Synopsys (NASDAQ: SNPS) projected fourth-quarter financial results that exceed Wall Street expectations for both earnings per share and revenue.

The semiconductor design automation company expects adjusted earnings per share (EPS) to range between $4.10 and $4.16, surpassing the consensus analyst estimate of $4.00. This indicates a potential upside of up to 4% against the midpoint of the estimate.

Revenue Outlook

For the same period, Synopsys forecasts sales between $2.530 billion and $2.580 billion. The upper end of this range exceeds the analyst estimate of $2.552 billion by approximately 1%, while the lower end falls slightly short.

What the Numbers Show

The EPS guidance suggests a clear beat across the entire projected range, whereas the revenue outlook is mixed relative to estimates. The company’s ability to deliver higher profitability per share despite a revenue forecast that brackets the estimate implies effective cost management or favorable mix dynamics within the quarter.

Synopsys, Inc. (NASDAQ: SNPS) says the era of AI assistants is giving way to autonomous engineering, where AI orchestrates entire product development workflows rather than helping engineers with isolated tasks.

In an exclusive interview, Chief Product Development Officer Shankar Krishnamoorthy told Benzinga that investors should look beyond today's AI copilots. "The most important trend to watch is the transition from AI-assisted to autonomous engineering," he said, adding that "AI will orchestrate end-to-end engineering workflows across design, verification, simulation, and system validation."

From assistant to orchestrator

Krishnamoorthy described a fundamental shift in how AI creates value inside engineering organisations. Rather than acting as another software tool, autonomous AI increasingly becomes the workflow itself, coordinating multiple stages of product development while allowing engineers to focus on higher-value innovation. As chip designs and intelligent systems grow more sophisticated, engineering teams face unprecedented complexity across hardware, software, and physics. In response, he said, "organisations are moving beyond point solutions and task-specific AI assistants toward autonomous engineering workflows that can help manage this complexity at scale."

Synopsys already has early data supporting this direction. One customer observed a 5x-6x productivity gain using Synopsys' agentic flow for formal verification, and the AI-driven workflow also identified a persistent modeling bug that traditional tools had missed. The company's autonomous debugging workflow, developed with Microsoft Discovery, has shown reductions of 25%-40% in debug cycle time, saving weeks of engineering effort.

Competitive advantage in autonomous engineering

Krishnamoorthy argued that the companies best positioned to lead will be those that successfully combine agentic AI, accelerated computing, and multiphysics simulation. The goal, he said, is to "improve engineering velocity, deliver first-time right silicon, and advance innovation." First-time right silicon refers to producing a chip that works correctly without costly redesigns. Krishnamoorthy noted that end-to-end autonomous verification workflows compress weeks of manual labor into hours of agentic execution, and that AI is enabling engineers to explore more design alternatives before production rather than replacing them.

What the numbers show

The divergence between productivity gains in verification (up to 6x) versus debug cycle reductions (25%-40%) indicates that agentic AI currently offers the highest leverage in formal verification tasks. While debugging benefits significantly, the complete automation of verification logic provides a disproportionately larger efficiency multiplier for engineering teams. This suggests that as autonomous workflows expand into more stages of chip development, the cumulative impact on engineering velocity could be substantial.

Investor implications

The AI conversation has largely centred on chatbots, coding assistants, and productivity software. Synopsys argues the next competitive battleground lies deeper inside enterprise engineering, where AI evolves from an assistant into an orchestrator. Synopsys is scheduled to report earnings after market close on Wednesday. Investors will be looking not only for evidence that demand for AI-enabled engineering software remains strong, but also for signs that customers are adopting more autonomous workflows rather than standalone AI features.