Stay Low - Provide good quality AI Advisory - Keep Collecting Unique Perspectives

 AI Advisory - High-speed learning, Applied past lessons, Lot of scars to build consistent and low latency and highly accurate solutions :)

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Transforming Setbacks into Strength: Lessons in AI Consulting and Trust

Introduction

I embarked on a journey to engage with my ex-colleague, who is currently a VP in a small industrial construction company, by providing AI advisory and learning sessions. Initially, it seemed like a promising exploration—teaching and guiding them through foundational concepts like LLMs, prompts, and RAG (Retrieval-Augmented Generation).

Early Teaching Phase

In the beginning, I had to explain the basics: what an LLM can do, what a prompt is, and how RAG techniques enhance information retrieval. After about a month, this ex-colleague returned, claiming there was negligible value and no tangible deliverables. This should have been a red flag, indicating that the cost and effort involved in teaching, training, and experimenting were not fully appreciated.

The Red Flags

In hindsight, I realize I should have caught the warning signs earlier. I kept insisting that experimentation was the key to understanding the capabilities and limitations of GenAI tools. Instead, this person seemed to push for more work in a shorter timeframe—a strategy to extract maximum value with minimal investment.

Shifting Roles and Promises

Later, I received an offer to join their team with a fixed pay and 5K shares, helping to architect solutions, pitch them to the market, and shape the product roadmap. The proposal seemed promising, aligning with my goal of taking on a more advisory and architectural role. Little did I know it was a tactic to consult, gain maximum value, and then part ways.

Building a Product and Architecture

As trust deepened—bolstered by a long-standing relationship spanning over a decade—we agreed on shares and informal terms. I invested significant effort: in training the team from scratch in LLM prompting, RAG, search customization, improving accuracy, data preprocessing, and system architecture. I demonstrated how to organize data effectively and leverage different approaches for better product outcomes. I also built a pitch deck, developed an API strategy, and created a technical feature roadmap.

The Unexpected Termination

Even as the product began to take shape, I was blindsided. Suddenly, he informed me they no longer required my services because they had found someone else to present the solution to the market. My requests for formal acknowledgments, like patents, were brushed aside. From the start, they had planned to offer low pay and shares, then terminate later. There was a clause stating that shares were invalid if I was no longer working for them—a clever strategy of betrayal. This was a person I had known for 14 years. It’s a stark reminder of what even people you know well can do.

Lessons Learned

This experience taught me that trust should be tempered with caution. Even long-standing relationships can falter when values, mindsets, and ethics come into play. Nonetheless, the knowledge I gained—developing product pitches, architectures, and end-to-end solutions—are useful for my current customers :), whether they need unstructured ETL solutions, industrial RAG systems, or tailored recommendation engines. Everything that broke you, builds you even stronger in the next epoch.

Always approach advisory roles with careful consideration and safeguards in place, no matter the length or depth of prior relationships. While losing out can hurt, the experience and skills you acquire will benefit you and your future clients.

My Advice

• → Don't be too open to "any opportunity."
• → Share your perspectives and answer questions with a clear, direct response.
• → Ask strategic, thoughtful questions to understand the big picture.
• → Show your value proposition and let your work speak for itself.

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Top 5 Practices to Master GenAI Product Development

• Focus on Solving the GenAI aspect - Prompts / Model Versions
• Focus on Scaling for multiple formats - Prompt Catalogs / Prompt Versions
• Focus on Low latency - Cache key data, Reuse data, RAG over docs, Graphs, Summarized data
• Focus on Accuracy across the board - Preprocess, Normalize, and Organize data effectvely based on use case, RAG over docs, Graphs, Summarized data
• Focus on Safe usage - Enforce Guardrails
• Entry of Agent - Once you have achieved it you can migrate to agentic approach but have more controls

If you need more AI Advisory, I am always available, You can learn from my course / schedule a call :)

GenAI and Cybersecurity – Frameworks and Best Practices 2024

Our course footprint :)

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Consistency, Latency, and Relevance in my AI Advisory Role :)

