Do Not Underestimate the Productivity Impact of AI

We are living in a time of unbelievable productivity.

Sitting on a flight home from London the other day, I was able to enhance two apps materially, incorporating design partner feedback from the week, and in addition, create two comprehensive prototypes from scratch ... all that, eat lunch and have a much-needed nap 😀

From research to ideation to prototyping to shipping production code, AI has become a powerful amplifier. I'm accomplishing things that were simply not possible six months ago.

We are living in wild times, and it's incumbent on all of us to understand these implications as we re-engineer our business processes, re-imagine personal productivity, and re-think how we build software companies in the future.

Carpe Diem

Build vs Buy ROI just got more complicated

It's 2025, and the "build vs buy" question has never been more nuanced.

Last week, we encountered one of these questions.

We wanted to implement a bug reporting and feature tracking system that we could seamlessly integrate into our apps. This capability would allow our design partners to submit issues and ideas effortlessly and permit us to gather all of this intelligence in real time.

We explored the many bug/feature reporting solutions on the market, but as we explored doing it ourselves, we realized we could deliver something far more compelling. In about four hours, we had implemented something that would become the gift that kept on giving.

Going far beyond traditional bug tracking tools, our AI-powered solution analyzed the appropriate GitHub repo as issues came in, diagnosed the reported issue and suggested solutions or workarounds. It also built detailed prompts to allow our coding agents to fix the bugs or create new features as appropriate.

Next steps? Having the agents automatically create a Git branch, make the changes and then request a code review/merge.

Agentic AI has upended traditional ROI calculations. Today, what you can accomplish is limited only by your imagination.

Keeping Up With The Agents

Some of you have been pestering me for more Breakfast with AI updates ...

Unfortunately, the productivity increase I have seen from leveraging the new persona-driven, semi-automated Agentic flow has increased the build velocity so much that it's been impossible to keep up trying to tell the stories. 🤦

So what's a Chief Agentic Officer to do? Well, of course, have the AIs tell their own story. So that's what I did, and it turns out they're just a little bit proud of the work that they did.

That, and an update on the $5.3MM of software created by the agents since October on this morning's quick 2-minute Breakfast with AI.

Enjoy ...

A Little Python Humour

Sitting here working on another Breakfast with AI session, watching the agents install several python libraries and wondering who comes up with these names?

And had they ever considered having them star in a kids book? 😊 So I asked ... and the agents themselves had some thoughts:

  • Numpy Panda: A delightfully dorky panda obsessed with arrays, matrices, and perfectly symmetrical bamboo sticks. He wears oversized glasses that always slide down his nose and carries a graph paper notebook that somehow always runs out of space exactly when he needs it.

  • Sniffio: A tiny, overly enthusiastic fox with a nose that’s so sensitive it detects context shifts—like sniffing out synchronous cupcakes versus asynchronous cookies. Known to randomly shout, “I smell concurrency issues!”

  • Matplot Sloth: An artistic sloth who takes forever to draw intricate, stunningly detailed maps. Infamous for taking naps mid-line drawing, often leaving maps half-finished and hilariously misinterpreted.

Yeh ... well ... not their best work ... but the visual was nice ...

From Frustration to Joy - What a difference point seven makes

I posted yesterday about my initial impressions of Claude 3.7 ... well it didn't disappoint today.

After going round and round in circles for a few days, trying to get Claude 3.5 to implement a dynamic controller for my synthetic data app, in less than 5 minutes, Claude 3.7 built something truly stunning today. In many ways, it was more than what I asked for.

Claude 3.7 just upped the coding game.

Claude 3.7 Just Upped the Coding Game

I spent almost 12 hours yesterday exploring the product management, UX design, system architecture, coding and testing prowess of Claude 3.7, and I was stunned. The projects I am working on took a huge leap forward. Issues that had been plaguing me for days were suddenly solved.

And Claude 3.7 is just the start ...

Each day I work with this technology, the more ambitious my coding projects become, and each day I explore what's possible, the more confident I am that Gen AI has fundamentally changed how we will build software companies in the future.

My product agents now conduct market research, conceive the products, design the UX, frame the architecture, review security implications, lay out an implementation plan, follow that plan to write code, build and execute the unit tests, debug the issues, battle-harden the code, and even create the landing pages to provide a sneak preview of the upcoming app.

It got a bit weird, though ...

Yesterday, one of the agents suggested they hold a kickoff meeting and even created an agenda for it. I had to politely ask them if they were going to meet with each other, perhaps in their own language, because they were the only members of the team other than me. I suggested that humans were moving away from incessant meetings, so perhaps they might consider not picking up on our bad habits.

So much to share in the coming days.

Creating Synthetic Data

One of the things that LLMs are very good at is creating synthetic data. And Synthetic data is so important in the software business, be it for testing your app, or demonstrating it in a credible manner.

