Future-Proofing Yourself in the Age of AI: Insights from Antony Slumbers

In our latest episode of the Project Flux podcast, we welcomed back a familiar voice—Antony Slumbers, creator of "Generative AI for Real Estate People" and one of our most thought-provoking guests to date. This marked a special milestone as Antony became our first-ever returning guest, a testament to the value and depth of insight he brings to discussions about AI's impact on our professional lives.

When we last spoke with Antony (back in Episode 21), we explored his background and expertise in the real estate sector. This time, our conversation ventured into more personal territory: "What's going to be the impact on individuals of all of this?" As Antony put it, whilst we often discuss AI's transformative effects on companies, cities, and society at large, the question of how individuals can navigate this rapidly evolving landscape deserves equal attention.

"I'm really interested in how an individual can future-proof themselves," Antony explained. "How can they make AI a feature, not a bug?" This framing perfectly captures the essence of our discussion—not whether AI will change our professional landscape (it undoubtedly will), but how we can position ourselves to thrive amidst these changes rather than merely survive them.

As our education systems continue preparing young people for a world that, in many ways, will no longer exist by the time they graduate, Antony's insights offer a valuable compass for navigating the AI revolution. Whether you're just starting your career or have decades of experience, his framework for future-proofing yourself deserves serious consideration.

The Four Super Skills for Future-Proofing Your Career

What skills will truly matter in an AI-powered future? According to Antony, there are four essential "super skills" that will help individuals thrive regardless of how technology evolves:

1. Exceptional Human Skills

"You are going to need to be a really damn good human," Antony emphasised. In an era of exponential technological advancement, our uniquely human capabilities become exponentially valuable. This isn't just about basic interpersonal skills—it's about developing an extraordinary capacity for empathy, connection, and communication.

As AI systems handle increasingly complex analytical tasks, our ability to build relationships, understand nuanced emotions, and navigate social dynamics becomes a key differentiator. Many professionals haven't prioritised these "soft skills" historically, but they'll soon become non-negotiable for career resilience.

2. Critical Thinking as Muscle Memory

We're entering an era where distinguishing reality from fabrication becomes increasingly challenging. "I don't know if you're real, I don't know if what I'm hearing is real, I don't know if what I'm reading is real," Antony observed, highlighting the growing difficulty of information verification.

The solution? Developing critical thinking that activates instinctively—what Antony describes as "muscle memory, like Gary Lineker sitting in the six-yard box." Just as elite athletes respond without conscious deliberation, we must cultivate the ability to automatically question, evaluate, and contextualise information.

This skill becomes particularly crucial as research shows people's growing tendency to defer to algorithmic judgments without scrutiny. "One of the absolute guaranteed ways to have a bad future is to stop thinking and allow the machines to think for you," Antony warned.

3. Problem-Solving Capabilities

The ability to deconstruct complex challenges into manageable components will remain invaluable. "How do we break this up into component parts? How do we eat the elephant one spoonful at a time?" Antony asked rhetorically.

This methodical approach to problem-solving—identifying core issues, establishing frameworks, and developing systematic solutions—will distinguish valuable contributors in any field. While AI can process vast amounts of data, human judgment in framing problems and evaluating potential approaches remains essential.

4. Data and Analytical Literacy

You needn't become a data scientist, but a fundamental understanding of data's importance, structure, and limitations will be crucial. "You need to have a much stronger awareness of the importance of data and the component parts of data and what data represents and biases," Antony explained.

As organisations increasingly make data-driven decisions, professionals who can intelligently interpret, question, and contextualise data analysis will maintain their relevance and influence. This includes understanding both the power and limitations of the data informing AI systems.

Antony's framework aligns with Meta's AI chief Yann LeCun's perspective that "humans are the apex species" and must maintain agency over machines. These four super skills collectively ensure we remain in control of technology rather than becoming subservient to it.

