Create your AI that knows when to say "I don't know." Try it on your data →
Building LLM-Based AI Agents as the core controller is a cool concept, as Lilian Weng puts it. It works best when you treat the LLM as a general problem solver plus strict controls. This is for AI engineers, product engineers, […]
Verified Q2 2026: ChatGPT Plus gives you 160 GPT-5.5 messages every 3 hours, 3,000 Thinking messages weekly, 80 uploads per 3 hours, and plan-dependent Project file caps. Below: what triggers each cap, and how to keep working when you hit […]
You should look for clear limits on data use, no model training on your data, defined security controls, subprocessor transparency, and enforceable deletion rights. A strong DPA makes it explicit how your data is processed, where it flows, how long […]
You control creativity by reducing generation freedom and increasing evidence constraints. In practice, that means using a low temperature, enforcing source-grounded responses, and requiring the AI to refuse when evidence is missing. Factual accuracy comes from constraints, not from letting […]
RAG is safer because enterprise data is never embedded into the model itself. Instead, data is retrieved at query time from controlled sources and used temporarily to generate answers. Fine-tuning permanently alters model weights with your data, making deletion, auditability, […]
You configure your AI bot to detect buying intent, answer the user’s question, and then route them to the most relevant landing page with a contextual recommendation. The AI should not drop random links it should guide users based on […]
The best system prompts clearly define the agent’s role, restrict it to approved sources, enforce qualification logic, control tone, and define what the agent must refuse. A strong prompt prioritizes accuracy and conversion alignment over creativity, ensuring the AI guides […]
Replace your keyword-based search with a RAG-powered AI answer engine that retrieves from your approved content and returns direct, source-grounded answers instead of document lists. Embed it where your search bar sits, connect it to your product, help, and marketing […]
AI search typically delivers higher ROI than traditional filters by increasing conversion rates, reducing bounce rates, and boosting average order value through intent-based product matching. Unlike static filters, AI interprets natural language queries and guides buyers toward purchase-ready decisions. Traditional […]
To get cited by AI engines, structure your help center content in clear Q&A formats, provide concise direct answers upfront, use consistent terminology, include supporting detail beneath summaries, and maintain authoritative, up-to-date documentation. AI systems prioritize clarity, structure, and evidence […]
