{
  "id": 674922,
  "title": "[Webinar] Can you prove AI is working? (Sponsored)",
  "url": "https://urgent.news/2026/08/12/webinar-can-you-prove-ai-is-working-sponsored",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-12T15:32:23.000Z",
  "source": {
    "name": "ByteByteGo",
    "slug": "bytebytego",
    "url": "https://watch.getcontrast.io/register/unblocked-can-you-prove-ai-is-working"
  },
  "original_language": "en",
  "account": "The webinar titled \"Can you prove AI is working?\" addresses the challenge faced by software teams in determining the actual impact of AI tools on their engineering workflow. Despite the token spend indicating AI usage, teams often struggle to prove its contribution to delivery. This is primarily due to the metrics commonly monitored rewarding motion over tangible results. The issue lies in the context in which AI operates. The gains made by AI can fade away when transitioning from a feature branch to the main branch, as the agent may not fully grasp the intricacies of the system. Consequently, the agent may generate code that malfunctions in production, prompting teams to spend the subsequent sprint rectifying the errors rather than progressing with the review backlog or delivering new features.\n\nDuring the session, experts will discuss methods to accurately measure AI adoption within an organization. They will also delve into how context maturity influences the obstacles teams encounter. Furthermore, the webinar will outline the necessary steps to maximize the benefits derived from AI agents. The event is particularly tailored for engineering leaders, senior and staff engineers, and platform teams who are keen on obtaining clear, measurable evidence regarding the effectiveness of their AI tools. Attendees will also receive a complimentary assessment to ascertain their team's position on the AI maturity curve.",
  "summary": null,
  "key_points": [
    "Webinar addresses AI impact measurement challenge for software teams",
    "Experts discuss measuring AI adoption and context maturity",
    "Tailored for engineering leaders, senior staff, and platform teams"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}