The Human-AI Relationship: Complementary Not Competitive

When discussing the future relationship between humans and AI, Antony offers a refreshingly nuanced perspective that challenges some of the more sensationalist narratives dominating public discourse.

Unlike futurists like Ray Kurzweil who envision humans merging with AI, Antony takes a more humanistic stance. "I'm not sure we do want to merge... I've got a history of art degree, so I'm a lovey under all this. I like humans," he shared with characteristic candour. This perspective informs his vision of AI as a complementary capability rather than something that should replicate or replace human intelligence.

One of the most thought-provoking questions Antony raised was: "Why on earth are we trying to build systems that can do everything we can do? I mean, honestly, why are we doing that? Why aren't we building systems that can do what we can't do?" This fundamental reframing challenges the prevailing approach to AI development and suggests a more productive direction—creating technologies that extend human capabilities rather than merely mimicking them.

This complementary relationship requires thoughtful design, particularly regarding when and how humans should remain in the loop. "When you're designing what you want one of these things to do, you've got to think: at what stage in this process do we insert a human?" Antony explained. While some processes might not require human intervention (as he put it, "two plus two equals four, just do it"), most complex scenarios benefit from human judgment at strategic points.

The challenge lies in identifying "where does the human add a dimension that the machine cannot do on its own." This requires what Yoshi aptly described as "a higher level of metacognition"—understanding not just what we know, but how we know it, and where human intuition and judgment provide irreplaceable value.

AI as Your Personal Thought Partner

One of the most compelling aspects of our conversation with Antony was us discussing using AI as a thought partner—a tool that extends our cognitive capabilities in unprecedented ways.

"I read in commerce a lot more now, but I don't actually read anymore," Antony explained, describing how he downloads reports, uploads them to tools like Notebook LM, and has them converted into audio summaries. "What that enables me to do is ingest a huge amount more than I ever could before." This approach allows him to cover significantly more ground, returning to source materials only when a topic warrants deeper exploration.

This capability becomes particularly valuable when tackling content that would otherwise be inaccessible. "I like reading about all these academic papers that the research labs put out. Now I can't read them—if I try and actually read them, it's just a page full of maths, it means absolutely nothing to me," Antony admitted. By using AI to translate complex academic content into accessible explanations, he can engage with ideas that would otherwise remain impenetrable.

Antony has taken this approach further by customising how AI processes information for him: "I stick those into Notebook and then I give it the customisation of 'please can you look at this through the lens of a commercial real estate professional? How might anything in this impact on the commercial real estate world?'" This personalisation transforms general knowledge into contextually relevant insights.

This represents what Antony aptly calls "a superpower" that democratises access to complex information. Different professionals can process the same content through their unique professional lenses—architects, project managers, and real estate professionals can each extract relevant insights from the same source material.

Perhaps most intriguingly, AI can serve as a virtual mentor, particularly for younger professionals. "These tools are going to be the most amazing virtual mentors for younger people that are actually going to be able to compress probably 20 years of learning into five years if we do it right," Antony suggested. This accelerated learning curve could help bridge experience gaps and provide guidance that might otherwise be inaccessible.

As James noted, this capability democratises intelligence: "Everyone's going to have access to the same intelligence. And then it goes back to what you said right at the beginning of the podcast, which is the people skills, the communication, the way that you actually use that knowledge." In this way, AI may paradoxically make our uniquely human capabilities more valuable than ever.

The Changing Information Landscape

The way we consume and process information is undergoing a profound transformation, and Antony's insights illuminate both the opportunities and challenges this presents.

"I think there's going to be a divide between the type of person that really leans into all of this and thinks, this is great. I can now ingest so much more, I can know more about more about everything," Antony observed. This divide is already emerging, with some professionals leveraging AI to dramatically expand their knowledge base while others remain hesitant.

James offered an interesting reframing of this shift: "You say that there's less people who read, but then if we turn that word around slightly and say, do you think less people are ingesting information, then the answer is probably no." The democratisation of knowledge continues, but the medium is evolving—from traditional reading to podcasts, audiobooks, and AI-processed content.

