Profound Logic Software

Every IBM i staffing firm has an AI story now.....and most of them mean the same thing, developers who use an AI assistant to write code faster. That's a faster human. It's not a different model for getting work done.

Our staff augmentation runs on an agentic orchestration platform. Our professionals operate autonomous agents that execute full build-test-fix cycles inside your environment. Not suggestions. Not drafts. Compiled, tested, validated code ready for developer review.

The distinction matters because the bottleneck in most IBM i development isn't how fast someone can write code. It's how much of the ex*****on cycle requires a human at every step. Agentic orchestration changes that. The developer shifts from executing to directing.

Output scales. Quality holds.

When every firm says they use AI, the question worth asking is what the AI actually does and what it leaves on the developer's plate.

Talk to us about what that looks like in practice: https://hubs.la/Q04rnj680

Most IBM i shops evaluating AI tools aren't asking which model to use. They're asking whether the tool understands RPG. The model underneath gets treated as an implementation detail.

That's worth a second look.

No single AI model is best at everything. Some handle long dependency chains better. Some are faster on well-defined, repetitive tasks. Some have deeper exposure to enterprise code patterns. RPG and COBOL sit in an unusual spot: not obscure, but underrepresented compared to Python or JavaScript in most training datasets. Model performance on IBM i work is genuinely uneven.

There's a simpler question worth asking any AI platform you evaluate. Can you see which model handled a given task, compare two models against the same input, and change your answer later without re-architecting your AI strategy?

If the answer is no, that's not an implementation detail. That's a strategic bet you're making by default.

Wondering if there's a better way? 🚨SPOILER ALERT: There is.
Check it out: https://hubs.la/Q04qxBsx0

A food retail company with over 50 years in business, hundreds of store locations, farming, processing, distribution, and retail all under one roof, was running store operations and maintenance workflows on IBM i green screens.

Field technicians couldn't report part purchases and usage in real time.
District managers couldn't see store-level performance without going through IT.
Equipment sat down longer than it needed to because the information to fix it wasn't accessible where the work happened.

By harnessing Profound AppDev they converted the green-screen applications to browser-based interfaces without touching the underlying RPG or COBOL. They gave District and Area Managers role-based dashboards with live visibility into performance across every location. Maintenance teams started logging part usage from the field in real time.

Faster equipment repairs. Smarter decisions from live data. Lower management overhead. And a foundation now in place for agentic AI to extend the platform further.

None of it required replacing the IBM i systems that had run the business for fifty years. And we can do the same for you.

Read the full case study: https://hubs.la/Q04qxwDq0

How One Food Retailer Futurized Store Ops Without Ripping Out Legacy Systems Real-time dashboards for area managers. Faster equipment repairs for maintenance teams. See how Profound AppDev helped a 50+ year food retail and dairy company futurize IBM i operations while keeping RPG and COBOL intact.

Multi-month IBM i development projects don't have to take months anymore.

Agentic coding environments handle code generation, testing, and validation autonomously. That compression is real: work that used to sit in a queue for a quarter can move to production in weeks. Not because the code is lower quality. Because the ex*****on loop no longer depends on a developer being present for every step of it.

CoderFlow brings that capability to every engagement model. Whether we own the project end to end, embed developers on your team, or set up the agentic environment that lets your existing developers move up to 10x faster, the tooling comes with us.

The features sitting in your backlog are not stuck because of effort. They're stuck because the capacity model for getting them done hasn't changed.

See how AI-accelerated development works: https://hubs.la/Q04pNdCv0

Technical debt doesn't stay the same. It compounds.

Every workaround added to a fragile codebase makes the next change harder. Every deferred fix increases the risk that the next release breaks something unexpected. Every patch layered on top of a system that was never designed for it consumes more maintenance budget than the one before.

IBM i organizations are feeling this in a specific way right now. IT budgets increasingly consumed by maintenance, patches, and firefighting leave less and less for the investments the business actually needs. Meanwhile, the developers who know where all the bodies are buried are approaching retirement, which makes existing debt exponentially harder to address.

The cost of unresolved technical debt isn't staying the same. It's going up. 😳

Our futurization process starts by mapping the environment to identify high-impact debt areas, those that carry the most operational and financial risk, before a single line of code is touched. You cannot build a future on an unstable foundation, and you cannot fix the right things without knowing which ones are actually costing you the most.

