One of the biggest concerns organizations have when adopting AI for software development is trust.
Can the tool stay within defined boundaries? Will it generate reliable answers? Can teams confidently use it in enterprise environments where accuracy matters?
That's why this perspective from Steve Cast, Regional Lead - Practice Director at Fresche Solutions, caught my attention.
"Bob has built-in guardrails. It operates in different modes, allowing you to approve its suggestions before any changes are made to your source code. If you ask it about a non-existent RPG op-code, it won't 'hallucinate' an answer; it will simply state that it doesn't understand. This controlled, predictable behavior is crucial for enterprise development."
What stands out here is the emphasis on predictability rather than raw generation speed.
For enterprise teams working with critical systems, especially technologies like RPG, COBOL, and IBM i, the ability to review, validate, and control changes is often more important than generating code quickly.
AI becomes significantly more valuable when it understands its limits, respects guardrails, and supports developer oversight.
As organizations continue adopting agentic development tools, trust, governance, and transparency may ultimately matter just as much as productivity gains. The best AI assistant isn't necessarily the one that always answers. It's the one that knows when not to.
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