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Blog Archives

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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28
Feb
AI Chatbot to Drive Traffic
How Do I Use an AI Bot to Drive Traffic to Specific Landing Pages or Offers?

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 […]

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28
Feb
AI Writing System Prompts
What Are the Best Practices for Writing System Prompts for Sales-Focused AI Agents?

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 […]

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28
Feb
AI-Powered Answer Engine for Better Conversions
How Can I Replace My Website’s Legacy Search Bar With an AI Answer Engine?

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 […]

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