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AI Agents and Digital Transformation

Inventing the Future of Agents

“The best way to predict the future is to invent it.” – Alan Kay, Computer Science PioneerOr, to channel Buzz Lightyear: “To infinity and beyond.” Inventing the Future of Agents The history of computing has always advanced in fits and starts, a pattern biologists call punctuated equilibrium. Revolutionary technologies emerge slowly—nurtured in research labs, garages, and the minds of visionaries—until the moment comes when a breakthrough shifts the axis of possibility. From there, a new paradigm takes shape, unleashing waves of innovation. Think of the Apple Macintosh, the iPhone, and Salesforce’s own Platform, which pioneered enterprise software-as-a-service (SaaS) and sparked an entirely new industry. Each of these milestones reshaped the way we live and work, setting the stage for even greater advances to come. Alan Kay: A Visionary for Computing’s Future One such paradigm-shifter was Alan Kay. In 1971, while working at Xerox PARC, Kay was immersed in an era when computers were room-sized behemoths. At the time, only four of these machines were connected to the fledgling ARPAnet, a precursor to today’s internet. Kay, a skilled musician with a deep appreciation for human-centered design, brought an empathetic and humanistic approach to innovation. In 1972, he introduced the Dynabook—a radical vision for personal computing that was decades ahead of its time. The Dynabook concept featured a battery-powered laptop with a touchscreen, wireless access to global information, and an interface so simple even children could use it. Kay and his team at PARC went on to develop many of the foundational elements of modern personal computing: overlapping windows, graphical user interfaces, and object-oriented programming. Later, while at Apple, Kay helped shape the vision for the groundbreaking 1987 Apple Knowledge Navigator video, which anticipated today’s iPad and iPhone. Agents and Humans: Driving Success Together Fast-forward to today, and we are on the cusp of another technological leap forward: AI agents. Much like Kay’s vision of personal computing, the emergence of intelligent, autonomous agents signals a new chapter in how humans and technology work together. Agentforce: Bringing the Future to the Present This interplay between visionary ideas and emerging technologies was on full display with the launch of Agentforce at Dreamforce 2024. A year earlier, at Dreamforce 2023, Salesforce Futures debuted its Salesforce 2030 film, drawing inspiration from Apple’s Knowledge Navigator. The film offered a glimpse into a world where humans collaborate seamlessly with autonomous AI agents—an aspirational vision of business transformed. Since then, the imagination gap between fiction and reality has narrowed. Salesforce’s work in Agentforce and publications like Personal AI Agents and Agents at Work have explored how agents are already changing business as we know it. These tools are bringing science fiction to life, enabling businesses to achieve unprecedented levels of efficiency, creativity, and success. A New Paradigm in Progress Like the Macintosh, the iPhone, or the Salesforce Platform, the rise of AI agents represents another transformative moment in computing history. By combining vision with technological breakthroughs, we are witnessing the dawn of a new era—one where humans and AI agents work together to push the boundaries of what’s possible. Alan Kay’s timeless wisdom rings true: the future isn’t something we wait for—it’s something we invent. With Agentforce, that future is already here. Inventing the Future of Agents. Are you ready to start Inventing the Future of Agents? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Agents and Digital Transformation

Ready for AI Agents

Brands that can effectively integrate agentic AI into their operations stand to gain a significant competitive edge. But as with any innovation, success will depend on balancing the promise of automation with the complexities of trust, privacy, and user experience.

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AI in Programming

AI in Programming

Since the launch of ChatGPT in 2022, developers have been split into two camps: those who ban AI in coding and those who embrace it. Many seasoned programmers not only avoid AI-generated code but also prohibit their teams from using it. Their reasoning is simple: “AI-generated code is unreliable.” Even if one doesn’t agree with this anti-AI stance, they’ve likely faced challenges, hurdles, or frustrations when using AI for programming. The key is finding the right strategies to use AI to your advantage. Many are still using outdated AI strategies from two years ago, likened to cutting down a tree with kitchen knives. Two Major Issues with AI for Developers The Wrong Way to Use AI… …can be broken down into two parts: When ChatGPT first launched, the typical way to work with AI was to visit the website and chat with GPT-3.5 in a browser. The process was straightforward: copy code from the IDE, paste it into ChatGPT with a basic prompt like “add comments,” get the revised code, check for errors, and paste it back into the IDE. Many developers, especially beginners and students, are still using this same method. However, the AI landscape has changed significantly over the last two years, and many have not adjusted their approach to fully leverage AI’s potential. Another common pitfall is how developers use AI. They ask the LLM to generate code, test it, and go back and forth to fix any issues. Often, they fall into an endless loop of AI hallucinations when trying to get the LLM to understand what’s wrong. This can be frustrating and unproductive. Four Tools to Boost Programming Productivity with AI 1. Cursor: AI-First IDE Cursor is an AI-first IDE built on VScode but enhanced with AI features. It allows developers to integrate a chatbot API and use AI as an assistant. Some of Cursor’s standout features include: Cursor integrates seamlessly with VScode, making it easy for existing users to transition. It supports various models, including GPT-4, Claude 3.5 Sonnet, and its built-in free cursor-small model. The combination of Cursor and Sonnet 3.5 has been particularly praised for producing reliable coding results. This tool is a significant improvement over copy-pasting code between ChatGPT and an IDE. 2. Micro Agent: Code + Test Case Micro Agent takes a different approach to AI-generated code by focusing on test cases. Instead of generating large chunks of code, it begins by creating test cases based on the prompt, then writes code that passes those tests. This method results in more grounded and reliable output, especially for functions that are tricky but not overly complex. 3. SWE-agent: AI for GitHub Issues Developed by Princeton Language and Intelligence, SWE-agent specializes in resolving real-world GitHub repository issues and submitting pull requests. It’s a powerful tool for managing large repositories, as it reviews codebases, identifies issues, and makes necessary changes. SWE-agent is open-source and has gained considerable popularity on GitHub. 4. AI Commits: git commit -m AI Commits generates meaningful commit messages based on your git diff. This simple tool eliminates the need for vague or repetitive commit messages like “minor changes.” It’s easy to install and uses GPT-3.5 for efficient, AI-generated commit messages. The Path Forward To stay productive and achieve goals in the rapidly evolving AI landscape, developers need the right tools. The limitations of AI, such as hallucinations, can’t be eliminated, but using the appropriate tools can help mitigate them. Simple, manual interactions like generating code or comments through ChatGPT can be frustrating. By adopting the right strategies and tools, developers can avoid these pitfalls and confidently enhance their coding practices. AI is evolving fast, and keeping up with its changes is crucial. The right tools can make all the difference in your programming workflow. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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