AI agents need fresher web data to stay reliable

A Business Reporter article featuring Decodo CEO Vaidotas Juknys argues that AI agents lose value when they rely on stale data and need live web connections tied to how fast information changes. The piece says fresher inputs can improve accuracy, transparency and confidence for tasks like code generation, regulation checks and market monitoring.

Why it matters: - AI agents are only as useful as the data they can reach, especially when they are used for code generation, automation and decision-making at speed. - Stale information can weaken trust in AI outputs and create errors when websites, regulations, products and technical documentation change. - A freshness strategy tied to data obsolescence can make AI systems more reliable and more transparent.

What happened: - Business Reporter published an article featuring Vaidotas Juknys, CEO of Decodo, on October 15, 2026. - The article argues that AI agents need a live connection to the part of the web they depend on. - The piece says static data snapshots should be replaced with live web access for current, authoritative information. - Decodo points readers to its article and its Web Data API, with a free starter plan offering up to 10,000 recurring requests.

The details: - Models trained on historical data have a knowledge cutoff. - Saved data snapshots can become stale quickly as online information changes. - The latest Stack Overflow Developer Survey found trust in AI-generated code accuracy fell from 40% to 29% in a single year, even as adoption increased. - The article says organisations should tier web connections based on how often data changes and how critical accuracy is. - Industry regulation may need monthly checks. - Product documentation may need weekly checks. - Market prices may need hourly or real-time updates. - Decodo’s Web Data API offers unified access across mapping, searching, crawling and scraping endpoints. - Decodo says the platform can help developers and businesses access reliable, real-time web data at scale. - Decodo says it has 125M+ ethically sourced IPs and proxy solutions for public web data collection.

Between the lines: - The core argument is not that AI needs more data, but that AI needs data refresh rates matched to the speed of change. - That shift would move AI infrastructure from static storage toward live connectivity and governed freshness. - The trust gap cited in the Stack Overflow survey suggests users are already noticing the limits of outdated inputs. - For businesses, the practical question is less about whether to use AI agents and more about which tasks can tolerate stale data.

What's next: - Organisations adopting AI agents may need to map each use case to a refresh cadence. - Faster-moving categories will likely require tighter live connections and more frequent updates. - Businesses that depend on public web data may increasingly look for infrastructure that can collect and refresh information at scale. - Decodo is positioning its Web Data API as part of that stack.

The bottom line: - AI agents work better when their data stays as fresh as the decisions they make. The more volatile the information, the more a live web connection matters.