Dev's site jumps from 4 to 115 Google-indexed pages in six weeks with minimal changes

·1 views

A developer behind tamethebot.com, a free AI prompt library, saw Google-indexed pages surge from 4 to 115 over six weeks without making significant content or technical changes to the site. The author had previously argued the low indexing was a crawl-budget issue on a new domain lacking backlinks, a theory largely supported by the outcome. The only notable off-site change was a DEV Community post that included two dofollow backlinks to the site, though the author acknowledges that domain aging and natural crawl recovery cannot be ruled out as contributing factors. Organic Google sessions rose roughly 163% over the following 30 days, though the author notes the base traffic was very small and some recorded visits were likely automated crawlers from known datacenter locations. A separate bug was discovered in the site's IndexNow deploy hook, which had been silently failing for weeks, though this affected only Bing and Yandex pings and had no bearing on Google's crawl behavior.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

How to Fix CORS Errors in React Apps: Backend Headers, Proxies and More

CORS errors are a common frustration for React developers, occurring when browsers block frontend requests to APIs that work fine in tools like Postman or curl. The root cause is a browser security policy that requires servers to explicitly allow cross-origin requests via response headers such as Access-Control-Allow-Origin. The correct fix lies on the backend, where developers using Node.js, Flask, or Laravel can add CORS middleware or headers to permit requests from their frontend origin. During local development, a proxy entry in package.json can route requests through React's dev server as a workaround, though this does not apply to production builds. Public CORS proxy services exist as a last resort but are discouraged for production use due to latency, rate limits, and security concerns.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Topicary Brings Structured Authoring to Technical Writers Without XML

Topicary is a content authoring tool that applies structured authoring principles — long associated with XML-based systems like DITA — without requiring users to write any markup. The platform lets writers save reusable content blocks called components, which automatically update across all referencing topics when the source is edited. It also supports conditional content filtering by audience, product, or platform, with changes reflected instantly in the editor without a separate build step. Variables allow single-point updates for recurring values like product names or version numbers across an entire project. Topicary can import existing content from formats including Markdown, DITA, MadCap Flare, Confluence, Word, and OpenAPI 3.x specifications.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Microsoft Launches Production-Ready AI Agent Harness and Hosted Agents at Build 2026

Microsoft announced the General Availability of Agent Harness and Foundry Hosted Agents at its Build 2026 conference, marking a shift from experimental tooling to a fully supported production runtime. Agent Harness is a single binary handling the operational core of AI agents, including function invocation, context compaction, history persistence, tool approval, and built-in OpenTelemetry observability. Foundry Hosted Agents offers the same capabilities as a managed, consumption-based cloud service accessible via a single API call. Both products run locally, in containers, or as a hosted service, and support multi-agent orchestration with connectors for GitHub Copilot and the Claude Agent SDK. The release addresses longstanding production challenges teams faced when deploying AI agents, positioning the infrastructure layer — not the AI model itself — as the core product.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Spring AI Tips to Cut LLM Costs by Managing Output Tokens and Chat Memory

A developer guide published on DEV Community outlines practical strategies for controlling large language model (LLM) costs using Spring AI, focusing on output tokens, reasoning tokens, and conversation history. Output tokens typically cost five to eight times more than input tokens, and reasoning models compound this by generating hidden thinking tokens billed at the same higher rate. Spring AI offers a provider-independent maxTokens cap and provider-specific reasoning controls, such as OpenAI's reasoning-effort setting and Anthropic's thinking-token budget, to limit runaway response costs. The guide warns that a Spring AI 2.0 upgrade raised Anthropic's default maxTokens from 500 to 4096, potentially multiplying response costs for users who relied on the old cap without realising it. Developers are also cautioned to disable reasoning during local Ollama development, since models like qwen3 and deepseek-r1 use reasoning by default, making hidden token usage easy to overlook before moving to a billed production environment.

0 comments Read more at DEV Community