#19-Heaven let AI Shine Down: Spiky Interview, The Next Decade of AI, Why People Fail when Using AI, and LUSTER LAUNCH

First and foremost, I decided to move the newsletter and podcast to come out on Tuesday morning from this week forward!

As a reminder, GTM AI Academy is an AI enablement and consulting company where we provide education, training, and advice on how to use AI in your GTM teams, companies, and individual use.

Business Impact> Learning Tools

Few things before we jump in:

1. We have LAUNCHED the FREE Slack Community , come hang with your fellow GTM professionals, get insights, and content free to help in your teams and roles.
2. The GTM AI Demo Tools Library is a free resource for you to view AI tools and demos to see what is out there to help your team or to help you in your own workflow.

Now with all that being said, lets move forward with todays newsletter which is:

1. We have #19 Podcast with Burak Aksar, PhD of Spiky.AI where we dive into one of my favorite conversations regarding AI and what his team are doing in conversations and recorded calls that is different than both competitors like Gong or free tools like Fathom.
2. Situational Awareness: The Decade ahead in AI, an ex OpenAI employee talks about where he thinks things are going after being in the inner circle of AI researchers.
3. Why 99% of people I talk to are failing or not getting what they want when working with ChatGPT, Claude, or Gemini...
4. GTM AI Tool of the week: Luster

You can go to Youtube , Apple , Spotify , or here on Linkedin as well as a whole other host of locations to hear the podcast or see the video interview.

https://spiky.ai/

Leveraging AI for Revenue Intelligence: Insights from Burak Aksar, Co-Founder of Spiky

Summary:

In this episode of the GTM AI podcast, host Jonathan welcomes Burak Aksar, co-founder and software engineer at Spiky, an AI-powered revenue intelligence platform. Burak shares his journey from a technical background in machine learning to the world of go-to-market and sales. He discusses how Spiky leverages AI to analyze customer conversations, measure non-conversational metrics, and provide actionable insights to help teams optimize their revenue processes. Burak also shares his thoughts on the current state of AI in business and what he's excited about for the future.

Highlighted Concepts:

- Revenue intelligence: Analyzing data from various sources (sales, customer success, support, product, engineering) to optimize revenue processes

- Non-conversational metrics: Measuring up to 60 different metrics per second, including vocal, visual, and contextual data, to provide insights beyond just transcripts

- Actionable insights: Identifying trends across customer conversations and tying them to revenue outcomes

- AI stack: Utilizing a combination of proprietary models, open-source, and closed-source APIs to power the Spiky platform

- Explainable AI: The importance of making AI models transparent, scalable, and ethically sound

Quotes from Burak:

- "The revenue domain is already very complicated, and I think no one has figured out yet, including us, what are some winning behaviors and how do I basically apply this at scale?"

- "If you don't understand, I don't think you can optimize any process. It can't, it doesn't need to be revenue, but the things that I'm like really excited, if I flip the page a bit, I think, like we've been expecting this, but the large language models are becoming a commodity."

- "I think making these ethically, like ethically, successful is a very big challenge because let me make an analogy here. Even explaining one decision tree or random forest, it's super hard. Like it doesn't make sense to humans."

Why this matters to GTM professionals:

This podcast episode provides valuable insights for GTM professionals looking to leverage AI to optimize their revenue processes. Burak's expertise in both machine learning and go-to-market strategies offers a unique perspective on how AI can be used to analyze customer conversations, identify trends, and provide actionable insights. By understanding the potential of AI-powered revenue intelligence platforms like Spiky, GTM professionals can make data-driven decisions to improve their sales processes, prevent churn, and ultimately drive revenue growth. Additionally, Burak's emphasis on the importance of explainable and ethical AI serves as a reminder for GTM professionals to carefully consider the implications of AI adoption in their organizations.

The website “Situational Awareness: The Decade Ahead” by Leopold Aschenbrenner discusses the rapid advancements in AI, predicting that AGI (Artificial General Intelligence) will surpass human intelligence by the end of the decade. It highlights the significant investments in AI infrastructure, the potential economic and military impacts, and the security challenges posed by AGI. The site outlines the expected timeline for these developments, emphasizing the need for strategic planning and security measures to manage the transition to superintelligent systems.

Leopold Aschenbrenner is the founder of an investment firm focused on Artificial General Intelligence (AGI), with anchor investments from prominent figures such as Patrick Collison, John Collison, Nat Friedman, and Daniel Gross. Before founding this firm, he worked on the Superalignment team at OpenAI. Leopold also has a background in long-run economic growth research at Oxford’s Global Priorities Institute. Originally from Germany, he now resides in San Francisco, California.

