Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:

🚨 AI Top Story: ChatGPT’s growing memory is reshaping how people trust, return to, and even depend on AI

💬 Killer Marketing prompt: Need a tool for your business but not sure what to build? This prompt helps you co-design an AI-powered app you can prototype.

🎥 YouTube Resource Of The Week: How To use Remix on Replit to copy code from existing templates. Super easy way to get working app environments in a matter of minutes.

🎯 AI Use Case Of The Week: Netflix is testing AI-powered search and TikTok-style previews to help users find the perfect show.

🌟 Creator Spotlight: Vamsi Bhavani shares ‘10 Things You Need To Know About OpenAI’s New Coding Model’.

How Memory Is Changing How We Use AI

More Memory, More Trust, More Decisions

Memory is starting to play a bigger role in how ChatGPT works. Instead of treating every conversation like a blank slate, the model is learning to carry details forward, picking up on tone, remembering preferences, and gradually building a sense of continuity.

It's a subtle shift now, but one that hints at something much bigger: a more familiar, more reliable kind of AI that can grow with the person using it.

And that reliability is already changing how people engage. What was once a quick way to generate ideas or check facts is becoming something more trusted, even consultative.

There’s a growing pattern: users returning to the same chat thread not just to ask questions, but to weigh options. In some cases, people hesitate to make big decisions without first running it by AI.

Of course, things could likely begin to get weird, if we as humans don’t feel comfortable with making decisions without hearing what AI has to say first, what could that mean for human judgement as a whole?

It’s about how comfort and consistency influence trust. The more natural and useful the interaction becomes, the more likely it is that AI will become a default part of daily decision-making - for work, for life, and eventually, for buying.

For marketers, that’s a signal worth paying attention to. If consumers start relying on AI to guide choices, from what to read to what to buy, the content that shapes those responses matters more than ever. It’s not just about visibility. It’s about showing up in the right tone, with the right context, in the places where decisions begin.

🧠 OpenAI Introduces Codex, an AI Agent to Automate and Accelerate Coding Tasks - Codex transforms ChatGPT into a virtual coding assistant, capable of writing, debugging, and testing code autonomously.

🔍 After a year of Google’s AI Overviews, marketers consider tweaking their paid search strategies - Google's AI Overviews are reshaping search behaviour, prompting marketers to adjust their paid strategies as organic clicks decline.

🎓 Top Gen AI Certifications to Elevate Your Marketing Career - With AI skills in high demand, certifications from institutions like Harvard and Cornell are helping marketers stay competitive and innovative.

💼 Why Microsoft is cutting roles despite strong earnings - Microsoft is laying off 6,000 employees to streamline operations and focus on AI investments, despite reporting strong financial results.

📺 YouTube announces Gemini AI feature to target ads when viewers are most engaged - YouTube's Gemini AI analyses viewer engagement to place ads at optimal moments, aiming to enhance ad effectiveness and viewer experience

Expedia’s DM Tool Makes Reels Bookable

The Overview

Expedia’s new Trip Matching feature helps turn travel inspiration into real plans—right from Instagram. When users send a public travel Reel to @Expedia, they’ll get a personalized itinerary back: where to go, where to stay, and what to do. It’s a smart way to connect social content with actual trip planning—no app switching, no searching required.

How It Works

Trip Matching is powered by generative AI that analyzes both the visual and textual content of the Instagram Reel a user shares with @Expedia.

Some coverage has speculated that tools like OpenAI’s Operator and Microsoft Copilot Actions may be involved, but Expedia has not confirmed which technologies are being used. What’s clear is that the system uses a combination of vision and language models to understand what’s happening in the Reel—recognizing settings, landmarks, and activities, then pairing that with captions or hashtags to extract user intent.

Together, these elements inform a personalised trip recommendation that’s sent back via Instagram DMs. No app switching, or extra searching required.

Replicate Something Similar

Step 1: Instagram DM Integration

What it does: Captures the user’s shared Reel and triggers the AI workflow.
Tools:

• Meta Messenger API for Instagram

• Webhook handler (e.g. Firebase Functions, AWS Lambda, Node/Express server)

Step 2: Retrieve Reel Metadata & Media

What it does: Pulls content data from the Reel for AI to analyze.
Tools:

• Instagram Graph API

• Reel thumbnail, caption, hashtags, audio info

How it connects: Reel URL triggers a Graph API call → returns media thumbnail + caption + metadata.

Step 3: Visual Analysis via Vision Model

What it does: Analyses the Reel thumbnail image to identify setting, objects, and visual themes.

Tools:

• OpenAI GPT-4 with vision

• OR Google Cloud Vision AI (for label detection, landmark detection)

• Image passed via API in base64 or URL format

How it connects: Your backend uploads the image → sends it to the vision API → gets structured tags and labels (e.g. "beach," "urban," "snorkeling").

Step 4: Text Analysis via LLM

What it does: Processes captions, hashtags, and any DM text to extract tone and intent.

Tools:

• OpenAI GPT-4 (text-only) or Anthropic Claude

• Prompt templates for extracting mood, preferences, and constraints

How it connects: Captions and hashtags sent via API → model returns structured user intent (e.g. “romantic”, “solo trip”, “adventure”).

Step 5: Merge & Generate Response

What it does: Combines visual + textual insights and generates a personalized reply.

Tools:

• Your backend logic (e.g. Node.js, Python Flask, or Make.com/Zapier for no-code MVPs)

• LLM (GPT-4 or Claude) to generate natural language message

• Optional: link to your own CMS or travel/product database

How it connects: AI outputs are combined → passed into a templated prompt → LLM generates the final message.

Step 6: Reply via Instagram DM

What it does: Sends the generated response back to the user.
Tools:

• Messenger Send API

• Optionally, use quick replies, carousels, or buttons for follow-up

How it connects: Backend formats response → calls Send API → reply lands directly in the same DM thread.

VAMSI BHAVANI - 10 Things You Need To Know About OpenAI’s New Coding Model

How to save, share, & copy Replit Apps with Remix