FoxyInvoice Dev Blog: How an Angular SPA Was Made Crawlable by Search and AI Bots

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Developer behind FoxyInvoice, an Angular single-page application, documented how the app was invisible to search and AI crawlers because it served an empty HTML shell by default. To fix this, the team implemented build-time prerendering, generating static, fully populated HTML pages for all public marketing and template routes. A restrictive robots.txt allowlists only specific public paths, while an llms.txt file guides AI answer engines to relevant content. The pipeline also integrates IndexNow to push URL updates to search engines on every deployment, rather than waiting for scheduled recrawls. Access logs at the edge are used to monitor crawler activity and measure the effectiveness of these visibility improvements.

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Meta's AI Dojo Concept Shows Training Environments Boost Agent Performance

A DEV Community article by Nokka, published in September 2026, explains the concept of an 'AI Dojo' — a training environment where AI agents can repeatedly attempt tasks, fail, and improve, as opposed to traditional one-time benchmarks. The piece argues that standard benchmarks measure whether an agent can pass a test, but do not allow it to learn from its own failures in a structured way. Meta's FAIR research team demonstrated this distinction in mid-2025 by moving an existing AI agent called AIDE into their AIRA-dojo environment without modifying the agent itself, which raised its Kaggle medal rate from 35.2% to 45.9%. Further adjustments to the agent's operator instructions and search strategy pushed that rate to 47.7%, with the researchers attributing the gains to the training environment rather than changes to the model. The article is the first in a five-part series exploring how AI Dojos work and how smaller teams can apply the approach in practice.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

Why MCP Server Deployment Differs Sharply Between Desktop and Hosted Environments

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