Talsco Weekly: IBM foresees AI agent revolution in enterprise IT

Welcome to another edition of Talsco Weekly

IBM i Brief: 📈 IBM stock rises on dividend announcement. IBM Granite 3.0 revolutionizes AI for businesses 🎥.
AI: 🦾IBM foresees AI agent revolution in enterprise IT. 🧹 Data quality is crucial for AI success. 🔑 Small language models boost enterprise AI adoption.
Development: 🎥 PHP evolves with exciting new features. 🔍 Special Authority Data Mart: Enhancing User Profile Management.
Modernization: 🔄 7 signs it’s time to modernize IT systems. 📈Modernization: The IBM i and Gall’s Law.
Security: ⚠️ AI hallucinations pose cybersecurity risks.

IBM i Brief

📈 IBM stock rises on dividend announcement IBM saw a 0.4% increase in stock price following a dividend declaration. The company will pay $1.67 per share on December 10th to shareholders of record as of November 12th. This represents a 3.23% yield and a 75.65% payout ratio. IBM’s stock reached $206.22 during trading, with reduced volume compared to average. IBM Granite 3.0 revolutionizes AI for businesses 🎥

If you are curious about IBMs strategy for AI, here is an informative interview with the VP of Research for AI, Sriram Raghavan.

IBM’s new Granite 3.0 models aim to boost ROI for AI adoption by enhancing efficiency and safety. These purpose-built models excel in tasks like retrieval-augmented generation and summarization, streamlining AI use cases.

With reduced computation costs and built-in guardrails, Granite 3.0 offers optimized performance for various enterprise applications, from customer care to consulting.

Note: IBM i Code Assist us using Granite.

AI

🦾IBM foresees AI agent revolution in enterprise IT

IBM’s VP of product management predicts AI agents will soon automate complex tasks in enterprises. These agents, with capabilities like planning, memory, tool use, and autonomous action, will work alongside humans. IBM expects “millions of AI agents” in enterprises, coordinated by “Super AIs”.

AI technologies have evolved from predictive models in traditional machine learning to the widespread use of chatbots. He predicted that the next leap will usher in an “agentic era,” where specialised AI agents collaborate with humans to drive organisational efficiencies.

This shift could transform work across various sectors, allowing employees to focus on more strategic tasks.

The linked article above goes into depth on what AI agents are and how they will impact the enterprise going forward.

What does this mean for the IBM i ecosystem?

I certainly don’t have a crystal ball, but there is no question that AI is starting to make it’s way into the IBM i shops.

Software vendors in the IBM i space that I speak with are starting to use it internally to help them develop their own software. While others are taking it a step further and starting to integrate it into their product offering for their customers.

As for IBM i shops, the interest in AI is coming from a number of different angles. The vendor side, that is AI embedded into the software they use, and then internally to how it can help their own development efforts.

Helping RPG developers with AI

One use case is how they can help their RPG developers become more efficient.

As we have covered in recent issues, IBM is looking to build the Watson Code Assist tool for the IBM i.

This Coding Assistant will:

Help younger developers that are unfamiliar with RPG
Help seasoned developers that are unfamiliar with modern RPG
Help business executive’s that are responsible for IT budgets understand why modernizing the code base is important.

🧹 Data quality is crucial for AI success As companies rush to integrate AI, many overlook data quality, risking falling behind competitors. Prioritizing data management is essential for unlocking AI’s full potential and driving innovation. Organizations must assess their AI readiness and develop robust data governance strategies to ensure successful AI adoption and maintain business momentum. Read the full article. 🔑 Small language models boost enterprise AI adoption

SLMs are gaining traction as cost-effective, secure alternatives to large language models for businesses. These specialized models offer faster processing, local deployment, and enhanced privacy, making them attractive for enterprise use.

Small language models (SLMs)—pared-down versions of the large language models that underpin generative AI technology

By focusing on specific tasks and running on-device, SLMs address key concerns like data security and speed, potentially accelerating AI integration in various industries.

Development

🎥 PHP evolves with exciting new features

While Node.js and Python offer unique characteristics running on the IBM i, and are very valuable, PHP has proven to be an incredibly reliable choice for web and API development.

PHP has been around a long time on the IBM i server, but if you haven’t looked at PHP lately, you might be surprised at what’s going on with the newer releases.

Alan Seiden’s webinar highlights PHP’s ongoing development for IBM i.

Recent versions bring performance boosts, stricter coding practices, and enhanced security. Key updates include extended support periods, easier installation via Yum and RPM, and new functions like JSON validation.

The Seiden Group specializes in PHP, Python, Node & RPG on IBM i.

🔍 Special Authority Data Mart: Enhancing User Profile Management

IBM i’s latest Technology Refresh introduces the Special Authority Data Mart, a new tool for tracking user profile special authorities.

The Special Authority Data Mart is held in the table SPECIAL_AUTHORITY_DATA_MART, which resides in the SYSTOOLS. Here is an example of how it can be used.

Modernization

🔄 7 signs it’s time to modernize IT systems

While this article is not written specifically for the IBM i community, IT Leaders across all technical stacks should watch for the following 7 signals that it might be time to modernize.

Technical debt
Business growth
Security weaknesses
Reduced agility
Outdated systems
Internal complaints
Service disruptions

To address this, leaders should assess current tools, build a business case, prioritize areas for improvement, and collaborate across stakeholders to align technology with long-term business objectives.

📈Modernization: The IBM i and Gall’s Law

Gall’s Law is a software development principle that states:

“A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working, simple system.”

The AS/400 was designed to be reliable, secure, and easy to manage. Its simplicity comes from its integrated hardware and software architecture.

Applying Gall’s Law to the IBM i platform

Gall’s Law aligns with the evolutionary approach to IBM i system development. Read the full article here.

Security

⚠️ AI hallucinations pose cybersecurity risks

AI hallucination is when a large language model (LLM), such as a generative AI tool, provides an answer that is incorrect.

AI hallucinations and incorrect outputs from language models can compromise cybersecurity efforts. Organizations increasingly use generative AI for threat hunting and training, but errors can lead to overlooked threats or false alarms.

To mitigate risks, companies should train employees on prompt engineering, focus on data quality, and implement fact-checking processes. By addressing AI hallucinations, businesses can better leverage AI for cybersecurity while staying vigilant against potential inaccuracies.

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