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01
Mar
what is an mcp client
What is an MCP Client in Model Context Protocol?

In Model Context Protocol (MCP), an MCP client is the host app’s per-server connection component. The host creates one client for each MCP server, and the client runs the session, negotiation, and message routing. It is not the LLM and […]

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01
Mar
PDF Readable To AI
Make a PDF AI-Readable so You Can Ask, Chat, Summarize, and Extract

To make a PDF readable to AI, ensure it has a real text layer, remove access restrictions, and fix structure so headings, columns, and tables keep their meaning. Then use an AI tool that can cite the exact passage it […]

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01
Mar
Ask AI
How to Ask AI a Question so You Get Accurate, Useful Answers

Ask AI one clear question, add the minimum context that changes the answer, set constraints and success criteria, and request a specific output format. Then use a short verification script that forces assumptions, sources, and a sanity check, because hallucinations […]

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01
Mar
Large Language Models
Best Large Language Models in 2026

The best large language models in 2026 depend on your job. Use leaderboards to shortlist, then run a small eval on real tasks. Avoid lock-in by running multiple models side by side and keeping failover. Current top contenders include Claude […]

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01
Mar
Gemini Chatbot
How to Make a Gemini Chatbot in 2026

To make a Gemini chatbot in 2026, create a Gemini API key in Google AI Studio or Vertex AI, choose a framework or no-code platform such as CustomGPT.ai, define system instructions and data sources, then deploy the bot to your […]

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01
Mar
Agentic AI
What is Agentic AI (2026)?

Agentic AI is AI that can perceive context, reason about a goal, take actions using tools, and learn from outcomes. It goes beyond text generation by executing work, with guardrails like permissions, confirmations, and audit logs. This is for ops […]

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01
Mar
ChatGPT Plus Limits 2026: New Caps & Fixes | CustomGPT.ai
ChatGPT Plus Limits 2026: Every Cap, Verified

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 […]

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28
Feb
DPA with Your AI Vendor
What should I look for in a Data Processing Agreement (DPA) with an AI vendor?

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 […]

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28
Feb
Business AI for Factual Answers
How Can I Control the “Temperature” or Creativity of My Business AI to Ensure Factual Answers?

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 […]

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28
Feb
rag vs fine-tuning safety enterprise data
Why Is Rag Considered Safer for Enterprise Data Than Fine-Tuning a Model?

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, […]

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