In this special two-week recap, the team covers major takeaways across episodes 445 to 454. From Meta’s plan to kill creative agencies, to OpenAI’s confusing model naming, to AI’s role in construction site inspections, the discussion jumps across industries and implications. The hosts also share real-world demos and reveal how they’ve been applying 4.1, O3, Gemini 2.5, and Claude 3.7 in their work and lives.

Key Points Discussed

Meta's new AI ad platform removes the need for targeting, creative, or media strategy – just connect your product feed and payment.

OpenAI quietly rolled out 4.1, 4.1 mini, and 4.1 nano – but they’re only available via API, not in ChatGPT yet.

The naming chaos continues. 4.1 is not an upgrade to 4.0 in ChatGPT, and 4.5 has disappeared. O3 Pro is coming soon and will likely justify the $200 Pro plan.

Cost comparisons matter. O3 costs 5x more than 4.1 but may not be worth it unless your task demands advanced reasoning or deep research.

Gemini 2.5 is cheaper, but often stops early. Claude 3.7 Sonnet still leads in writing quality. Different tools for different jobs.

Jyunmi reminds everyone that prompting is only part of the puzzle. Output varies based on system prompts, temperature, and even which “version” of a model your account gets.

Brian demos his “GTM Training Tracker” and “Jake’s LinkedIn Assistant” – both built in ~10 minutes using O3.

Beth emphasizes model evaluation workflows and structured experimentation. TypingMind remains a great tool for comparing outputs side-by-side.

Carl shares how 4.1 outperformed Gemini 2.5 in building automation agents for bid tracking and contact research.

Visual reasoning is improving. Models can now zoom in on construction site photos and auto-flag errors – even without manual tagging.

Hashtags

#DailyAIShow #OpenAI #GPT41 #Claude37 #Gemini25 #PromptEngineering #AIAdTools #LLMEvaluation #AgenticAI #APIAccess #AIUseCases #SalesAutomation #AIAssistants

Timestamps & Topics

00:00:00 🎬 Intro – What happened across the last 10 episodes?

00:02:07 📈 250,000 views milestone

00:03:25 🧠 Zuckerberg’s ad strategy: kill the creative process

00:07:08 💸 Meta vs Amazon vs Shopify in AI-led commerce

00:09:28 🤖 ChatGPT + Shopify Pay = frictionless buying

00:12:04 🧾 The disappearing OpenAI models (where’s 4.5?)

00:14:40 💬 O3 vs 4.1 vs 4.1 mini vs nano – what’s the difference?

00:17:52 💸 Cost breakdown: O3 is 5x more expensive

00:19:47 🤯 Prompting chaos: same name, different models

00:22:18 🧪 Model testing frameworks (Google Sheets, TypingMind)

00:24:30 📊 Temperature, randomness, and system prompts

00:27:14 🧠 Gemini’s weird early stop behavior

00:30:00 🔄 API-only models and where to access them

00:33:29 💻 Brian’s “Go-To-Market AI Coach” demo (built with O3)

00:37:03 📊 Interactive learning dashboards built with AI

00:40:12 🧵 Andy on persistence and memory inside O3 sessions

00:42:33 📈 Salesforce-style dashboards powered by custom agents

00:44:25 🧠 Echo chambers and memory-based outputs

00:47:20 🔍 Evaluating AI models with real tasks (sub-industry tagging, research)

00:49:12 🔧 Carl on building client agents for RFPs and lead discovery

00:52:01 🧱 Construction site inspection – visual LLMs catching build errors

00:54:21 💡 Ask new questions, test unknowns – not just what you already know

00:57:15 🎯 Model as a coworker: ask it to critique your slides, GTM plan, or positioning

00:59:35 🧪 Final tip: prime the model with fresh context before prompting

01:01:00 📅 Wrap-up: “Be About It” demo shows return next Friday + Sci-Fi show tomorrow