• Sometimes we need to move beyond the myth of waiting for #growth or #title to understand how well we can perform across roles, leveraging our strengths based on the situation.
• Sometimes you provide a tech overview, and that may translate into a PRD (Pseudo PM :).
• Sometimes you discuss latency again and again, slice and dice data, and there will be an “aha” moment (RAG specialist).
• Past experiments, current failures, and handling unknowns with a bit of intuition make you an optimistic solution architect.
• With GenAI, every role seems to blend multiple functions. Know the product, know the futuristic workflow, code, demo, and be hands-on whenever possible to make an impact.
• Be focused only on areas where you can scale. You cannot scale in every tech/role.
• GenAI in supply chain course preparation work made me revisit my Microsoft experience and reimagine the agentic supply chain.
• GenAI for the leadership project creation work helped me create usecases to evaluate balance time, money, and talent for 'C'-suite planning.
• Auditing the GenAI app made me realize that security and Ethical AI need more attention.
• Knowledge is collected through multiple highs, lows, failures, and moments in life. In the end, you can be a well-informed mentor who has tried technology to the best of your ability.

#HumanwrittenAIEdited #Perspectives #GenAI #Myworkperspectives

Automation, Assistance, Copilot - Metamate

 

Meta rolls out internal AI tool as it pushes into business market

• Social media group targets burgeoning artificial intelligence sector as it develops ‘Metamate’ workplace assistant
• This will also be used to build AI-based Marketing products

Automation, Assistance, Copilot = Metamate

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AIGovernance / AI Regulation for better Future

 

Geoffrey Hinton: the future with smarter AI is unpredictable

We're entering an era of uncertainty when we start dealing with things as intelligent or more intelligent than us.

Then, we have no idea what's going to happen. pic.twitter.com/a4rX8eZqdW

— Haider. (@slow_developer) December 14, 2024

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Responsible AI Adoption, Profits vs Purpose

 

Klarna CEO stopped hiring employees last year because “AI can do most jobs” and is down -22% headcount to 3500.

The private Swedish buy-now-pay-later company is worth $14.6B, up from $6.7B in 2022 but down from $45.6B in 2021 and is trying to go public next year. pic.twitter.com/P0eFADQqUS

— Deedy (@deedydas) December 15, 2024

Productivity Improvements vs Job Pressure vs Job Cuts

This is the reason we need Responsible AI Adoption!!! 

Agents = All Business Logic in AI Tier

Satya Nadela explains the AI Agentic Future.

The business logic is all going to these Agents.

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Video from Bg2 Pod Youtube Channel (link in comment) pic.twitter.com/CCzcvPvmZ5

— Rohan Paul (@rohanpaul_ai) December 14, 2024

• Business Logic in Agents
• All Logic in AI Tier
• More AI Native Business Apps
• Data Analyst = AI Native Excel Apps (Visualization, Analysis)

Keep Creating Agents!!!

From #Swartz to #Balaji: history shows the cost of inaction

From #Swartz to #Balaji: history shows the cost of inaction. AI needs #transparency & oversight now.  We need: - Mandatory AI #data disclosure - Fair creator compensation - Clear #copyright standards  #Policymakers #AIPolicy #TechEthics #AIEthics #ResponsibleAI

What happened to #suchir 👀‼️

"Suchir Balaji, former OpenAI researcher and whistleblower, tragically passed away on November 26, 2024, at the age of 26. Known for his role in highlighting legal and ethical concerns regarding AI's data use, Balaji’s passing has left the tech… pic.twitter.com/gCb9cdnaLQ

— @SakashiNakamoto (@SakashiNakamoto) December 14, 2024

I recently participated in a NYT story about fair use and generative AI, and why I'm skeptical "fair use" would be a plausible defense for a lot of generative AI products. I also wrote a blog post (https://t.co/xhiVyCk2Vk) about the nitty-gritty details of fair use and why I…

— Suchir Balaji (@suchirbalaji) October 23, 2024

Some Things to Deep Dive / This should not have happened

• Truth only becomes dangerous when someone realizes it's worth silencing
• If his accusations against OpenAI held weight, it underscores a systemic failure where whistleblowers are silenced instead of being protected. 
• Corporate greed and systemic apathy cannot continue unchecked
• Depression is sadly a major side-effect of whistleblowing

Need more Guardrails in Responsible, Transparen,t and Ethical Adoption

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Future Robotic Farmer - Tesla Optimus

 

Optimus can now walk on highly variable ground using neural nets to control its electric limbs.

Join @Tesla if you want to work on interesting real-world AI systems. https://t.co/C8J90Age5Y

— Elon Musk (@elonmusk) December 9, 2024

Keep Exploring!!!