A critical barrier to timely decision-making has been the verification process itself. Verification workflows currently implemented by industry produce mountains of documents that are neither actionable nor readily digestible encouraging continuous analysis rather than prioritization based on operational impact. To counter this, acquisition stakeholders are now turning to tools such as Celeris Systems’ iRIS platform that are purpose-built to manage verification activities and provide real-time decision support on requirements compliance.

iRIS aggregates data across test events, analyses, and supplier inputs presenting and highlighting compliance status against mission-centric thresholds rather than against every technical line item. Program teams answer crucial questions: Which requirements materially affect warfighter performance? Which ones can be deferred to later increments without undermining capability? With transparent and actionable verification status available on demand, decision makers can exercise informed judgment rather than defaulting to a checklist mentality.

Increasingly, platforms like iRIS are being augmented with agentic AI to further accelerate that judgment. Agentic AI does not make decisions; it evaluates evidence, monitors progress, identifies risk patterns, and surfaces trade options aligned to mission priorities. Verification shifts from a retrospective reporting function to an active decision-support capability operating at tempo. Humans are accountable but no longer blind to what matters most.

Importantly, “good enough” is not a euphemism for cutting corners. It is an operational discipline grounded in mission relevance, informed risk management, defining performance thresholds tied to warfighter needs, accepting incremental delivery when appropriate, and using tools that illuminate where a system truly stands. When a verification tool such as iRIS shows that key operational parameters are satisfied and lower-priority elements remain pending, leaders can make disciplined calls that accelerate fielding without sacrificing essential performance.

The challenge is that this form of disciplined judgment is difficult. Program and systems engineering principles allow for trade-space analysis and risk management, but historically, these tools have been under-exercised. Over time, the system has trained itself to reward compliance and punish deviation – even when deviation would better serve warfighter needs. Program managers and engineers are responding to incentive structures that favor exhaustive adherence over timely relevance.

As a result, critical-decision-making muscles have atrophied. Choices are deferred upward or outward. Engineering design complexity rises exponentially. Reviews multiply to distribute accountability. The irony is that this pursuit of safety through compliance often produces the opposite outcome: late discovery of irrelevance, cost overruns, and capabilities that arrive too slowly to matter.

By restoring authority, responsibility, and accountability to program leadership and technical experts—supported by real-time compliance visibility, decision support, and agentic AI–driven prioritization—leaders can validate “good enough” against mission requirements with confidence and document those judgments in a defensible, data-forward way.

Industry must internalize a simple truth: perfection delivered too late is failure. “Good enough,” when grounded in mission priorities and informed judgment supported by real-time verification data, is not a compromise – it is a competitive advantage. The real enemy is not imperfection, but indecision disguised as rigor.