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Writer's pictureDerrick Edward

o1 Release: Why We're Not Rushing to Pro Mode

Here's the thing about major AI releases - they're exciting, they're promising, and they often come with a hefty price tag that makes us pause and think. The recent o1 and Pro Mode release from OpenAI is no exception. We've dived into the research and analysed benchmarks. Let's talk about what we've discovered.



Beyond the Buzz


You've probably heard the excitement around o1 and its Pro Mode variant. The marketing is compelling, and yes, there are improvements. But here's what's really interesting - the standard O1 model (the $20/month tier) is doing most of the heavy lifting. The Pro Mode's $200/month price tag? That's where things get interesting


There is no model card for the o1 Pro Mode, which leads us to believe that it is aggregating multiple responses from the o1 model and selecting the majority-vote answer. While clever, it's a bit like buying three cars to make sure you get to work on time - expensive and probably not the most efficient solution.





The Numbers That Matter


Let's break this down in real terms:


  • Standard o1 ($20/month): We're seeing 80-90% of what you actually need

  • o1 Pro Mode ($200/month): Sure, it's better, but marginally

  • Claude 3.5 Sonnet: Keeping pace and often pulling ahead


The gains from Pro Mode often don't translate into meaningful productivity improvements for most business workflows.



The Real Efficiency Story


Remember when we all upgraded our laptops to get that 5% performance boost? Pro Mode feels a bit like that. Here's why:


  1. Each query uses significantly more compute power

  2. You're waiting longer for responses

  3. The quality improvement isn't proportional to the cost




What's Actually Working


Through our conversations with businesses and analysis of implementation patterns, we're seeing a clear trend. The organisations getting the most value aren't necessarily the ones using the most expensive tools. They're the ones being smart about their existing resources.


Smart Implementation Looks Like This:


  1. Getting creative with standard models

  2. Building solid prompt engineering practices

  3. Actually measuring what matters (yes, we mean ROI)


ROI That Makes Sense:


  1. Track those time savings (but be honest about them)

  2. Document your wins (and your lessons learned)

  3. Measure what's actually improving

  4. Know your real costs


The best success stories we've analysed aren't about having the fanciest AI - they're about having the clearest understanding of what they need to achieve.




The Road Ahead


The AI landscape moves fast - we all know that. While Pro Mode might not be the game-changer it's marketed as today, we're keeping our eyes on how it evolves. The key is building a foundation that can adapt to whatever comes next.


Making It Happen


Ready to make this practical? Start here:


  1. Take stock of your current AI tools (and how you're actually using them)

  2. Find those workflows that are eating up hours of time

  3. Start measuring - seriously, measure everything

  4. Build your team's AI muscles (it's not just about the tools)



The Bottom Line


Here's what it comes down to - AI isn't about having the most expensive tools. It's about having the right tools and knowing how to use them effectively. Right now, our analysis shows that Pro Mode is a solution looking for a problem that most businesses don't actually have.


We're passionate about helping organisations make smart AI investments that drive real value. If you're wrestling with these decisions, let's have a conversation about what makes sense for your specific context. No hype, no pressure - just practical, research-backed guidance for your AI journey.


Curious about how to make the most of your current AI investments? We're here to help you cut through the noise and find what actually works.




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