Ready to smash your technical debt? 👉 https://hubs.la/Q04qxvVr0

Ask an AI coding tool to fix a bug, and it hands you a suggestion. You still compile it. You still test it. You still debug whatever the model missed. You still validate it against how the system actually runs. The tool accelerated the writing. The engineering cycle that determines whether the code actually works is still yours.

In a clean greenfield environment, that gap is manageable. In an IBM i environment running RPG, COBOL, multi-library structures, and decades of interdependent business logic, the distance between "generated" and "verified" is often the majority of the work.

Verified, ready-to-commit code has been compiled against the real build environment. Tests have passed. Failures were caught, fixed, and retested autonomously until the output met defined acceptance criteria. The developer reviews a completed, bounded change with enough context to understand what ran and why.

A suggestion generated in the cloud and pasted into an IDE is not that. It is plausible. Those two things are not the same. Read how: https://hubs.la/Q04p96P_0

Most IBM i organizations have been through at least one modernization cycle. UI refreshes, code conversion, incremental patches. And most of them are still sitting with the same underlying problems they had before: technical debt racking up beneath the surface, fragile integrations that break under pressure, and a talent pool that keeps shrinking.

Surface-level changes don't solve deep problems. Every workaround, legacy integration, and deferred fix quietly increases operational risk.

Modernization addresses how your system looks.
Futurization addresses what it's capable of.

The difference is not cosmetic. It's structural. Futurization reduces complexity first, prioritizes by business value, builds automated testing as a safety net, and establishes a foundation for AI readiness from the beginning, not as an afterthought.

If your current path is giving you a system preserved, not a system transformed, it's worth asking whether you're solving the right problem.

Learn how IBM i Futurization works: https://hubs.la/Q04pN5Cb0

A head of customer service needed a single-character status column added to a subfile. She wanted to see which customers were active or inactive before opening individual records.

Small ask. In a normal development queue, it waits weeks.

The developer launched a CoderFlow task, described the requirement conversationally, and selected the specific screen element to give the agent direct visual context. CoderFlow spun up a container, pulled the source, and the agent read the program structure before making any changes. A few minutes later? The status column in the right position, F11 expand working correctly, status value accurate on navigation into the detail record.

Full account of what the agent did, which library it created, which objects it built, how it tested. Git diff available line by line. VS Code open in the container if the developer wanted to inspect before approving.

She got her answer the same afternoon.

That's the part of agentic coding that doesn't get talked about enough. It's not just the big conversion projects. It's every small request that used to wait weeks because there was always something more urgent.

See three real IBM i task walkthroughs: https://hubs.la/Q04qwJ2d0

1,250 locations. 14,000 types of equipment. A workforce of 20,000 people. And a system that required staff to physically carry large equipment to an indoor terminal to check it in, or write down the information by hand and re-enter it later.

For equipment that cannot be wheeled to a counter, that gap created delays, manual entry errors, and workflow bottlenecks across every branch.

The fix was not a platform replacement. It was a targeted mobile futurization using Profound AppDev.

Staff now carry mobile devices throughout the facility, scanning barcodes on equipment of any size with real-time synchronization back to IBM i. No middleware. No manual entry. No trip to the terminal.

The result? 70% increase in efficiency. Faster customer service. Fewer errors. And a workforce that mastered the new tools with minimal training.

The IBM i foundation stayed exactly where it was. The workflow around it changed everything.

Want to know how? Read the full case study: https://hubs.la/Q04p8W3R0

If you work with IBM i customers and you are not part of the Profound Futurization Alliance, it is worth understanding what you are leaving on the table.

IBM i shops are under more pressure than they have been in a long time. Developer retirements. Green screen fatigue. Board-level questions about the platform. That pressure translates into real, active demand for futurization solutions from the resellers, ISVs, and consulting partners those organizations already trust.

The Alliance gives partners access to the full Profound Logic suite, co-branded marketing materials, sales training, 24/7 support, and a recurring revenue model that extends client relationships rather than ending them at project close.

Task Force IT-Solutions is one example. They used Profound API to double Witra Logistics' daily processing capacity from 6,000 to 12,000 SKUs. That kind of outcome is what happens when a partner with deep IBM i customer relationships has enterprise-grade futurization tooling behind them.

If that sounds like something worth exploring, the application is open! Learn more about the Futurization Alliance: https://hubs.la/Q04p9s320