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Saturday, February 8, 2025

The Power of Graph Technology

While exploring Knowledge Graphs, I came across Tony Seale's insightful series on Embracing Complexity - a fascinating read!

"...The Knowledge Graph is not a product that you can buy off the shelf. It is a way of organizing your data and algorithms in a unified network for each organization to bring its genius to this process..."

In a world of increasing complexity, organizations must move beyond traditional tabular data structures and embrace Knowledge Graphs—dynamic, interconnected networks that unify data, cloud, and AI. The articles highlights how graph-based data models unlock hidden insights by capturing relationships, feedback loops, and abstractions that traditional databases overlook. 

Key tools like Graph Adapters, Data Services, and Graph Neural Networks enable seamless integration of diverse data sources while enhancing AI-driven decision-making. 

A well-structured Knowledge Graph provides a holistic view of an organization, fostering systemic thinking, better change management, and more informed decision-making. As businesses accelerate into the digital age, building a Knowledge Graph is no longer optional but it is essential for survival and growth.

The graph-shaped data enables richer context, while a graph-shaped cloud ensures seamless connectivity across distributed data sources. 

Traditional AI struggles due to its reliance on linear, structured data, but Graph Convolutional Networks (GCNs) offer a breakthrough by incorporating networked relationships into AI learning. 

By embedding intelligence directly into the data-cloud network, organizations can unlock context-aware AI, enabling smarter predictions, systemic automation, and deeper insights. This network-based approach represents a paradigm shift, making AI more adaptive, intuitive, and lifelike for organizations navigating complex data ecosystems.

Its quite an informative read. Please read through all parts.

https://medium.com/@Tonyseale/embrace-complexity-conclusion-fb8be6f39deb

Tuesday, November 26, 2024

Book Summary : 'How to Become a Rainmaker: The Rules for Getting and Keeping Customers and Clients" by Jeffrey J. Fox'

It is is a bestselling guide that offers straightforward, practical advice on how to excel in sales and business development. 

A "Rainmaker" is a term used to describe the seller who consistently brings in new clients, generates revenue, and drives business growth—an invaluable asset to any organization.

Key Lessons from the book:

1. The Rainmaker Mindset:

  • Rainmakers think and act differently from average performers.
  • They focus on delivering value to clients and building long-term relationships.

2. The Rules of Selling:

  • Always sell the benefits of a product or service, not just its features.
  • Ask probing questions to understand what the client truly needs.
  • Follow up promptly and regularly—timing and persistence are critical.

3. Prioritize the Customer:

  • Focus on how you can help clients achieve their goals.
  • Make every interaction about them, not you.

4. Mastering Business Etiquette:

  • Handwritten thank-you notes go a long way in building trust and goodwill.
  • Always be professional, respectful, and courteous in all dealings.

5. Be Results-Oriented:

  • Rainmakers don’t just set goals—they surpass them.
  • They measure success by the results they deliver, not just the effort they put in.

6. Networking and Referrals:

  • Build a network of advocates who can refer you to new opportunities.
  • Reward and thank those who provide referrals to maintain strong relationships.

7. Time Management:

  • Rainmakers focus on high-value activities that directly contribute to revenue generation.
  • Eliminate distractions and prioritize actions that lead to results.

Key Takeaways:

  • Sales Excellence: Sales is about helping people solve problems, not just making a pitch.
  • Focus on Results: Rainmakers are relentless in delivering measurable outcomes.
  • Personal Branding: Build a reputation for reliability, expertise, and professionalism.

Wednesday, November 20, 2024

AI Agents Market landscape.

