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Welcome Automaters, 👋

So fresh data from the app intelligence gurus at Appfigures just dropped, and it confirms what we’ve all suspected: our beloved AI conversation partners are officially losing the popularity contest.

According to the report, when AI firms drop new image generation models, they pull in 6.5 times more downloads than when they release a shiny new chatbot upgrade. You read that right. We don't just want a better writer; we want a better artist.

The clearest proof of this obsession? When Google Gemini launched its latest image model, Nano Banana, the app racked up over 22 million new downloads in just 28 days.

That’s not a typo. Twenty-two million people rushed to the app store specifically because they wanted to see what those pixels could do.

The Plot Twist: Downloads do not automatically mean dollars. While Gemini had its 22-million-download moment, it only translated to around $181,000 in estimated consumer spending in that same period.

Meanwhile, ChatGPT’s 4o image model launch drove approximately $70 million in consumer spending over 28 days. It’s the same category, but a completely different financial reality.

The Translation: People absolutely love free image AI, but getting them to reach for their wallets? That is a much tougher conversation.

The Bottom Line: The AI industry spent years betting that smarter, more "human" chatbots would be the ultimate hook. Turns out, users just want to see something cool. 

Here's what we have for you today

🔐 OpenAI Launches Advanced Account Security for ChatGPT: Here’s How It Works, and How to Enroll

OpenAI just dropped a gift for the security-obsessed, and honestly? It’s about time. They’ve rolled out a brand-new, opt-in feature called Advanced Account Security. Think of it as a total "Witness Protection Program" for your data, bundling four hardcore protections into one tidy package.

The catch? You have to be the one to flip the switch.

So yeah, if you’ve been losing sleep over hackers or your data being used to train the next big model, you can finally breathe. OpenAI’s new Advanced Account Security is here, and it is intense. While they built this with "high-risk" folks in mind; we’re talking journalists, researchers, and political types, anybody who wants to turn their account into a digital vault can jump in.

So, what actually happens when you hit that "Enroll" button?

  1. Passwords are officially "So 2025": Say goodbye to your "Password123" (we know it’s you). Once you opt in, passwords are shown the door entirely. Logging in now requires a passkey or a physical security key. OpenAI even partnered with Yubico to offer a custom two-key bundle (the YubiKey C NFC and YubiKey C Nano) at a massive discount—$68, down from the usual $126. It’s basically the gold standard of protection, and now it’s actually affordable.

  2. No more "Account  Recovery" drama: You know those annoying text codes? Well they’re gone. Traditional recovery options like email and SMS verification are disabled to prevent SIM-swapping attacks. Instead, you’ll rely on backup passkeys or recovery keys generated during setup. Pro tip: Keep those somewhere safer than your "Notes" app.

  3. Shorter sessions, less stress: OpenAI is also shortening your active login sessions. This reduces the "window of opportunity" for anyone trying to hijack your account via malware. It’s a bit more logging in, sure, but it’s a lot less worrying.

  4. The Privacy Bonus: Here is the best part: turning this on automatically excludes your conversations from AI training. So yes, no more digging through three layers of privacy menus to make sure your business secrets aren't becoming part of GPT-6.

Oh and, there is a major trade-off you need to know before you commit: If you lose your keys, you lose your account. Period. OpenAI support cannot, and will not, recover it for you. This is "big kid" security; and the responsibility is 100% on you.

Ready to lock it down? Head to the enrollment page on the web, sign in, and hit Enroll.

What 2,000 SaaS Companies Reveal About Growth in 2026

Is your growth in-line with your peers in B2B SaaS & AI? 

Benchmark yourself against actual billings data for Maxio’s 2000+ global customers, alongside firsthand company perspectives to understand how growth varied by company size, business model, and strategic focus.

Key takeaways from the report: 

  • Average growth across 2,000 companies

  • Growth by revenue band 

  • AI-led vs AI-enhanced. Who performed better? 

🧱 Around The AI Block

🤖 AI Workout Of The Day: How To Write Data-Backed Blog Posts That Build Authority

In today’s world of content overload, what truly sets your blog apart is proof. 