I recently created a fun LLM log generator that allows us to create fictitious LLM logs for Law, Financial Services or Insurance industry use cases. The data reflects a selected distribution of query types, and contains examples of both safe and unsafe queries.

Enjoy!

#SyntheticData #AI

Agents and Compliance ... BFFs forever

Welcome back to another season of Breakfast with AI.

For this project, we unleashed an army of agents on the challenge of regulatory compliance. It was surprisingly fun and insightful, though I wonder if FUN and COMPLIANCE should ever be uttered in the same sentence.

Please have a look and let me know what you think! If you want to see more of these explorations (from the CEO, who hasn't coded in 25 years), let me know by giving it a like or adding a comment!

Lots more Breakfast with AI sessions are coming ... it was a productive holiday season :-)

Note: Please let me know if you want the wacky coding agents at AFINEA Labs to build anything fun. They rolled their little digital eyes when I suggested they work on a compliance project.

#agentic #ai #compliance #coding

Building an App over Breakfast to Visualize 15 Years of Travel

Breakfast with AI met Breakfast with BI this weekend, and a travel app was born.

After a conversation with Claude, 15 years of travel information were crunched into a dashboard that provided fascinating and silly insights into the madness of my international travel over the last few years.

Along the way, I learned some things that continue to shape how I work with AI ...

Enjoy!

#AI #CEOsWhoCode #OldDogNewTricks #Analytics

Microsoft is All In on AI

At Microsoft Ignite 2024, held on November 19, the company made significant announcements focused on its AI strategy, showcasing how AI will continue transforming workplace productivity, cloud infrastructure, and security. Here are the key highlights:

AI Agents and Copilot Enhancements

  • Copilot Actions: Microsoft introduced Copilot Actions, a new feature for Microsoft 365 Copilot that automates repetitive tasks such as summarizing meeting actions, preparing reports, and managing schedules. These AI agents can operate autonomously once set up, running tasks without constant prompts.

  • Autonomous AI Agents: Microsoft revealed autonomous agents that can act on users' behalf in the background. These agents plan, learn from processes, adapt to new conditions, and make decisions independently. They are designed to streamline workflows across platforms like SharePoint and Teams.

  • Agent SDK: Developers can now use the Agent SDK to build custom AI agents that integrate with Azure AI and Microsoft’s Copilot services. This SDK allows for deploying multi-channel agents across platforms like Teams and third-party messaging apps.

Azure AI Foundry

  • Azure AI Foundry: Microsoft introduced Azure AI Foundry, a platform for designing, managing, and deploying AI applications. The Foundry includes a portal for managing models and an SDK for integrating AI into business applications. It also offers tools for scaling AI agents and ensuring compliance with data privacy regulations.

  • AI Agent Service: The Azure AI Agent Service will allow developers to orchestrate and scale AI agents to automate business processes.

Multimodal Capabilities

  • Multimodal Agent Integration: Microsoft is enhancing Copilot Studio with multimodal capabilities. Agents will soon be able to analyze images and voice content in addition to text, allowing richer interaction across different media types.

AI-Powered Productivity Tools

  • Teams Enhancements: New features in Teams include an Interpreter Agent that can replicate a user’s voice in up to nine languages for real-time translation during meetings. This feature will roll out in early 2025.

  • PowerPoint Translation: PowerPoint users can use AI to translate entire presentations into other languages, further expanding the capabilities of Microsoft’s productivity suite.

Custom AI Chips

  • Custom Silicon Chips: Microsoft announced two custom-made AI chips designed to enhance the performance of its data centers and reduce reliance on external suppliers like Nvidia. These chips will improve the speed of AI applications while bolstering security.

AI Security Initiatives

  • Windows Security Overhaul: As part of its security push, Microsoft introduced new security measures for Windows systems to prevent incidents like the CrowdStrike breach. The updates include more robust controls over applications and drivers alongside antivirus processing.

Overall, Microsoft’s announcements at Ignite 2024 highlight its commitment to embedding AI deeper into enterprise workflows through autonomous agents, enhanced productivity tools, and custom infrastructure designed to scale AI securely.

AI helped me code a fully functional iOS app with no experience.

Today's 𝗕𝗿𝗲𝗮𝗸𝗳𝗮𝘀𝘁 𝘄𝗶𝘁𝗵 𝗔𝗜 mission was to code a native iOS app from scratch.

The app SafetyElephant provides real-time data on fires, earthquakes, and weather alerts near you or any region you plan to visit —all mapped, with details visible on demand.

The context:

(1) I have never built a Mobile App
(2) I have never used Xcode
(3) I have never used Swift

It sounds like a tall order ...

Well, I managed to build it. Check out how it all came together using Cursor AI and Xcode.

