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Quiet Dashboards, Hidden Dependencies: How to Retire a Legacy System Safely
Retiring a legacy system can look like an easy win: remove an expense, reduce maintenance, and give engineers one less thing to support. The difficulty is proving the business can actually function without it. An application that barely attracts a login may still supply a finance report, run a background task, or support an important maintenance procedure that nobody has needed in months. For senior engineers and technical leaders, that makes decommissioning a consequential assignment. It requires understanding work beyond your own team, persuading stakeholders to accept a change, and deciding when new evidence justifies delaying it. Those decisions can demonstrate leadership, provided you can explain what you found and what the organization gained. Engineers and technology leaders who spoke with Dice describe retirements that exposed missing functionality, undocumented dependencies, and gaps in otherwise successful migrations. Their experiences offer a practical framework: establish w
When Should a Tech Leader Stop an AI Pilot?
An AI pilot can deliver impressive results and still fall short of what a business needs. A translated page may contain mistakes; an automated report may need corrections before a client can use it. This requires human intervention, which increases time and cost spent on delivering a product. For tech leaders, the question is whether an AI-driven solution delivers enough value once you account for that additional work. The experiences of five business and technology leaders suggest a useful distinction. Redesign may make sense when a different workflow or better review could resolve the problem. Stopping may be warranted when the tool cannot meet an essential requirement or the remaining risks outweigh the expected benefit. Narrower automation use may preserve value, too. The decision depends on identifying what failed and what, if anything, would make the investment worthwhile. Evaluate What Customers Will Actually Receive Anthony Guerriero, managing partner at Manhattan Miami Real Es
What Did the ‘Black October’ Vulnerabilities Show Cyber About AI?
Was this year’s cybersecurity October surprise a shock to the system or overblown? Dubbed “Black October,” the month saw several vulnerability and bug disclosures that sent concerns rippling through the cybersecurity community. The most significant announcements over those 31 days were a pair of critical vulnerabilities, CVE-2026-109618 and CVE-2026-109619, discovered in PHP, the open-source scripting language that reportedly runs about 70 percent of the web. These critical remote code execution (RCE) vulnerabilities each have a CVSS rating of 9.2. Researchers at Palo Alto Networks Unit 42 initially uncovered about 22.6 million exposed instances potentially vulnerable to these PHP2Shell flaws. Another notable part of these disclosures is that researchers with Palo Alto Networks and others used OpenAI’s GPT-5.6 Sol, an advanced large language model designed to help solve complex mathematical, computational and cybersecurity problems, to uncover these flaws. Following those initial discl
Your Team Grew. Your Job Should Change Too.
A growing engineering team can change a manager’s job before anyone changes the expectations that come with it. Code reviews, technical decisions and delivery questions still need answers. Meanwhile, more direct reports need feedback, support and room to develop their own judgment. Keeping every responsibility can leave a manager stretched across work that increasingly competes for the same hours. Deciding what to give up is difficult when technical involvement helped establish your credibility in the first place. But a larger team calls for deliberate choices about who owns the work, who can make decisions and when the manager needs to step in. The challenge is to preserve accountability while creating enough space for other people to lead - and enough time to do the management work the team now needs. Identify Where the Team Is Waiting on You A full calendar can tell you that you’re busy. A closer look reveals which responsibilities belong on someone else’s calendar. Jason Long, foun
Foundational Coding Skills Still Essential In The Age Of AI
An efficiency gap is emerging when it comes to double-checking the work of artificial intelligence. In fact, Anthropic researchers recently surveyed 52 software engineers using Python to find out how AI affected their own abilities to produce and understand code. It assessed participants in four areas: debugging, code reading, code writing and conceptual understanding. Participants who used AI averaged 50% on the quiz, compared with 67% for those who coded by hand. The results raised concerns about whether software engineers who rely on AI can recognize when code is incorrect. “Productivity benefits may come at the cost of skills necessary to validate AI-written code if junior engineers’ skill development has been stunted by using AI in the first place,” an Anthropic blog post stated. Code literacy and foundational coding skills will be essential for checking AI-generated code, and for stepping in manually when that code breaks down. “Deep fundamentals are the superpower,” says Fisayo