Introduction

Artificial Intelligence (AI) has been advancing at a rapid pace, and we're on the brink of an extraordinary transformation. The transition from GPT-4 to Artificial General Intelligence (AGI) and ultimately to superintelligence is a topic of great importance for professionals in the GTM (Go-To-Market) space. This newsletter will break down these advanced concepts and explain why they matter to you as a GTM professional.

Understanding the Transition from GPT-4 to AGI

1. Orders of Magnitude (OOM) in AI Progress

- Concept: OOM refers to a logarithmic scale used to measure significant increases in AI capabilities. Each OOM represents a tenfold increase in computational power or algorithmic efficiency.

- Importance: Understanding OOM helps predict the pace of AI advancements. For instance, GPT-4's development involved approximately 1.5 to 2 OOMs of compute increase compared to its predecessor, GPT-3 [oai_citation:1,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ) [oai_citation:2,II. From AGI to Superintelligence: the Intelligence Explosion - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-agi-to-superintelligence/ ).

2. Computational Scaling

- Compute Requirements: The leap from GPT-4 to AGI necessitates substantial scaling of compute resources. This involves clusters with capacities far exceeding current standards, driven by massive investments in AI infrastructure [oai_citation:3,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ) [oai_citation:4,IIIa. Racing to the Trillion-Dollar Cluster - SITUATIONAL AWARENESS](https://situational-awareness.ai/racing-to-the-trillion-dollar-cluster/ ).

- Infrastructure Investment: Companies like Microsoft and Google are making huge investments in specialized hardware and data centers, setting the stage for AGI development [oai_citation:5,IIIa. Racing to the Trillion-Dollar Cluster - SITUATIONAL AWARENESS](https://situational-awareness.ai/racing-to-the-trillion-dollar-cluster/ ).

3. Algorithmic Advances

- Efficiency Improvements: To achieve AGI, significant advancements in training techniques and model architectures are essential. Methods like reinforcement learning from human feedback (RLHF) and chain-of-thought (CoT) help unlock latent capabilities in AI models [oai_citation:6,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ).

- Unhobbling Models: Removing constraints on models to enhance their performance, allowing them to utilize their full potential [oai_citation:7,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ).

4. Automated AI Researchers

- Automated Research: AGI will leverage automated AI researchers capable of conducting research at speeds far greater than human capabilities. This could accelerate AI advancements, compressing decades of research into a much shorter timeframe [oai_citation:8,II. From AGI to Superintelligence: the Intelligence Explosion - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-agi-to-superintelligence/ ).

- Massive Parallelization: Deploying millions of automated researchers working in parallel will dramatically increase the pace of AI development [oai_citation:9,II. From AGI to Superintelligence: the Intelligence Explosion - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-agi-to-superintelligence/ ).

5. Milestones and Predictions

- Timeline: The path from GPT-4 to AGI involves incremental steps marked by significant improvements in AI capabilities. Estimates suggest AGI could be achieved within the next decade [oai_citation:10,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ) [oai_citation:11,IIIa. Racing to the Trillion-Dollar Cluster - SITUATIONAL AWARENESS](https://situational-awareness.ai/racing-to-the-trillion-dollar-cluster/ ).

- Expected Breakthroughs: Each step forward will likely bring new breakthroughs in solving complex benchmarks and enhancing reasoning abilities [oai_citation:12,I. From GPT-4 to AGI: Counting the OOMs - SITUATIONAL AWARENESS](https://situational-awareness.ai/from-gpt-4-to-agi/ ) [oai_citation:13,IIIa. Racing to the Trillion-Dollar Cluster - SITUATIONAL AWARENESS](https://situational-awareness.ai/racing-to-the-trillion-dollar-cluster/ ).

Why This Matters to GTM Professionals

1. Strategic Planning

- Future-Proofing Your Strategy: Understanding the trajectory of AI advancements helps GTM professionals plan strategically for the future. Anticipating how AI will transform industries allows for proactive adaptation and innovation.

2. Competitive Advantage

- Leveraging AI Capabilities: By staying informed about AI developments, GTM professionals can leverage cutting-edge AI tools to gain a competitive edge. This includes utilizing advanced AI for market analysis, customer insights, and predictive analytics.

3. Operational Efficiency

- Enhanced Productivity: Automated AI systems can streamline operations, reduce costs, and increase productivity. For example, AI-driven automation can handle repetitive tasks, allowing teams to focus on higher-value activities.

4. Customer Engagement

- Personalized Marketing: Advanced AI enables highly personalized marketing strategies, improving customer engagement and satisfaction. By leveraging AI, GTM professionals can deliver tailored content and recommendations to individual customers.

5. Risk Management

- Mitigating AI Risks: Understanding the potential risks associated with powerful AI systems is crucial. GTM professionals need to be aware of ethical considerations and governance issues to ensure responsible AI deployment.