 ๐—ง๐—ต๐—ฒ ๐—จ๐—Ÿ๐—ง๐—œ๐— ๐—”๐—ง๐—˜ ๐˜„๐—ฒ๐—ฏ๐˜€๐—ถ๐˜๐—ฒ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐—”๐—œ ๐—”๐—ด๐—ฒ๐—ป๐˜ ๐—บ๐—ฎ๐—ฟ๐—ธ๐—ฒ๐˜ ๐—ถ๐˜€ ๐—ต๐—ฒ๐—ฟ๐—ฒ — ๐—œ ๐˜„๐—ผ๐˜‚๐—น๐—ฑ๐—ป’๐˜ ๐—ฏ๐—ฒ ๐˜€๐˜‚๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ๐—ฑ ๐—ถ๐—ณ ๐—ถ๐˜ ๐—ฏ๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ด๐—ผ-๐˜๐—ผ ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ — ๐˜๐—ต๐—ถ๐—ป๐—ธ ๐—ผ๐—ณ ๐—ถ๐˜ ๐—ฎ๐˜€ ๐—ฎ ๐—ณ๐—ผ๐—ฟ๐—บ ๐—ผ๐—ณ ๐—ช๐—ถ๐—ธ๐—ถ๐—ฝ๐—ฒ๐—ฑ๐—ถ๐—ฎ, ๐—ฏ๐˜‚๐˜ ๐—ณ๐—ผ๐—ฟ ๐—ณ๐—ผ๐—ฟ ๐—”๐—œ ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€! 

https://aiagentsdirectory.com/landscape 

Source: Andreas Horn

AI agents are more than robots, software, or simple automation. They’re ๐—ฎ๐˜‚๐˜๐—ผ๐—ป๐—ผ๐—บ๐—ผ๐˜‚๐˜€ ๐—ฑ๐—ผ๐—ฒ๐—ฟ๐˜€ that can ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป, ๐—ฟ๐—ฒ๐—ฎ๐˜€๐—ผ๐—ป, ๐˜๐—ฎ๐—ธ๐—ฒ ๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป, ๐—ฎ๐—ป๐—ฑ ๐—บ๐—ฎ๐—ธ๐—ฒ ๐—ฑ๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป๐˜€. And currently everyone’s talking about them. Despite the growing buzz, real use cases are taking off already. Whether it is predictive maintenance in manufacturing, customer service, or AI agents disrupting software development, AI agents will be the autonomous specialists of the future.  

The field is very dynamic and there are lots of new approaches, frameworks, and use cases added every week in this field. To keep a good overview the website below is helping a lot. It categorizes most existing AI Agent projects (450+) in the market and breaks them down into the following categories:  

➤ ๐—•๐˜‚๐—ถ๐—น๐—ฑ๐—ฒ๐—ฟ๐˜€: 142 projects  

➤ ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜๐—ถ๐˜ƒ๐—ถ๐˜๐˜†: 56 projects  

➤ ๐—–๐—ผ๐—ฑ๐—ถ๐—ป๐—ด: 55 projects  

➤ ๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ ๐—ฆ๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฐ๐—ฒ: 42 projects  

➤ ๐—ฃ๐—ฒ๐—ฟ๐˜€๐—ผ๐—ป๐—ฎ๐—น ๐—”๐˜€๐˜€๐—ถ๐˜€๐˜๐—ฎ๐—ป๐˜/๐——๐—ถ๐—ด๐—ถ๐˜๐—ฎ๐—น ๐—ช๐—ผ๐—ฟ๐—ธ๐—ฒ๐—ฟ๐˜€: 58 projects  

➤ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€: 28 projects  

➤ ๐—ช๐—ผ๐—ฟ๐—ธ๐—ณ๐—น๐—ผ๐˜„: 20 projects  

➤ ๐—–๐—ผ๐—ป๐˜๐—ฒ๐—ป๐˜ ๐—–๐—ฟ๐—ฒ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: 19 projects  

➤ ๐—ฅ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต: 12 projects  

๐—ง๐—ต๐—ฒ ๐—ฏ๐—ฒ๐˜€๐˜ ๐—ฝ๐—ฎ๐—ฟ๐˜: ๐—ง๐—ต๐—ฒ ๐˜„๐—ฒ๐—ฏ๐˜€๐—ถ๐˜๐—ฒ ๐—ถ๐˜€ ๐˜‚๐—ฝ๐—ฑ๐—ฎ๐˜๐—ฒ๐—ฑ ๐˜„๐—ฒ๐—ฒ๐—ธ๐—น๐˜† ๐—ฎ๐—ป๐—ฑ ๐—ถ๐˜€ ๐—ฎ๐—น๐˜„๐—ฎ๐˜†๐˜€ ๐˜‚๐—ฝ-๐˜๐—ผ ๐—ฑ๐—ฎ๐˜๐—ฒ! ๐—œ ๐—ฏ๐—ฒ๐—น๐—ถ๐—ฒ๐˜ƒ๐—ฒ ๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐˜๐—ต๐—ฒ ๐—บ๐—ผ๐—ป๐˜๐—ต๐˜€ ๐—ฎ๐—ต๐—ฒ๐—ฎ๐—ฑ, ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐˜„๐—ผ๐—ฟ๐—ธ๐—ณ๐—น๐—ผ๐˜„๐˜€ ๐˜„๐—ถ๐—น๐—น ๐—น๐—ถ๐—ธ๐—ฒ๐—น๐˜† ๐—ฑ๐—ฟ๐—ถ๐˜ƒ๐—ฒ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ฝ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฒ๐˜€๐˜€ ๐˜๐—ต๐—ฎ๐—ป ๐—ฒ๐˜ƒ๐—ฒ๐—ป ๐˜๐—ต๐—ฒ ๐—ป๐—ฒ๐˜…๐˜-๐—ด๐—ฒ๐—ป ๐—ณ๐—ผ๐˜‚๐—ป๐—ฑ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€. 

