COMMON POWERUp 2026

Your IBM i isn't going anywhere, but the systems around it keep growing. You have cloud platforms, third-party tools, and APIs that all need to talk to your core data and business logic. Getting them all to work together was already a challenge. Now, AI needs to fit in too.
In this session, we’ll show you how to bring AI to your current tech stack. We'll build a working AI application that connects to existing systems and data. We’ll connect to DB2 files, call RPG programs, and integrate with external APIs and cloud services. 
Along the way, we’ll cover the important decisions: data access controls, LLM selection, and AI governance so nothing touches your production environment without your say-so.
You'll leave with a clear picture of how AI connects to the data and systems you already have and how to build AI tools that fit into your business.

All IBM external storage units can perform “instant copy” of all the disks of your IBM i LPAR.
Historically made using the ‘FlashCopy’ technology, these “instant copies” are now possible with a new method called ‘Snapshot’ or ‘Policy based FlashCopy’.
Discover the differences and how to use those two technologies to simplify and secure operations on your IBM i partitions:

• To create easily manually a copy of your prod to test a change on it (or create a backup copy before a version change)
• To perform daily several planned “instant copy” to create regular protection against ransomware or data corruption
• To reduce, using IBM i commands, the backup window to less than 2 minutes
• To refresh nearly instantly your test/acceptance/preprod environment

 
See how to use and automate this capability with the powerful product “Flash for i”

As applications are modernized, it is common to move from green screen interfaces to browser-based applications. In many cases, the associated HTTP server runs on the IBM i in the QHTTPSVR subsystem. These web applications access the database, perhaps directly, but also by using SQL CLI, which results in the database access running in an QSQSRVR jobs in the QSYSWRK subsystem. As environments become more complex, one may see several web instances using a large number of QSQSRVR jobs. This default configuration can make it difficult to understand system resources used by the application, as well as related challenges in troubleshooting problems. This session is a case study of using subsystems to isolate web applications to their own subsystem; the HTTP server instance and related QSQSRVR jobs running in the same subsystem.

Learning Objectives:

In this session you will learn how to: - Configure HTTP instances to run in their own subsystem - Set up the system so QSQSRVR jobs run in the subsystem of the requester - How to use the Performance Data Investigator to review performance by subsystem after the configuration changes are made

Most AI coding tools make you faster at writing code. CoderFlow does something different: it finishes the work — and it keeps working while you don't. In this webinar, we will walk through how CoderFlow, Profound Logic's enterprise agentic coding platform, executes the full engineering workflow autonomously. From compiling and testing to fixing failures and iterating until acceptance criteria are met, CoderFlow delivers verified, ready-to-commit outcomes instead of suggestions that still require you to drive every step.

Unlike copilot-style tools that pause and wait for your next prompt, CoderFlow runs continuously in the background — tackling queued tasks, resolving issues, and closing tickets without requiring a developer in the loop at every stage. Think of it less like a coding assistant and more like a tireless team member that works in parallel with your existing engineers, around the clock.

We will cover how autonomous agents work inside isolated containers, how the build-test-fix loop actually runs, and what work automation looks like in practice — including how teams are restructuring their sprint workflows, reducing toil, and reallocating engineering time to higher-value problems.

If you have been exploring AI coding tools and wondering whether there is something more capable for complex, real-world systems — or if you are ready to move from AI-assisted development to AI-automated delivery — this session is for you.

Learning Objectives:

• Understand the difference between AI assistance and AI automation — Learn how agentic coding platforms like CoderFlow move beyond suggestion-based copilots to autonomously complete end-to-end engineering tasks.
• See the build-test-fix loop in action — Discover how CoderFlow runs inside isolated containers, iterates on failures, and delivers verified, commit-ready code without manual intervention at each step.
• Explore real-world workflow transformation — Learn how engineering teams are restructuring sprints, reducing repetitive toil, and shifting developer focus from debugging AI output to reviewing completed work.
• Assess the impact on team capacity and throughput — Understand how running autonomous agents in parallel with your existing team can increase delivery speed without proportionally increasing headcount.
• Identify where agentic automation fits in your stack — Leave with a practical framework for evaluating whether CoderFlow is the right fit for your organization's complexity, systems, and engineering goals.

Call Home Automation is changing the way IBM systems detect and respond to issues, cutting down manual work and speeding up resolution. In this session, we will walk through what Call Home is, how the automation works behind the scenes, and how recent enhancements create an improved customer experience by improving accuracy, efficiency, and overall system reliability.

We will cover how these updates reduce noise, prevent duplicate actions, and get the right information where it needs to go faster. Whether you have are looking to have Call Home enabled or are looking to get more out of your current setup, you will walk away with practical takeaways you can leverage immediately.

Did you know your CL programs can run SQL statements directly — no RPG required? In this quick, practical session, you’ll learn how to combine the simplicity of CL with the power of SQL to automate and simplify everyday IBM i operations. Simon will demonstrate how to use the RUNSQL and RUNSQLSTM commands to perform tasks such as clearing or updating data, saving results to output files, and even controlling system operations dynamically. You’ll see examples of using SQL for file maintenance, logging, and automation — all inside standard CL programs. If you still think CL is limited to DLTF, CPYF, and SAVLIB, this session will change how you write job control forever.

Learning Objectives:

Learning Objectives = After attending this session, participants will be able to: - Use the RUNSQL and RUNSQLSTM commands within CL programs. - Perform file updates, inserts, and deletes directly from CL. - Capture SQL results and use them to control job flow. - Combine CL and SQL for more efficient batch and automation scripts.