Flux Expands Platform to Expose AI-Accelerated Engineering Blind Spots Undermining Business Outcomes

Engineering leaders can now deliver code-based evidence that proves AI investment payoff to leadership and the board


BOSTON, MA – September 23, 2026 – Flux, a code-first engineering intelligence platform, today announced a platform expansion with five new capabilities that enable engineering leaders to measure and prove the return on AI-accelerated development: verified velocity, trusted review, auditable work, continuous quality, and defensible spend. Each addresses a blind spot that otherwise leaves the outcomes of AI adoption unproven.

Over the past year, Flux has heard the same question from engineering leaders across industries and company sizes: is our AI bet paying off, and can we prove it? Most leaders measure tickets, story points, sprint velocity, token usage, and adoption percentages. That shows activity, not outcomes. DORA’s 2025 research found 90% of software professionals use AI daily, up from 76% in 2024, yet AI primarily amplifies the gap between strong organizations and struggling ones.

“AI is the biggest bet most engineering organizations have ever made, and the blind spots undermining adoption hide inside tools built for a different era of software development,” said Ted Julian, CEO at Flux. “Tickets and adoption rates describe intent. The code itself shows what the team actually built and delivered.”

The new capabilities add an outcomes layer to Flux’s platform, drawn from the same code analysis Flux already performs. Leaders don’t require new instrumentation or process change. Flux identifies each blind spot independently: an organization can be strong on one and exposed on another.

  • Verified velocity: addresses velocity theater by classifying every merged change as feature, maintenance, bug fix, or refactor, then checking deployment frequency and lead time against the organization’s historical baseline, so a spike in activity counts as progress only when the code backs it up.
  • Trusted review: manages review debt by tracking time-to-first-review, reviewer availability, and review load distribution, then reading review depth against the size and risk of each change. Leaders catch review pile-up before the bottleneck falls on an under-resourced group of senior engineers.
  • Auditable work: uncovers hidden work by surfacing code activity directly from commits and pull request history, so significant changes are visible and attributable regardless of ticket status.
  • Continuous quality: identifies quality drift by tracking new versus resolved security findings, newly introduced dependencies, and failure and recovery trends against each team’s norms, so drift becomes visible before it turns into an incident in production.
  • Defensible spend: resolves unproven spend by classifying work as capitalizable or operational, and as feature or maintenance investment, giving finance and leadership defensible evidence for spend and R&D credits. It measures effort and allocation instead of AI spend and token usage.

“I’ve spent the last year trying to prove where our engineering budget actually goes,” said Gunter Ollmann, CTO at Cobalt, the leader of human-led, AI-powered offensive security. “Now I have evidence I can hand to finance for R&D credit substantiation, and to the board when they ask if these bets are paying off.”

Flux’s new platform capabilities are now generally available. Join Flux’s October 20 webinar on the five blind spots and how to address them.

About Flux

Flux is a code-first engineering intelligence platform that helps engineering leaders make better decisions with ground-truth visibility into the work actually happening across today’s complex, AI-accelerated codebases. Instead of relying on tickets, Flux reveals the work teams are doing, surfaces risk and technical debt, and connects engineering activity to business outcomes. With this visibility, leaders can distinguish innovation from maintenance, spot emerging issues before they become incidents, and understand collaboration patterns to build healthier, higher-performing teams across their engineering organization. Learn more at www.askflux.ai, explore the resource library, and follow Flux on LinkedIn.