It was also a surprising amount of fun.

#AI #CEOsWhoCode #OldDogNewTricks

Understanding AI Security Risks: A Critical Imperative for Enterprises

As I have been exploring the accelerative power of AI in various forms over the past few months, I have been arriving at the conclusion that this is a form of grand sorcery. I jest … sort of … but in some respects I think this is an apt analogy.

Like all grand sorcery, AI is powerful stuff. But also, like all grand sorcery, we don't understand it well. It is becoming pretty clear that, in many respects, at this stage, we don't know what we don't know.

This applies, in particular, to securing AI in our enterprises.

There is a growing tension between our desire to use this powerful technology and the need to do so with the appropriate guard rails. To complicate things, emerging regulatory frameworks (the EU AI Act, for example) now have to be adhered to. The challenge for many enterprises in securing their companies and adhering to these frameworks is whether they have the technologies in place to help them meet these obligations.

The rise of Generative AI (GenAI) introduces a range of new vulnerabilities that malicious actors can exploit. As we integrate AI more deeply into our business operations, monitoring our use of AI, and understanding the security risks accompanying this powerful technology is crucial.

Let me give you some examples.

The Invisible Threat: Unicode Exploitation

A fascinating yet concerning aspect of AI security involves the exploitation of invisible text through quirks in the Unicode standard. AI models can recognize these invisible characters but remain unseen by human users, creating a covert channel for attackers to conceal and exfiltrate sensitive data. This vulnerability opens the door to prompt injection attacks, where hidden commands can be injected into AI prompts, potentially compromising confidential information.

The GenAI Attack Chain

To better understand how these vulnerabilities manifest, it’s essential to explore the GenAI attack chain, which outlines the steps attackers may take to exploit AI systems:

  1. Bypassing Guardrails: Attackers often begin by circumventing the model’s built-in safeguards. Techniques such as encoding and token manipulation allow them to mask malicious inputs, making it easier to exploit system vulnerabilities.

  2. Privilege Escalation: Once attackers bypass these defences, they can escalate their privileges through direct and indirect prompt injections. This enables unauthorized control over the model, leading to potential security compromises.

  3. Security Compromise: The culmination of these actions can result in severe consequences, including sensitive data leakage, phishing attacks, and operational disruptions. Attackers can access critical systems, spread malicious code, and disrupt business operations.

Real-World Implications

Proof-of-concept attacks have demonstrated how invisible text can extract sensitive data from AI tools, such as Microsoft 365 Copilot. These incidents highlight the urgent need for organizations to prioritize understanding these security challenges. It's also becoming clear that sensitive data, including personally identifiable information (PII) and corporate secrets, can be exploited for identity theft or corporate espionage, leading to significant financial and reputational damage.

Addressing the Risks

As leaders, we must strike the right balance here. Find ways to embrace and leverage this technology while ensuring robust security measures and keeping people informed and well-educated about potential vulnerabilities. Understanding the GenAI attack chain and the risks associated with invisible text exploitation is critical for safeguarding sensitive information.

Conclusion

I'm pretty excited by AI's transformative capability. However, as we start to harness its potential, it’s imperative that we collectively understand and address the risks inherent in this new form of sorcery.

#AISecurity #EnterpriseAI #Cybersecurity #Innovation #Leadership

Leaning into Agentic AI

As I promised you last time, I would spend some time exploring Agentic AI. Sorry it has taken a few weeks, but it's been a bit hectic.

At any rate, I finished my first "Agentic" project on the flight home from London last night.

It's an app that allows you to enter any topic and have it debated (pro and con) by multiple AIs. Two AIs (Claude and OpenAI) debate each other, and a third (Perplexity running LLAMA) summarizes the debate (both points of contention and common ground) and comes up with a "winner."

In fairness, not all of this code was built on the flight, as I could leverage several components I had already assembled. However, the first cut of this app was ready in about five hours (or less than the flight time from London to Toronto).

Each time I experiment with AI, I get new ideas ... so ... wait until you see what I intend to build next. It's called Board Bot ... and it's coming soon to a board meeting near you 🙂

Enjoy!

#AgenticAI #CEOsWhoCode #ExploringAi

It's worth getting to know Daniel Miessler

Daniel Miessler's projects are interconnected efforts to address significant societal challenges through AI and open-source frameworks.

Miessler is concerned about three main issues:

  • Lack of Purpose: Many people struggle with finding meaning in life, leading to mental health and societal issues.

  • AI Disruption: Rapid AI advancements are causing work disruptions, potentially exacerbating this lack of purpose.

  • Limited Human Development: People are trained to be economically useful rather than becoming well-rounded individuals.

His five significant projects aim to help people articulate their identities, improve themselves, and engage meaningfully with others. They emphasize clarity, transparency, continuous optimization, and purpose. AI is a central component due to its ability to identify patterns and provide insights across different contexts.

