ChatGPT Traffic Up 48% in July 2026 as Bing Drops 50%, Creating Analytics Blind Spots

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ChatGPT.com recorded approximately 1.09 billion monthly US visits in July 2026, a 48% year-over-year rise, ranking it ninth among top US websites per Semrush data, while Bing.com saw traffic fall by roughly 50% over the same period. Google and YouTube continued to dominate, logging around 25.31 billion and 10.27 billion monthly US visits respectively, underscoring that AI has not displaced traditional search overnight. However, the data highlights a growing shift in how users first discover information, with AI assistants increasingly serving as an early step in the customer journey. A key challenge for businesses is that visits originating from AI platforms like ChatGPT often arrive without identifiable referral data, causing them to appear as direct traffic in tools like Google Analytics 4. This attribution gap means companies relying solely on conventional SEO metrics may be significantly underestimating the role AI-assisted discovery plays in driving traffic to their sites.

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WebForms.php 2.1 Released Using DeepSeek Conversion and Qwen Evaluation

WebForms.php 2.1, the PHP back-end for the WebForms Core server-driven web framework, has been officially released. Unlike a standard port, the codebase was converted from the primary C# reference implementation using the DeepSeek AI model, then independently evaluated using Qwen. The process involved multiple stages: AI-assisted conversion, manual review, AI evaluation, corrections, and final testing before release. A key requirement was that the output follow PHP conventions rather than mirroring C# syntax, including adapting naming styles and handling language differences such as PHP's lack of method overloading. The release brings the full WebForms Core programming model — covering DOM manipulation, events, WebSockets, SSE, and more — to PHP applications.

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ProgrammingDEV Community ·

AI Tools Now Drive 38% of New API Builds, Cutting Delivery Time Nearly in Half

According to multiple 2026 industry reports, AI-enabled tools were involved in designing, testing, or maintaining 38% of new APIs built in 2025. Postman's 2026 State of the API report found that 61% of backend teams now use at least one AI-assisted API tool weekly. Teams leveraging AI for spec generation, code scaffolding, and automated testing ship production code in roughly 14 days, compared to 25 days for manual-first workflows — a 44% speed improvement cited by RapidAPI's 2026 Benchmark Report. AI-generated test suites catch 41% more post-deployment bugs than manual scripting, though security experts caution that manual reviews still identify 27% more logic errors than AI alone. Tools such as Postman AI, GitHub Copilot, and Mintlify are among the leading platforms driving this shift, with Forrester estimating annual labor savings of $4,800 per developer.

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ProgrammingDEV Community ·

AI Tools Now Drive Daily SQL Work for 41% of Enterprise Database Engineers

According to a 2026 Gartner report, 41% of enterprise database engineers now use AI tools daily for SQL generation, optimization, or review, up sharply from 14% in 2023. AI-assisted database development has become standard practice in 52% of Fortune 500 engineering departments, cutting schema build times by an average of 48%, per the 2026 Stack Overflow Developer Survey. Tools such as GPT-5-powered copilots help developers draft data definition language, flag performance issues, and automate migration scripts, with projects reportedly shipping 23% faster as a result. AI-driven query optimization is also reducing tuning time by 72% compared to manual methods, while saving companies an estimated $2,100 per month in cloud compute costs. Experts caution, however, that AI-generated schema and query suggestions should always be reviewed before deployment, as blind adoption can lead to data loss or inefficient database design.

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ProgrammingDEV Community ·

Why Average Latency Misleads Engineers and What p90, p95, p99 Actually Mean

Average latency metrics can mask serious performance problems because slow outlier requests get diluted by the majority of fast ones, making dashboards look healthy while some users experience significant delays. Percentile metrics like p90, p95, and p99 offer a clearer picture by describing the experience of specific portions of traffic rather than a single blended figure. For example, a p99 of 3,100ms means one in every hundred requests takes over three seconds, a fact that an average would never reveal. Calculating these percentiles requires no advanced statistics — response times are simply sorted and the value at the corresponding position in the list is read off. Engineers are advised to track all three percentiles together, since p90 reflects typical performance while p99 exposes worst-case conditions on an ordinary day.

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