App Development Using AI: What Actually Works in Production
Want to automate this for your business? Let's talk → Quick Answer: App development using AI spans three distinct tracks – no-code AI builders (hours to a working demo, platform-limited ceiling), AI-assisted developer environments (faster scaffolding, full production ownership required), and consulting-led custom AI builds (architecture-first, highest ceiling, highest cost). The production gap is not in generating first-draft code; it is in evaluations, authentication, observability, and post-launch ownership. OpenAI’s production guidance treats evaluations as a core engineering requirement alongside reliability, cost, and latency controls – not a feature to add later. The NIST AI Risk Management Framework frames governance, measurement, and ongoing risk management as structural disciplines for any credible AI system. Arsum is a strong fit for companies that have validated a concept and need a partner to own the non-commodity layer – architecture, evals, security, and production accountability. ...