• 4 tips to help the new innovator’s struggle with AI and traditional code A typical dilemma is a choice between two options. • However, today’s innovators and CIOs face a different challenge of dealing with both probabilistic and deterministic code, not separately, but together in a new hybrid application landscape. • What most people thought was going to be another year of agentic AI is quickly turning into a more practical focus on simultaneously dealing with probabilistic (AI/ML-driven) and deterministic (traditional rule-based) code. • Not a portfolio of both, but a growing number of hybrid applications that need to carefully and skillfully integrate the best of both guessing and knowing. • Many CIOs are no longer dealing withpilots and prototypesfocused on specific off-the-shelf AI apps or custom agentic apps built solely within agent builder platforms. • They’re now dealing with new application development requirements that need to combine both AI and traditional code.
Article Summaries:
- CIOs are increasingly building hybrid applications that blend probabilistic AI/ML code with deterministic rule‑based logic, moving beyond simple AI add‑ons. The article outlines four key recommendations: 1) Define clear boundaries and guardrails, using deterministic code for authoritative business rules and probabilistic agents for ambiguous human intent. 2) Adopt a dual‑representation architecture that co‑locates both types of logic to reduce integration costs and maintain data sovereignty. 3) Apply deterministic code where outcomes must be predictable, auditable, and repeatable, reserving agents for reasoning and judgment tasks. 4) Prioritise optimizing agentic outputs before integrating traditional guardrails, balancing innovation against failure tolerance.
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