This evolution extends to content creation as well. Antony highlighted a conversation with a technology leader at a major real estate advisory firm who advocated for making research reports machine-readable: "Everyone puts out all these research reports, how many people actually read them, but the machines will read them and you need to start thinking like that."

James extended this thought: "When you're writing a report of research, you have to assume that the vast majority of people won't read it. It will just be referenced by an LLM or something." This suggests a fundamental shift in how we should approach content creation—optimising not just for human readers but for AI systems that will process and recontextualise the information.

As Yoshi noted, referencing Andre Karpathy's perspective: "Everything that we write at the moment is created for the human mind... But then he said, actually, what you need to be doing is making everything machine readable." While this might seem counterintuitive, it acknowledges the reality that AI increasingly serves as an intermediary between information and human consumers.

Amidst this changing landscape, Antony emphasised the continued importance of deep concentration: "The ability to concentrate deeply on something... it's built into those four skills, but it's an important thing to really get your head around." As James noted, this capacity for sustained focus becomes increasingly rare and valuable in an era of constant distraction and information overload.

The Challenge of Innovation and Growth

As AI capabilities expand, organisations face a critical strategic choice: use these tools merely to reduce headcount or leverage them to pursue ambitious growth and innovation.

"If James and Yoshi are 10x more productive, but the pie stays the same, the quantum of work stays the same, you need less people," Antony acknowledged. This reality creates powerful incentives for workforce reduction, particularly in shareholder-driven environments. "The incentives of a CEO to sack as many people as they possibly can is huge because the share price always goes up."

However, Antony advocates for a more visionary approach: "I think the smarter action is going to be, well, now I've got Yoshi and James and we can be 10 times more productive. Well, let's go and grow the business 10 times." This growth mindset represents a fundamental shift from efficiency-driven cost-cutting to opportunity-driven expansion.

This expansion could address challenges previously considered too complex to tackle. "There's the UN sustainable development goals, there's 17 of them. And I say, well, when you've fixed all those, come back and worry about there not being any work to do," Antony remarked. "So many of those development goals we don't really address because they're too big, they're too wicked. We can't cope with them."

In his more optimistic moments, Antony envisions AI enabling humanity to address these grand challenges: "What I'd like to see is these tools enabling us humans to fix all those things." Rather than merely optimising existing processes, AI could help us tackle previously insurmountable problems.

James echoed this sentiment: "I'm hoping what this will do will encourage businesses to be more innovative because you can go and try and you can fail fast." The reduced cost of experimentation could fundamentally change risk calculations around innovation. "I'm hoping that humanity will rise to the challenge that's been given to them, which is you don't have any excuses anymore. Whatever you can dream of, you can do."

This perspective reframes AI not as a threat to employment but as an enabler of previously impossible ambitions. As Antony put it, the essential question becomes: "What does this enable?" Organisations and individuals who focus on this question—rather than merely on efficiency gains—will likely discover entirely new domains of value creation.

Practical Applications: AI Tools Worth Exploring

Throughout our conversation, Antony highlighted several AI tools that have transformed his workflow and could provide similar benefits to others seeking to future-proof their careers.

Notebook LM: Your Information Processing Assistant

Antony described how Notebook LM has revolutionised his information consumption: "I'll get some new report, I just immediately download it, upload it to Notebook, push create, create a podcast." This allows him to listen to summaries while driving, dramatically increasing the volume of information he can process.

Beyond simple summarisation, Notebook enables customised analysis: "Please explain this to a humanities graduate" or "Please can you look at this through the lens of a commercial real estate professional?" These prompts transform general information into personally relevant insights.

Deep Research: Transparent Reasoning

The reasoning capabilities of modern AI tools particularly impressed Antony: "What I find incredibly interesting with these is when they respond, they first go through this process of telling you what they're thinking about, the thinking process."

