01 · openaiGPT-4 is powerful but not infallible. Here's how to add a verification layer between OpenAI and your users. Code examples for Python and TypeScript.
Read post → 2026-02-25 · ragFive pitfalls every RAG team hits: tenant isolation, confidence signals, hybrid retrieval, source attribution, model routing. With pseudocode.
Read post → 2026-02-20 · verificationUpload documents, ask questions, get answers with sources and a numeric support score. One API, no hallucinations, full audit trail.
Read post → 2026-02-15 · hallucination3-path retrieval, multi-source merge, post-generation fact-checking, confidence calibration, and an audit trail that proves every answer came from source.
Read post →Posts ship sporadically — when we have a number to report or a pattern to share. Subscribe via RSS to catch every one. No email capture.
Six adapters, 70 adversarial tests, Wilson 95% CI. Wauldo 96%, LangChain 66%, LangChain+Guard 66%.
Open leaderboard → weekly · reproducibleEval suite 77%, hard suite 85%, RAG-only accuracy 89%, 0% hallucination. Auto-refreshed every Monday.
See benchmarks → product · APIEvery answer grounded against sources, support_score on every claim, OpenAI-compatible endpoint, 5ms p50.
See the product →Paste an AI answer in our home widget to see support_score live.