Having an AI Mindset

It's the process

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Friends,

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I was intrigued to read that the New York Times recently introduced AI for in-house tasks: writing headlines, drafting social copy, and helping with code. This decision signalled an important shift. Teams there are now experimenting with Echo, a summarisation tool built by their in-house development. They are also using GitHub Copilot and other AI options for faster product development. !t’s a big deal for me that large news organisations have embraced technology to simplify everyday work - and it should be for you too.

In ad hoc conversations I have had over the last 6 months, there are a few camps:

1. The "I don’t knows" who are not quite sure what they should be doing, other than using Chat-GPT for some research - and it potentially doesn’t apply to their traditional business.

2. The “We’re strategically planning” because it seems too scary to dip a toe in because of their business (Usually, it’s too big or important or niche)

3. The phrase “we’re doing lots” invariably implies that there are many pockets of unorganized innovation, which may not be very strategic.

4. “It’s top of our agenda” and they’re working on shifting the business, looking for cost savings and revenue opportunities - and figuring out agentic workflows.

5. “We’ve changed our whole business around this opportunity.” (as well as those businesses which are AI-first or AI-only)

The New York Times fits into category 4. Big enterprises and lean startups alike have pivoted toward AI. Many are using it to automate administrative tasks, schedule meetings, or draft documents. Others have gone deeper, saving billions by adopting AI in logistics, supply chains, and finance. Often, these moves start small, a simple chatbot or a test run of generative AI, and then spread as leaders see the efficiency gains.

Some highlights:

Two-thirds of organisations worldwide now use AI in at least one function.

Global corporates like SAP and ExxonMobil expect multi-billion-dollar savings through automation.

Slack envisions AI coworkers who handle meeting notes and project updates, freeing humans to focus on trickier problems.

Hospitals are using AI for patient triage and scheduling, boosting margins while giving care teams more face time with patients.

People who take this seriously talk about AI as a “new industrial revolution”, myself included, a sort of mechanical shift replaced by a digital wave. The main challenge is not the tech itself. It’s leadership. Companies that rewrite their workflows and reskill teams see bigger wins. Those who hesitate? They keep daily routines tangled in manual tasks. But once AI takes hold, staff suddenly have time to do real thinking. We start to elevate our own skillsets and abilities. Managers see faster output, fewer mistakes, and a culture more open to experimentation.

It’s not magic. AI can and will still stumble. Teams often start with low-risk tasks before trusting AI to handle complex work. When done right, though, businesses discover surprising bandwidth. They offload the drudgery, find shortcuts, and reimagine operations. In a nutshell, this is how they gain an edge in the AI journey. It doesn’t matter whether it is Grok3 today or Mistral tomorrow. What matters is the AI Mindset and applying it to the problems you have.

Stay Curious - and don’t forget to be amazing,

Rahim

Here are my recommendations for this week:

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Now

1. We all know too much about each other - Social platforms and location-sharing apps have reframed how we see each other, which sets a new norm of mutual surveillance. This trend has fed anxiety and fear of missing out, with one study highlighting that FOMO is a leading cause of smartphone addiction. It has become common for friends and lovers to track each other in real time, which drains the trust and privacy that relationships require. A pair of wearable rings even claims to track a partner’s heart rate and emotional state, reflecting how far we have gone down this path of constant visibility. Any benefit from these tools often comes at the cost of personal space, and real closeness thrives on respecting boundaries rather than chasing unlimited transparency.

2. Chatbots of the dead - We can now create compelling experiences of talking with our dead. Is this ghoulish, therapeutic or something else again? Chatbots that speak in the voices of those who’ve passed can function as imaginative props rather than attempts at exact recreations of a person. They highlight how memory is rooted in creative interpretation since working with text archives and data can nurture a deeper understanding of someone’s identity. They hold the potential for comforting reflection and historical exploration, yet they also demand thoughtful design choices and ethical care to avoid exploitation or confusion.

3. How to get hired when AI does the screening - AI now drives how many employers sift through applications, and 83% of companies rely on software that checks for exact matches to job-description keywords. You need to tailor your resume with those keywords but avoid letting generative AI do all the work because 69% of HR professionals say they detect and deprioritise AI-generated text. You also need a plan for AI-based interviews, which often measure clarity, body language, and your use of role-specific language.

4. Want a better social life? Try these easy habits. - The research highlights that daily quality conversation—whether catching up, expressing affection, or having a laugh—can foster stronger mental well-being. Even trivial chats with strangers or colleagues make a difference since they grant a sense of belonging without draining energy. Yet these moments must be balanced with time alone, which refreshes us and prepares us to reconnect in meaningful ways.

5. A.I. Is Changing How Silicon Valley Builds Start-Ups - Start-ups are turning profitable sooner by using AI tools for everything from coding to customer support, which drastically reduces the number of people they need to hire. Venture capitalists are still eager to invest, but many founders no longer rely on big funding rounds because AI-driven efficiency lets them build sustainable products with leaner teams. Companies that once would have grown large teams now focus on generalist hires who thrive on a mix of tasks, giving leaders more time to speak with customers to refine their offerings.

Next

1. The hottest AI models, what they do, and how to use them - Just to keep up with the growing and changing list so you know you grok from your Qwen

2. The Inside Story of How Altman and Musk Went From Friends to Bitter Enemies - Altman and Musk founded OpenAI together to steer AI toward the public good but split over control and vision, which prompted Musk to leave and attack OpenAI for straying from its nonprofit ideals. ChatGPT’s massive success caused a power shift, leading Musk to launch xAI, but he failed to match OpenAI’s market dominance or infrastructure deals. Their rivalry escalated when Altman announced a major data centre project called Stargate, blindsiding Musk, who tried to buy OpenAI’s nonprofit arm in a hostile bid, Game of Thronesesque

3. Meta is reportedly developing humanoid robots that help with chores. It aims to develop a humanoid robot software platform similar to how Android powers many smartphones. Meta's robotics initiative will build on its investments in hand tracking, low-power AI, and sensor technology to handle everyday chores like folding laundry. While Meta plans to build prototype robot hardware in-house, it ultimately intends to license the underlying technology for other manufacturers to use in their own robots. This will allow Meta to focus on software and AI rather than producing finished consumer robots.

4. The Great AI UI Unification—ChatGPT’s interface became tangled with too many model choices and sub-menus, prompting OpenAI to unify them so the system automatically selects the right intelligence. This consolidation matters because it aligns with Google's simpler approach with its single search box, reducing friction for both new and advanced users. It also signals a broader trend: AI labs like Anthropic and Google plan to streamline their product lines, integrate chain-of-thought features, and eliminate confusing model pickers in favour of one adaptable system.

5. True AGI Means 10% Economic Growth, Says Satya Nadella - Satya Nadella says economic growth is the best measure of true AGI, pointing to a 10% GDP growth target as the real sign that AI is paying off. He believes the biggest beneficiaries will be regular industries that harness AI for productivity, not the tech giants themselves. Microsoft is pushing toward this future through breakthroughs like topological quantum computing and projects such as Muse, aiming to spark an Industrial Revolution-level impact rather than chasing quick AI milestones.

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