How Professional Developers Should Use AI Coding Tools
Where AI coding tools genuinely speed up professional development work, and where manual review still matters.
Not scheduled yet — no date, time or fee fixed. The most-voted topic is hosted next.
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Suggested mentor
Ajay Prajapat
AI Systems Architect
15+ years of experience · Ex-Apple
About mentor & skills Visit siteinnovatewithajay.com
About the suggested mentor
Ajay Prajapat
AI Systems Architect
- 15+ years of experience
- Ex-Apple
AI Systems Architect with 15+ years of experience, including building production GenAI systems — RAG pipelines, AI agents, prompt engineering and GenAI architecture. His sessions are hands-on: expect real workflows, live builds and honest trade-offs, not slideware.
Skills & expertise
- AI-assisted Development
- Full-stack Development
- AI Agents
- RAG & MCP
- System Design
- Project Reviews
- Prompt Engineering
- GenAI Architecture
A suggested match for this topic. The trainer and session details will be confirmed when the webinar is scheduled.
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
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- Time, format and fee confirmed by email first
What this session would cover
Proposed outline — the mentor finalises the agenda once this topic is scheduled.
- 1Tasks where AI tools save real time: boilerplate, tests, refactors and explanations
- 2Tasks where AI output needs careful checking: architecture, security and edge cases
- 3Giving the tool the right context from your codebase
- 4Keeping changes small and reviewable
- 5Team practices: code review, attribution and shared guidelines
- 6Avoiding skill atrophy while using AI every day
Who it's for
- • Working software developers
- • Engineering leads setting team practices for AI tools
You'd leave with
- A personal AI coding workflow
- A list of tasks to delegate vs. review closely
- Starting points for team AI guidelines
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