- The Boost
- Refining Productivity in an AI World
Refining Productivity in an AI World
Hi Friends 👋
Did you notice? I am 2 days late this week, I’ve been busy bringing on new The Boost Academy clients. If you’re keen to grow your business too, reply to this email for details.
In this week’s email:
Refining Productivity in an AI World: A 8 min video
ChatGPT can now talk with you
Image creation is coming to ChatGPT
An AI tool to grow on Linkedin
ChatGPT database is now up to date, Bing Search is back
Let’s get started…
AI for Marketing 🔗
Are you looking to grow on Linkedin, but don’t have the time or know where to start? You need to read this. Taplio is the all-in-one, AI-powered tool to grow your personal brand and find leads on LinkedIn. Content creation, scheduling, engaging with other accounts, lead generation, analytics and more! Trusted by 6,100+ LinkedIn pros and creators. Free trial included. [Link]*
Pika is an easy way to create videos from your images. Below is an example of an image I created in Midjourney and then turned into a video using Pika. It’s free to try out via Discord here [Link]
OpenAI’s image generator, DALL·E 3, will soon be accessible to ChatGPT Plus users. The best part? It seamlessly works with ChatGPT, eliminating the need for brainstorming image prompts. Just ask ChatGPT to create one for you. And that's not all, DALL·E 3 can now add text on images too [Link]
ChatGPT has other new features coming. Soon, you can have conversations with it, just like talking to a friend and it will respond to you. You can also share pictures with it, which will help you understand them. ChatGPT is even more of a conversational partner [Link]
Bing search is back! ChatGPT once again browses the internet to provide current information with direct links to sources. Turn on Bing on your ChatGPT by going to ‘Settings & Beta’ > ‘Beta Features’ and toggling the ‘Browse with Bing’ switch on [Link]
Refining Productivity in an AI World
Why you should care: Many AI projects in companies don't succeed. There is too much confusion, and people pick projects that will fail.
What you need to know: How we think about productivity is holding us back. We need to reframe our thinking to ensure automation projects work out.
…ten years ago, electric cars weren’t about and only for the die-hard enthusiasts.
Yet Tesla will make nearly 2,000,000 electric cars this year.
What happened, and what can we learn from this?
Find out in the video below…
(I suggest watching at 1.5x speed)
Takeaways at a glance
We are more productive if we change how we think about work.
We want fast and noticeable results, but meaningful and sustainable results require time.
At the start of a project, work can feel unproductive. But this feeling is crucial for long-term success. It is an essential step of the process that cannot be skipped.
Reframe the “unproductive” feeling work to the part that makes the biggest difference.
0:00 You might believe this module is unrelated to AI, but in fact, it significantly pertains to AI. AI is crucial to enhancing productivity and transforming our perceptions and approaches to it. AI tools like ChatGPT enable us to develop a variety of new workflows and processes that were previously impossible.
0:18 Thus, we need to shift our perspective from operating within the machine and our business to constructing the actual machine.
0:24 Redefining productivity may seem odd, but it is crucial. This concise video of six or seven minutes will hopefully clarify my standpoint.
0:33 This module aims to redefine productivity. Reflect on your most successful growth projects—those continuous sources of benefits. Perhaps they’re marketing campaigns or partnerships. Did success occur overnight, or was it a gradual process?
0:49 Most likely, it was gradual. Exceptional outcomes demand time and seldom feel productive during the building phase.
0:56 Our instinct to hastily construct and attain immediate results, particularly in team management, can create undue pressure, leading to rushed, unfocused efforts.
1:07 In contrast, AI systems and automation necessitate a more measured approach, recalibrating our mindset towards patience and precision.
1:19 Given our innate preference for active, visible productivity, especially under managerial pressure, redefining productivity becomes pivotal. Today, we’ll explore this through a brief instructional video.
1:30 I’ll present a diagram and a ChatGPT prompt designed to retrain your brain, offering a fun and insightful experience.
1:39 We aim to transition from being the machine to building the machine. Our focus should be on creating sustainable, purposeful systems rather than transient, manual tasks.
1:56 Initial unproductive work paves the way for future time savings, especially as we venture into uncharted territories of AI, collaboratively seeking solutions and learning.
2:19 This initial learning and research phase may feel stagnant, but the subsequent diagram will elucidate the relationship between time investment and productivity in AI.
2:29 The graph depicts the correlation between output and time, illustrating various project trajectories, including successful ones that reach the “happy zone” and others that fluctuate between strategies before finding the right fit.
3:38 Some projects may seem unproductive initially but suddenly ascend into the happy zone. Although seemingly stagnant, this phase of research and experimentation is crucial and productive, provided there's a clear, sophisticated plan for automation.
4:13 Examining the progress over one year reveals the diminishing investment of time compared to the consistent productivity of automation projects.
4:52 Understanding and implementing proven technologies strategically in business is highly productive and beneficial in the long run.
5:00 Our objective is to construct self-sustaining, infinitely productive machines. Given the current semi-automated state of AI, incorporating low-cost virtual assistants for non-automatable tasks can optimize the core team’s focus on more intricate aspects.
5:45 ChatGPT can be envisioned as a knowledgeable friend providing extensive information but lacking practical experience. Efficient utilization requires clear, precise prompting and iterative refinement to obtain desired results and to integrate them into automated processes.
7:03 The challenge is to avoid the indiscriminate, distractive use of ChatGPT and to strategically deploy it where it provides consistent advantages, such as in excel or Google Sheets, where it can save significant time and effort by providing accurate formulas and formatting.
7:42 It's crucial to apply the learned insights pragmatically, rather than perpetually seeking novelty.
7:51 The analogy of baking a cake is apt for AI automation processes: successful outcomes depend on the right ingredients and the right recipe. Blind automation without understanding the tools results in chaos. Clear prior understanding of what and how to automate is crucial, and we will cover that, along with the right tools and prompts for GPT, in upcoming modules.
8:20 It may take time, but it is not only acceptable; it’s the most productive approach.
Slow can be fast, especially when you are building an AI machine.
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Thanks for reading,