Practical, hands-on AI training for software developers, engineering teams, and IT organisations ― covering coding, testing, documentation, automation, and responsible AI.
// Training Session → 30-Day Adoption Challenge → Day 30 Management Report
Each module is built around real developer tasks ― not AI theory. Every session is hands-on with live coding, testing, and documentation scenarios.
We don’t just train your developers and leave. We run a structured 30-day adoption programme that turns a training session into a measurable, organisation-wide habit — with a full management report on Day 30.
Before training begins, each developer completes a short AI readiness survey. We map the team’s current tool usage, skill gaps, and which repetitive tasks consume the most time. This becomes the baseline for the Day 30 report.
A full-day (or 2-day) hands-on workshop where developers build real AI workflows using their own codebase, documentation, and testing scenarios. Our ai expert leads every session personally.
Every developer receives a personalised 30-day challenge card — specific AI tasks to apply to their daily work. Not generic exercises. Tasks drawn from the actual work each developer does, identified during the pre-training assessment.
Throughout the 30 days, we track participation, challenge completion, and adoption signals via a lightweight weekly survey. No invasive monitoring — just a 3-minute weekly check-in that takes less time than a coffee break.
During the 30 days, developers flag repetitive development processes they encounter that are suitable for AI automation. These become part of the organisation’s AI opportunity backlog — informing future automation investment.
Your CTO, Engineering Head, or L&D Manager receives a comprehensive report on Day 30 — covering adoption, impact, and the road ahead for your team’s AI journey.
Participation Rate
How many developers actively engaged with the 30-day challenge and completed weekly check-ins
Adoption Observations
Which AI tools and workflows were most adopted, and where adoption friction occurred
Use Cases Discovered
Real AI use cases your developers identified in their own daily work during the 30 days
Developer Feedback
Aggregated, anonymised developer feedback on barriers, enablers, and tool preferences
Workflow Opportunities
Prioritised backlog of developer workflow automation opportunities identified by the team
Recommendations
Deepak’s specific next-step recommendations for continuing AI adoption across your engineering organisation
This is significantly more valuable than a training certificate. It is an AI adoption roadmap — built from your team’s real experience over 30 days.
📅 Book Free Assessment — Start Your 30-Day Journey| What you get | Typical 3-hr AI Workshop | AI Workflow India Programme |
|---|---|---|
| Hands-on with real developer code | ✗ Usually slides | ✓ Live sessions with actual code |
| 30-Day structured adoption programme | ✗ | ✓ Included — not optional |
| Personalised per-developer challenge card | ✗ | ✓ |
| Adoption monitoring throughout 30 days | ✗ | ✓ Weekly pulse surveys |
| Day 30 management report | ✗ | ✓ Full report to CTO / L&D |
| Responsible AI & security module | ✗ Rarely covered | ✓ Built into every session |
| India-specific tools & context | ✗ Usually US/UK content | ✓ |
| Automation workflow identification backlog | ✗ | ✓ |
AI-assisted coding, debugging, refactoring, and code explanation — so developers spend more time on complex problem-solving and less time on boilerplate, repetitive code, and basic documentation.
40% less time on routine coding tasksAutomated test case generation, AI-assisted bug analysis, and edge case identification — so QA engineers cover more test scenarios in less time and catch issues earlier in the development cycle.
3× faster test case generationAI-powered code review acceleration, architectural documentation, requirement analysis, and technical decision research — so tech leads spend time on architecture and mentoring, not administrative work.
Code review time cut by 50%User story generation, requirement analysis, PRD drafting, and technical documentation — so PMs and BAs produce sharper, more complete specs faster, reducing back-and-forth with engineering.
5× faster user story and spec creationAI-assisted script generation, infrastructure documentation, runbook automation, and incident analysis — so DevOps teams build more reliable platforms with AI-accelerated tooling and documentation.
Runbook and IaC documentation automatedThe 30-day adoption programme is designed specifically to give engineering leaders measurable, reportable outcomes — not just a training completion certificate. The Day 30 report is your ROI evidence.
Day 30 Management Report — your ROI evidenceAll tools are evaluated for code security, IP considerations, and responsible use. We teach frameworks that protect your codebase while maximising productivity.
🔒 Code Security & IP Protection: We never teach developers to paste proprietary business logic, client data, or trade secrets into public AI tools. Every module includes specific guidance on what to share with AI tools and what to keep within your secure development environment ― fully aligned with your company’s security and IP policies.
“I was sceptical that an AI training programme would teach experienced developers anything genuinely useful. By the end of Day 1, every developer on my team ― including our most senior engineers ― had at least 2 workflows they were going to implement immediately. The testing module alone saved us an estimated 6 hours per developer per sprint.”
“The 30-day adoption programme is what sets this apart from every other AI training we’ve done. After previous trainings, AI usage peaked on Day 1 and faded. After AI Workflow India’s programme, at Day 30 we had 18 of 24 developers actively using AI tools daily. The management report gave our CTO exactly the data he needed to justify further investment.”
“As a tech lead, my biggest time drain was writing technical documentation and code review comments. After the training, I use Claude for first drafts of both ― it takes me 10 minutes to review and refine what used to take an hour to write. I now cover 3× more code review requests per week and my documentation is more comprehensive.”
“The responsible AI module was the one I didn’t know I needed. We had junior developers pasting entire database schemas into ChatGPT. After training, the whole team follows our new AI usage policy ― which we built as part of the training using Deepak’s templates. Security and productivity, both addressed in one programme.”
Start with a free 30-minute assessment. Our team maps your team’s AI readiness, runs a live demo using your actual tech stack, and outlines your 30-day adoption roadmap. No commitment required.
Join developers across India using AI to write better code faster, generate tests automatically, and spend more time solving problems — and less time on everything else.
AI Workflow India · Saraj Systems (OPC) Pvt Ltd · +91 987 3816 607 · Info@aiworkflowindia.com