Data-driven posts don’t just share opinions, they provide clarity, credibility, and value your readers can trust. Whether you’re trying to build thought leadership, attract high-quality backlinks, or just give your audience something worth bookmarking, research-focused posts are your best asset.

And guess what? AI can help you structure and draft these kinds of posts in minutes, as long as you give it the right direction.

Here’s  How to Use This Prompt Effectively

  • Be specific with your topic: Include a narrow focus (e.g., “remote work productivity in 2025” instead of just “remote work”).

  • Clarify the tone: Choose from authoritative, analytical, neutral, academic, or even persuasive—this helps shape the voice and structure.

  • Add context or target audience: If you’re writing for executives, students, marketers, etc., say so.

  • Optional: Add a goal: For example, “The goal is to persuade tech CEOs to adopt AI” or “Highlight gaps in existing research for future innovation.”

  • Cite real research: If you already have studies, reports, or stats in mind, include them. Otherwise, let AI suggest areas where citations could go, and you can replace them with accurate sources during editing.

  • Set your word count target: 1000+ is the default, but you can raise or lower it as needed.

💡 Prompts to try:

You are an expert researcher, senior writer, and content strategist specialising in [Insert Industry/Niche].
Your task is to write a full-length, research-backed blog post on the following topic:

TOPIC: [Insert specific, narrow topic — e.g., "How AI-powered hiring tools affect diversity outcomes in tech companies, 2023–2025"]

STRUCTURE:

1. HEADLINE:  Write 3 headline options: one curiosity-driven, one data-led, one direct benefit. Flag your recommended pick and explain why in one sentence.

2. INTRODUCTION (150–200 words): Open with a surprising statistic, counterintuitive finding, or a sharp question that reframes the reader's assumption. Establish the stakes clearly. End with a signpost sentence that previews the post's argument.

3. CONTEXT SECTION (200–300 words):  Provide background: why this topic matters now, what has changed recently, and what most people still misunderstand about it.

4. BODY SECTIONS (3–5 sections, each 250–400 words)
   Each section must:
   — Open with a clear, specific sub-heading
   — Lead with a data point, study, trend, or expert insight
   — Explain what the evidence means (not just what it says)
   — End with a 1–2 sentence transition or implication

5. COUNTERPOINT OR NUANCE SECTION (optional but recommended):  Acknowledge the strongest objection or limitation of your main argument. This builds credibility and pre-empts reader skepticism.

6. CONCLUSION (150–200 words): Summarise the core argument in 2–3 sentences. Offer a concrete, actionable takeaway — not a vague "think about it." Close with a CTA.

7. META-ELEMENTS
   — Suggested meta description (150–160 characters)
   — 5 internal linking suggestions (topic areas, not URLs)
   — 3 possible social pull-quotes

PARAMETERS:
 -Tone: [authoritative / analytical / neutral / academic / conversational / persuasive]
 -Target audience: [Be specific — role, industry, level of expertise]
 -Goal of the post: [e.g., build authority, drive newsletter sign-ups, attract backlinks, spark debate]
 -Word count: [1,000 minimum — raise to 2,000–3,500 for pillar content]
 -SEO keywords to include naturally: [list 3–6 terms]

CITATIONS:

If you have specific sources: paste them and instruct the model to reference them accurately.

If you do not have sources: use this instruction instead:
"Where data is referenced, insert a [CITATION NEEDED] placeholder and specify the ideal source type (e.g., peer-reviewed study, government report, industry survey). I will verify and replace during editing."

OPTIONAL ADD-ONS:

 -Competing viewpoints: [Should the post engage with opposing arguments? Yes / No / Briefly]
 -Examples or case studies: [Name specific companies, events, or scenarios to include — or ask for suggestions]
 -Call to action (CTA): [What should readers do next? e.g., "Download our free toolkit", "Book a discovery call", "Subscribe for weekly research roundups"]
 -Content upgrades: [Should the post reference a lead magnet, checklist, or template? Describe it briefly.]
 -Formatting preferences: [e.g., include a TL;DR box at the top, add a summary table, use numbered lists sparingly]

Is this your AI Workout of the Week (WoW)? Cast your vote!

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