We see engineering teams adopting artificial intelligence (AI) coding agents, who hit a wall they didn’t expect. Their agents handle single functions cleanly, but the moment work spans multiple files, output falls apart because the agents have no memory of the architecture they are building against. Isolated functions are manageable, while multi-file infrastructure work requires […]
Your team has been running Agile for years. Stories are planned in Jira, sprints run on two-week cycles, and the sprint board tells you exactly where everything stands. Releases ship on time, retrospectives close out action items, and the Definition of Done is defined and followed. Then comes the requirement: Automotive SPICE® (ASPICE) compliance. When your […]
Artificial intelligence is transforming how engineering teams develop products, analyze requirements, and identify risks. But for organizations developing safety-critical or highly regulated products, the conversation is about doing so responsibly. Many engineering leaders face the same challenge: How can we introduce AI into engineering workflows while maintaining control over the development process? The answer isn’t simply choosing the right AI model. Successful […]
Most proposal teams lose bids to process breakdown: a missed requirement buried in a 200-page document, a compliance gap discovered the night before submission, a subject matter expert who gave feedback in an email that never made it into the final draft. The request for proposal (RFP) response management process is one of the highest-stakes […]
Artificial intelligence (AI) coding assistants can make individual coding tasks appear faster, while organizational delivery metrics lag. The speed may show up in commits and pull requests (PRs), while customer-visible delivery stays flat. Those gains get absorbed somewhere between the individual keyboard and the production release, lost to downstream bottlenecks. Vice Presidents (VPs) and Directors […]
One of the challenges I often hear from our automotive customers is that a large portion of time disappears into tasks that are both very manual as well as very tedious. An example of one of these tasks is scanning standards or regulatory documents, finding consistencies both between the standards and their internal requirements, then tracing them […]
A two-person team ships a working product in three weeks. Eighteen months later, that same team has fifteen engineers, four enterprise prospects in the pipeline, and nobody who can answer a basic question about which features trace back to a committed requirement. The product that moved fast now moves slowly, and every change introduces another […]
A systems engineer writes, “The system shall respond quickly.” Three months later, a test engineer finds no pass/fail threshold attached to that word. The hardware team had designed for 500 milliseconds, while the software team built to 50. That conflict surfaced during integration, where the fix cost far more than a single clarifying question. Ambiguous […]
A founding team building a diagnostic instrument with companion software shipped its first prototype on the back of a shared Google Doc, Excel sheet, and a Jira backlog. Eighteen months later, an auditor pulled a random requirement and asked them to walk the chain from the user need down to the test that verified it. […]
Agent-first software workflows can begin with an empty git repository and a team of coding agents. By shipment, application logic, tests, continuous integration (CI) configuration, documentation, and internal tooling may all come from agents. The shift moves engineering work to a different layer. The job now is to design the specs, constraints, tools, and feedback […]
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