Skip to contentSkip to main content
Get Useful Answers from AI — a free microcourse with a reusable templateStart learning
TechlyUp
Guest-Led Webinars Suggested first

Innovate with Ajay: Engineering Production-Ready AI Systems

See how a real AI feature moves from prototype to something you'd actually ship — with a checklist for what “production-ready” means.

Not scheduled yet — no date, time or fee fixed. The most-voted topic is hosted next.

Get mentorship on this topic

1:1 or squad batch · join the community or channel

Ajay Prajapat

Hosted by

Ajay Prajapat

AI Educator · Engineer · innovatewithajay.com

Visit site
TechlyUpGUEST-LED WEBINARSInnovate withAjay:EngineeringProduction-ReadyAI SystemsFREE WEBINAR TOPIC · VOTE

Learn this topic with a mentor

Don't want to wait for the webinar? Pick how you'd like help. Nothing is paid now — you see the fee before anything is booked.

  • Bring your own work — code, campaign, report or plan
  • Mentor matched to this topic
  • Time, format and fee confirmed by email first
1:1 mentorship for Innovate with Ajay: Engineering Production-Ready AI Systems
Ask on WhatsApp instead

See typical costs on mentorship pricing.

What this session would cover

Proposed outline — the host finalises the agenda once this topic is scheduled.

  1. 1What separates a working AI demo from a feature you can put in front of real users
  2. 2Walking one AI feature from prototype to release: inputs, prompt/model layer, output handling and fallbacks
  3. 3Handling the failure cases: empty, wrong, slow or unsafe model output and what the user sees each time
  4. 4Cost, latency and rate limits — measuring them before launch instead of discovering them after
  5. 5Logging, evaluation sets and how to know if a change made the feature better or worse
  6. 6A “production-ready” checklist you can run against your own AI feature, reviewed item by item

Who it's for

  • • Developers who have built an AI prototype and want to ship it responsibly
  • • Tech leads deciding whether an AI feature is ready for users

You'd leave with

  • A production-readiness checklist for AI features
  • A clear picture of the failure modes to design for before launch
  • A simple plan for evaluating and monitoring one AI feature