๐—ง๐—ต๐—ถ๐˜€ ๐—บ๐—ถ๐—ด๐—ต๐˜ ๐—ฏ๐—ฒ ๐—ฎ ๐—ฟ๐—ฒ๐—ฎ๐—น๐—น๐˜† ๐˜‚๐˜€๐—ฒ๐—ณ๐˜‚๐—น ๐—ฟ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ ๐—ณ๐—ผ๐—ฟ ๐˜๐—ต๐—ผ๐˜€๐—ฒ ๐—ผ๐—ณ ๐˜†๐—ผ๐˜‚ ๐˜„๐—ต๐—ผ ๐˜„๐—ผ๐—ฟ๐—ธ ๐—ถ๐—ป ๐—”๐—œ ๐—ฎ๐—ป๐—ฑ ๐˜„๐—ถ๐˜๐—ต ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€.

Tuesday, October 29, 2024

Book Summary: Great Demo!: How to Create and Execute Stunning Software Demonstrations" by Peter Cohan

Demos and presentations are an integral part of every presales and sales professional’s life. Quite often, I have encountered situations where teams are required to deliver demos at short notice with minimal information. Whether it’s showcasing POC work or presenting a POV as part of an RFP evaluation, demos offer a valuable opportunity to highlight key capabilities to stakeholders in a short span of time. Solution demos play a crucial role in sales conversations, and making them impactful can often be challenging. However, if not executed well, they can have significant consequences.

A partner once recommended this book '"Great Demo!: How to Create and Execute Stunning Software Demonstrations" by Peter Cohan' to me, and I found it incredibly insightful. 

I highly recommend the book to my colleagues in Presales and Solution teams, especially those involved in product, solution, and POC demos. 

Gathering the necessary requirements from prospects is often tough, and with limited time, we must make the most of every opportunity. One of the common dilemmas we face is deciding what to showcase and what to leave out.

The book “Great Demo!" is about shifting the focus from a feature-heavy presentation to a problem-solving, customer-focused narrative. By keeping the customer’s needs at the center of the demo, the approach helps sales teams deliver more compelling presentations, shorten the sales cycle, and close deals more effectively.

This book provides a structured approach to software demos, focusing on demonstrating products in a way that captures customer interest, engagement, and buying intent. Below is a detailed summary of the core principles and strategies from the book to help guide effective and compelling software demonstrations.



Core Concepts:

1. The “Last Thing First” Principle

This principle emphasizes delivering the primary value or result the customer seeks right at the beginning. Instead of starting with extensive background information, jump straight to what the customer wants to see. This approach captures the audience's attention quickly and immediately establishes the product's relevance to their needs.

2. Critical Business Issue (CBI)

Peter Cohan stresses the importance of identifying the prospect's Critical Business Issue (CBI) before creating or delivering a demo. Understanding this core problem ensures that every feature or functionality shown in the demo directly addresses the customer’s most pressing needs.

3. Situation, Solution, and Value

A successful demo should clearly present:

  • Situation: The current challenge or status quo that the customer faces.
  • Solution: How the product directly addresses or improves upon this challenge.
  • Value: The tangible benefits or ROI the customer can achieve with the product.

4. The “Do the Last Thing First” Workflow

This structured workflow for software demos consists of four key steps:

  • Discovery: Conduct an in-depth discovery process to uncover the customer’s needs, pain points, and specific use cases.
  • Introduction: Introduce the product by immediately showing how it addresses the critical problem identified during discovery.
  • Demonstration: Dive into the software, keeping the focus on features that provide direct value to the customer.
  • Summary: Conclude by reinforcing the key points, emphasizing the benefits, and restating how the solution meets the customer’s problem.

