If you only wanted to pay for 2 AI tools for local SEO, of the three mentioned, which would you choose and why? I jumped on ChatGPT about a year ago and it has been my daily driver but it's losing ground to Gemini so I've been using Gemini more and more to see what the fuss is about. I find Gemini to be just as good except when it comes to writing. ChatGPT blows it away. I also find that Gemini is really lazy and hallucinates a lot more than ChatGPT. I'm constantly correcting Gemini where I rarely correct ChatGPT. Maybe I have ChatGPT trained better? I have no idea. I know a lot of SEO pros use Claude but I haven't used it much. It seems to me that Gemini would have a huge leg up on any other AI when it comes to local SEO since it presumably has search and behavior data directly from Google. Is Claude just better at writing, or does it have other inherent strengths over Gemini when it comes to doing SEO research, on-page optimization, etc.? Long story short, my stack for local SEO has been primarily Gemini for everything except writing, which I use ChatGPT for. Should I be adding Claude to the stack, or can Claude replace ChatGPT? I don't want to pay $100/month for Claude Max so I'd be considering the $20/month Claude plan vs the ChatGPT $20/month plan.

I've been thinking about this since I spotted a headline about agents replacing apps. At first I thought it was just hype. But the more I sat with it, the more I realised I already feel this in my own business. On my phone, I've got multiple apps for things that should be simple. In the UK you end up with three or four parking apps because every car park uses a different provider. All you want to do is pay for parking. But in my working day, it's browser tabs. My CRM, my email marketing platform, my calendar, my automations, my bookkeeping, my outreach tools. That's just how we've always worked. Before AI, there wasn't really an alternative. You needed a separate platform for each job, and you lived in the tabs. But collectively? They've become a tax on my attention. Too many logins. Too many dashboards. Too many places to check before I can actually do the work. The shift that's happening is this: instead of us going into each tool to get things done, AI agents sit across our tools and do the work on our behalf. The platforms don't disappear. They become the back end. The agent becomes the front door. I'm already living a version of this. I use Claude Code as an agent layer that works across my Airtable CRM, my automations, my email, my calendar, and my content. I don't open five tabs to prepare for the week. I have a briefing system that pulls from all of them and tells me what matters today. What puzzles me is that while this shift is happening, a lot of AI communities are focused on building more apps. Wrapper tools with a nice front end on top of an LLM call. Build ten, charge a subscription, stack income. But if agents are becoming the interface layer, another standalone tool is just another tab to keep open. The value is moving to orchestration across your existing tools, not more widgets. For anyone building a personal brand or marketing business with AI, this raises real questions. If agents become the discovery layer instead of app stores and search engines, what happens to how people find your content? If your customers stop opening tools and start asking agents to do things for them, does your product need to be agent-friendly rather than just user-friendly?

Anthropic just published their AI Fluency Index, and the standout finding is one we should all be thinking about. 85.7% of the most "fluent" AI conversations involved iteration and refinement, treating the first response as a starting point, not a finished product. Those conversations showed double the AI fluency behaviours compared to quick, one-and-done exchanges. The data makes a strong case for treating AI as a thought partner rather than a vending machine. The more you push back, ask follow-ups, and refine within the same conversation, the better the output, and the better you get at using it. A few practical takeaways I found useful: - Stay in the conversation. Don't take the first answer and run. Refine it. - Question polished outputs. Ironically, the research found that when AI produces something that looks finished, a doc, code, an artifact, users become less likely to critically evaluate it. That's a trap worth knowing about. - Set the terms upfront. Only 30% of users tell Claude how they want it to interact with them. Try prompts like "Push back if my assumptions are wrong" or "Tell me what you're uncertain about." For anyone doing AI-assisted marketing work, this is a good reminder: the magic isn't in the prompt, it's in the conversation. What habits have you built around iteration in your AI workflows? https://www.anthropic.com/research/AI-fluency-index?utm_source=aitoast.beehiiv.com&utm_medium=newsletter&utm_campaign=ai-can-now-find-your-exact-location

So many ch-ch-ch-ch-changes in models recently, and we just witnessed the first big extinction event in the history of AI since the release of ChatGPT in 2022. Every platform deprecates their models for different reasons and at different times, but January/February 2026 was tectonic. In order to track these extinction events and the overall evolution of the space, I recently updated The Great AI Explosion app to help keep everyone (who cares!) in the loop. I'll be improving this app over time so it can be a true resource, and I would be more than open to hearing what features you would appreciate seeing in an app like this. DM me or provide feedback right here in the thread (if that's OK with Ryan!).

This video covers a Claude Skills Hack that will improve your AI results. Learn how to repurpose any Claude skill markdown file, personalize it with your own context, and get a new custom skill built in Claude Code for your specific situation. As always be sure to Like/Comment/Share if you found this helpful 🫡