Welcome to another edition of Talsco Weekly

IBM i Brief: 💰 IBM announces global Power Systems price hikes. 📊 IBM i PTF Guide updates available for 7.3, 7.4, and 7.5.
AI: 🤖 IBM i welcomes Python-powered machine learning. 🤖 LLMs vs SLMs: Understanding the Language Model Landscape.
Career: 🚀 AI Skills Now Essential for IBM i Developer Career Growth.
Development: 💻 JavaScript opens new doors for IBM i developers. 🔍 New Audit Data Mart filter parameter enhances journal data selection capabilities. 🚀 SQL Views vs. Logical Files: Unpacking the Modernization Magic.
Data: 🚀 Rocket Software launches CDC tool for IBM i.

IBM i Brief

💰 IBM announces global Power Systems price hikes

Big Blue is implementing price increases across Power Systems and storage products effective April 1, 2025. The changes include foreign exchange adjustments affecting 18 currencies in Asia/Pacific and EMEA regions, with increases ranging from 0.7% to 4%. Notable impacts include a 13% rise in Power Systems shipping costs and significant storage-related price hikes, with some handling charges jumping up to 232%. Learn more about it here.

📊 IBM i PTF Guide updates available for 7.3, 7.4, and 7.5

New PTF group updates have been released for IBM i versions 7.3, 7.4, and 7.5, with minimal software stack issues or security vulnerabilities reported.

AI

🤖 IBM i welcomes Python-powered machine learning

While this article was published a couple years ago, it is still very much relevant today.

Here is a quick demo on how Python machine learning models can analyze and predict data directly on IBM i systems. Using libraries like NumPy, Pandas, and Scikit-learn, developers can build predictive models that leverage existing business data. The implementation shows practical applications from forecasting raw material needs to analyzing quality control images.

🤖 LLMs vs SLMs: Understanding the Language Model Landscape

LLMs (Large Language Models) are massive AI systems with billions of parameters, excelling at complex tasks like essay writing or code generation. They require significant computing power.

SLMs (Small Language Models) are smaller with fewer parameters, making them faster and less resource-intensive. They suit simpler tasks like basic Q&A and can run on devices like phones. In short, LLMs offer greater capability but demand more resources, while SLMs prioritize efficiency over depth.

🔄 SLMs find sweet spot for developers. Small Language Models offer developers an efficient middle ground between capability and resource use. These lightweight AI models run on standard hardware, enable offline functionality, and speed up development with faster training and debugging cycles. While they may not match LLMs in complexity, their practicality and cost-effectiveness make them increasingly attractive for everyday development tasks.

Career

🚀 AI Skills Now Essential for IBM i Developer Career Growth

After spending the last three days at the WMCPA Spring Technical Conference, it’s clear that AI dominates the conversation in the IBM i community.

The discussion around AI goes beyond mere curiosity—it reflects a genuine desire to learn everything about it, both advantages and disadvantages. The community sees AI not only as a developer tool but also as a business solution.

Both developers and business leaders find themselves in a discovery phase, exploring and learning how AI can be effectively integrated into their operations and workflows.

Here are some of the key takeaways from the conference:

AI is here to stay – organizations must adapt quickly to remain competitive
AI presents both opportunities and challenges for security on all levels and areas.
Developers should expect to work with both Small Language Models (SLMs) and Large Language Models (LLMs)
Carefully review third-party AI service User License Agreements (ULAs) to avoid legal and compliance risks that could significantly impact organizations.

The message from the speakers at the WMCPA this year is clear: developers who fail to embrace AI tools and concepts risk being left behind.

As AI becomes deeply integrated into development workflows, from code assistance to testing and optimization, understanding these technologies is no longer optional—it’s a career imperative.

There was so much to learn at the conference that this only scratches the surface. We’ll be diving deeper into many more AI-related insights and developments from WMCPA Spring Conference in future issues.

Development

💻 JavaScript opens new doors for IBM i developers

The rise of JavaScript in IBM i development reflects the platform’s evolution toward modern enterprise needs. With official Node.js support on IBM i, developers can now combine traditional RPG strengths with JavaScript’s web capabilities, enabling responsive interfaces, real-time processing, and seamless API integration while maintaining core business logic in RPG.

🔍 New Audit Data Mart filter parameter enhances journal data selection capabilities

IBM i’s MANAGE_AUDIT_JOURNAL_DATA_MART procedure now includes a DATA_MART_FILTER parameter, allowing customized SQL-based selection criteria up to 1000 characters for audit journal data management.

🚀 SQL Views vs. Logical Files: Unpacking the Modernization Magic

In this SQL 101 recap, Rafael Victoria-Pereira dives into the debate: Are views and logical files (LFs) the same?

Spoiler: Not quite.

Views handle bigger data (up to 64Kb) but lack keys, unlike most LFs. The fix? Pair a view with an SQL index for LF-like functionality. This combo boosts performance and modernizes IBM i databases, though source code safety remains key. It’s a practical nudge toward smarter SQL use.

Data

🚀 Rocket Software launches CDC tool for IBM i

The newly announced DataEdge suite includes outbound change data capture capabilities for IBM i. The Data Replicate & Sync tool now pushes Db2 data off the IBM i to systems like Apache Kafka in real-time via outbound change data capture (CDC)—all without taxing host CPWs. This keeps your production system lean while fueling off-host analytics and AI. Learn more about CDC tool.

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