This transparency provides a window into comprehensive analytical approaches that many of us neglect: "I tell you what it has made me think though, I don't think hard enough. You look at these and it goes through all these different variables that you should look at. I think, I haven't taken that into account."

Yoshi highlighted how different models approach this reasoning process: "When you look at DeepSeek's chain of thought reasoning, it has an internal monologue like a human... it will say, 'Oh, but I should do this. Oh, maybe I should do this. Oh, but he mentioned this.'" This human-like reasoning process can help us develop our own critical thinking skills.

Claude 3.7: Extended Thinking Mode

For complex analytical tasks, Antony praised Claude 3.7's extended thinking capabilities: "I was using Claude 3.7 in the new extended thinking mode. It's fantastic. God, it is so good." He described using it to break down sustainability frameworks into component parts, identifying necessary data inputs and processing steps.

The depth and detail possible with these advanced models surprised even experienced users like Antony: "I was pushing a prompt harder than I've ever done. And it sort of amazed me. It took about 10 minutes to print out the answer. And it was extraordinary."

The Prompt Engineering Approach

Rather than treating AI as a simple search engine, Antony emphasised the importance of thoughtful interaction: "Talk to the models, ask the models what you need to know, but push them hard."

Yoshi offered a meta-approach to prompt engineering: "If you want to write the best prompt for a model, just ask a model to develop you a meta prompt. Ask a prompt to build you a prompt." This recursive approach leverages the AI's own understanding of its capabilities.

As James noted, many users still approach these tools with outdated mental models: "People still treat it like Google. The number one complaint I get is, 'I tried it and I typed something in and it was rubbish.'" The shift from keyword-based queries to conversational, context-rich prompts represents a fundamental change in human-computer interaction.

Conclusion: Maintaining Human Agency in the AI Era

As we reflect on our conversation with Antony Slumbers, several powerful themes emerge that can guide our approach to future-proofing ourselves in the age of AI.

The four super skills Antony identified—exceptional human capabilities, critical thinking as muscle memory, problem-solving prowess, and data literacy—provide a robust framework for professional development. Rather than competing with AI on processing power or memory, these skills leverage our uniquely human attributes whilst complementing technological capabilities.

Perhaps most importantly, Antony's perspective encourages us to maintain human agency in our relationship with technology. "One of the absolute guaranteed ways to have a bad future is to stop thinking and allow the machines to think for you," he warned. This caution applies equally to individuals and organisations—we must remain conscious of where and how we delegate decision-making to algorithmic systems.

At the same time, Antony's approach is fundamentally optimistic. He envisions AI as a tool that can help us tackle previously insurmountable challenges, from the UN Sustainable Development Goals to complex business problems. "What does this enable?" remains the essential question—one that focuses on possibilities rather than limitations.

The transformation of our information landscape presents both opportunities and challenges. Those who embrace AI as a thought partner can dramatically expand their knowledge base and processing capacity. As Antony demonstrated with his use of tools like Notebook LM, Claude, and Deep Research, we can now engage with complex information that would previously have remained inaccessible.

For younger professionals, AI offers unprecedented opportunities for accelerated learning. "These tools are going to be the most amazing virtual mentors for younger people that are actually going to be able to compress probably 20 years of learning into five years if we do it right," Antony suggested. This potential for compressed experience could fundamentally change career trajectories.

As we navigate this rapidly evolving landscape, Antony's parting advice resonates strongly: "Talk to the models, ask the models what you need to know, but push them hard." This active, questioning approach—treating AI as a collaborative partner rather than an oracle—exemplifies the balanced relationship we should strive to develop with these powerful tools.

By developing our super skills, maintaining our agency, and thoughtfully leveraging AI capabilities, we can do more than merely survive the AI revolution—we can use it to expand our horizons and tackle challenges that once seemed beyond our reach. The future belongs not to those who resist technological change nor to those who surrender their agency to it, but to those who forge a complementary relationship that amplifies uniquely human capabilities.