Conclusion

The journey from GPT-4 to AGI represents a transformative era in AI development. For GTM professionals, this transition offers immense opportunities to enhance strategic planning, operational efficiency, and customer engagement. By staying informed and leveraging advanced AI capabilities, GTM professionals can navigate this evolving landscape and drive significant business growth.

Here is why 99% of people I talk to are failing or not getting what they want when working with ChatGPT, Claude, or Gemini...

The prompts they use are barely scratching the surface of what is possible with AI and in the GTM AI Academy we deep dive into this.

Let me give you an example, here is a type of prompt I see online and when I see prompt libraries, they look like this:

You are an?Enablement Expert?and?very good with creating online resources for learning.?Create a summary of the?Persona Messaging?course, including?5 learning goals, overview of modules,?key learning goals?and an abstract for each module within the course.

At first glance the above is not bad, but most people will only get 20-40% to as close as they need to get to their desired output.

Here is the issue:

1-It lacks detail

2-It lacks structure

3-It lacks specific instructions & guidance

4-It lacks context about the company, methodology, etc

To get 90% of the way of what you want, you need better input aka prompt, so lets change the above a bit and use the GRACE? Framework which is:

Goal or Role: Define the goal or role for which you need information from the AI tool.

Rules: Set clear rules for the AI tool to follow, ensuring quantifiable and relevant KPIs, unique competencies, and specific observable skills.

Advanced Context: Provide as much context as possible to help the AI tool generate more specific and tailored responses.

Clear Instructions: Communicate your requirements clearly to the AI tool by providing detailed instructions on what you need.

Examples: Include examples or samples of what you are looking for in the prompt to guide the AI tool in generating the desired information.

An example is like this:

*Goal or Role:

*You are an Enablement Expert and very good with creating online resources for learning. You excel at breaking down complex content into digestible learning modules. Your task is to create a comprehensive summary of the Persona Messaging course for learners.

*Rules:*

? You MUST take a deep breath, go step by step, and be thorough in your output.

? You MUST base your responses based on the given information regarding [ADVANCED CONTEXT] which includes methodology, company info, and product as well as key personas

? You MUST follow the example given in the [EXAMPLES] section below, only use it as a guide and template in the output

? You MUST confirm understanding or ask 5 clarifying questions in order to fulfill the original request

? You MUST Ensure the abstracts are unique and specific to each module.

*Advanced Context:

*(Include company info, value prop, key personas, or titles, methodology, product info each under its own section title, usually copy pasted from company website if needed)

*Clear Instructions:*

? 5 clear and concise learning goals for the course.

? Instruction 2, etc

*Examples:

*(copy paste in an example of what output you are looking for or create it with AI)

The goal is to literally have an example that the AI can mimic or copy when it responds to you.

Try this out and tell me what you think!

I am so excited to have had a back end look at Luster the last few months and seeing what the team over there is cooking up. It will be game changing my friends with their concept around Predictive Enablement?

Christina Brady , CEO and co-founder of Luster.ai , and ex-guest on the GTM AI Academy podcast, emphasizes that the platform is designed to augment, not replace, traditional sales training methods. By providing a space for sales professionals to practice and perfect their skills, Luster.ai aims to empower teams to achieve greater success in their sales engagements. The tool’s customer-centric design and robust AI capabilities make it a must-have for any sales team looking to stay ahead in a competitive market.

For GTM professionals, the integration of AI into sales training represents a significant step forward. It offers a scalable, efficient, and highly effective way to enhance team performance, making Luster.ai an essential tool in the modern GTM and enablement tech.

Why Should GTM Professionals Care About Luster.ai ?

1. Predictive Enablement?:

Luster.ai introduces the concept of Predictive Enablement?, allowing sales teams to identify training and coaching gaps before they impact deals. This proactive approach ensures that reps are always prepared, improving deal velocity and overall performance? .

2. Realistic Simulations:

The platform offers hyper-realistic customer simulations that mimic real-world selling scenarios. This “perfect practice” environment helps sales reps refine their techniques and build confidence by repeatedly tackling common objections and challenges they will face with actual customers.

3. Data-Driven Insights:

Luster.ai provides real-time analytics and individual feedback, allowing sales managers to tailor coaching to each rep’s specific needs. Team dashboards offer insights into overall performance, helping to inform and optimize sales strategies? .

4. Enhancing Engagement and Skill Development:

Gamified elements keep sales reps engaged, making the training process not only effective but also enjoyable. This engagement is crucial for maintaining consistent practice and ensuring that new skills are retained and applied effectively in real-world situations.

5. Security and Compliance:

Luster.ai is SOC 2 compliant, ensuring that all data is handled securely. This commitment to security gives GTM professionals peace of mind, knowing that their training data and insights are protected.

Ok my friends, that is all for me this week, let me know what you think!