Key Strategies:

1. Focus on Customer Benefits

An effective demo should not be a technical walkthrough but a focused presentation on how the product provides value to the customer. Rather than overwhelming them with features, concentrate on functionalities that directly solve their problem.

2. The “Inverted Pyramid” Structure

Cohan suggests using the inverted pyramid model, common in journalism, where the most important information is presented first, followed by supporting details. This keeps the audience engaged from the beginning and allows them to leave at any point without missing key takeaways.

3. Minimal Viable Demo (MVD)

Deliver a Minimal Viable Demo, showcasing only the essential parts of the product that directly address the customer’s issue. Avoid spending time on features that do not contribute to solving their critical business problem.

4. Vision Generation Demos

These demos are designed to help the customer envision success. By illustrating how your solution fits their specific needs, you enable the prospect to see the value it can bring to their organization, fostering early buy-in and commitment.

5. Interactive Demos

Encourage interaction by asking questions, seeking feedback, and allowing the prospect to use the software. This makes the demo feel like a collaborative exploration rather than a one-sided presentation, enhancing engagement.

6. Handling Questions and Objections

Cohan recommends addressing customer questions and objections openly during the demo. Rather than avoiding tough questions, tackle them head-on while maintaining control of the demo flow, linking responses back to the product’s key value proposition.


Techniques for Effective Delivery:

1. Storyboard the Demo

Just like a movie, a software demo needs a storyboard. Plan out what you will show, the sequence of steps, and how you will communicate each point. This ensures a smooth, logical flow that keeps the audience engaged.

2. Demo Flow

Keep the flow of the demo simple, avoiding unnecessary complexities. The demo should be easy for the audience to follow, focusing on how it solves their problem, not just how it functions.

3. Use Scenarios and Use Cases

Present the demo in the context of specific customer scenarios or use cases. By demonstrating how the software solves a real-world problem, the prospect will have a clearer understanding of the product’s value.

4. Repeat Key Points

Throughout the demo, emphasize and repeat the key benefits and outcomes the customer will gain. Reinforcement ensures that these points resonate with the audience and that they leave the demo with a clear understanding of how your solution helps them.

5. Summarize and Reiterate Value

At the end of the demo, summarize the main points and reiterate the value your product brings. Remind the prospect of the Critical Business Issue and how your solution resolves it.


Post-Demo Engagement:

1. Follow-Up

After the demo, follow up promptly with materials that reinforce the key takeaways. These could include:

  • A summary of what was demonstrated
  • Relevant case studies
  • Answers to questions raised during the demo

2. Tailored Proposals

Build on the demo by creating a tailored proposal that addresses the specific needs and goals identified during the demonstration. This ensures continuity in the sales process and maintains momentum.

Tuesday, April 30, 2024

LLMs: Understanding Tokens and Embeddings

I'm sure that since ChatGPT went mainstream, you've been hearing the term LLM quite frequently. The article below provides a clear and insightful explanation of Large Language Models (LLMs) and the concepts of tokens and embeddings.

The article explores how LLMs process text by converting it into numerical representations. It first explains why text must be transformed into numbers for machine learning systems, emphasizing that tokens—the fundamental units derived from text—are mapped to unique numeric identifiers.

While words might seem like natural token candidates, the article highlights that tokens can also be sub-word units, offering greater flexibility in text representation. This approach helps address challenges such as case sensitivity and the emergence of new words, which can complicate text processing. By breaking text into smaller components, like characters or sub-words, LLMs can handle linguistic variations and nuances more effectively.

The article also delves into embeddings, which are vector representations of tokens that capture their meanings and relationships in a continuous vector space. These embeddings allow LLMs to understand context and semantics, enhancing their ability to perform tasks like language generation and comprehension.

Overall, the piece underscores the crucial role of tokenization and embeddings in improving LLMs' capabilities in natural language processing (NLP).

https://msync.org/notes/llm-understanding-tokens-embeddings/

The Power of Graph Technology

While exploring Knowledge Graphs, I came across Tony Seale's insightful series on Embracing Complexity -  a fascinating read! "...T...