It’s worth reading this article, where he explains everything. If you wish, you can watch his summary of this work in the video below.

Substrate

  • Purpose: An open-source framework to enhance understanding and problem-solving by making important issues transparent and discussable.

  • Application: Provides a structure for shared understanding, allowing AI to analyze and generate insights on various human concerns.

Fabric

  • Purpose: Simplifies the use of AI to solve everyday problems by providing a library of problem-solving use cases.

  • Application: Helps with tasks like learning, decision-making, and optimizing daily life by reducing friction in AI tool usage.

Telos

  • Purpose: Captures deep context about entities (individuals, teams, organizations) to improve understanding and management.

  • Application: Allows AI to analyze an entity's goals and challenges, providing actionable insights and recommendations.

Daemon

  • Purpose: An open-source framework for creating personal APIs.

  • Application: Enables individuals to present their identity and capabilities as an API, enhancing personal branding and interaction.

Human 3.0

  • Purpose: A framework for transitioning humans from traditional corporate roles to self-actualized individuals offering unique value.

  • Components: This program includes video courses, assessments, and a maturity model to guide personal development toward becoming full-spectrum humans.

Beyond the interesting philosophical and societal challenges he touches on, his technology provides fascinating insights into AI's possibilities.

Notebook LM Magically Generates An AI Powered Podcast From 3 Documents

As some of you know, over the past couple of weeks, I have been running some AI-powered experiments:

If you are interested, you can read about them below:

Why am I doing this?

Well, (a) it is essential to get your hands on AI to understand its potential, (b) CEOs need to eat their own dog food if they are going to lead in this increasingly AI-accelerated world, and (c) it's my way of trying to understand the impact of AI across a software company's value chain.

What could a 𝘁𝗲𝗮𝗺 powered by AI do if I could do these things independently?

Last night, I tried something different.

Building on the INEA relaunch exercise over the weekend, I wanted to see if AI could help me create compelling content marketing—not in the form of dry, static documents but a dynamic AI-generated podcast.

The results were interesting ...

AI is transforming interactions between clients and creatives

My wife and I re-designed and rebuilt our downtown Toronto garden not too long ago.

Because we had a pretty clear sense of what we wanted, we assembled a Pinterest board of ideas, and I drew a rough proposed layout in PowerPoint (don’t judge me; I’m a CEO, and I do everything in PowerPoint).

The team we worked with was superb. They took our clear wishes to heart (good-naturedly), and we were thrilled with the results.

I couldn’t help but feel that this process would have been even more straightforward with AI tools like Midjourney.

As an experiment, I embarked on another thought experiment to design a bright, modern and airy garden in a challenging urban space, surrounded on two sides by high walls (such as you might find in a city like London, England). The results after less than 5 minutes of effort are reflected in the image above.

AI democratizes creativity. It allows us to unlock our creativity without having to be craftsmen. It enables us to render a pretty close facsimile of what is in our heads, even if we cannot draw or paint. It can then allow us to validate whether specific components (plants, etc.) would work given location constraints, sun exposure, etc., without being horticultural experts. It can even write a project brief in a form familiar to the design/build team.

Fundamentally, AI can transform how clients and creatives interact throughout a project's lifecycle. Through real-time (interactive) visualization, collaboration can be streamlined from ideation to final execution. This can potentially drive radical improvements in the speed of iteration and (potentially) a reduction in design costs.

The trend of customers arriving with more fully developed concepts isn’t just restricted to the creative realm. One senior lawyer told me recently that clients are showing up with surprisingly good first drafts of contracts and requesting that those be vetted. That differs from yesterday's legal value chain, where law firms charged clients for creating those drafts and then for the refinement process.

As leaders, we must consider AI's growing impact on our companies. Will it be a force multiplier, competitive advantage, or existential threat? That’s really up to us.

Can AI reimagine the launch of a 25 year old company?

As many of you will know, I recently published a few reflections on how AI has helped me code, prototype apps, and more in record time as a CEO who hasn't coded for 25 years.

I tried something very different this weekend. I went back to company and business plan creation ...

I asked AI to imagine the relaunch of INEA, a company I co-founded about 26 years ago, and to write a white paper covering what INEA might look like if it launched in 2025 as transformational performance management software for the financial services industry.

Could it be compelling and differentiated? If so, why? What would the product offering look like? What new technologies might it leverage? What would the TAM be? What would the competitive landscape be? What would the go-to-market strategy be?  What might the financial projections be? etc.

I gave it the only two legacy documents I could find, a brochure and an old copy of a business plan, and let it get to work. I even played the results of one AI off against another to refine the output.

The results astounded me. I achieved what would have taken us days or weeks before in a couple of hours.

AI is here ... and it is (already) changing everything ...