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AI & agentic workshops

Your team learns to ship with AI agents — on your own code.

We teach the way we build our products: every session is a lab on the participants' own code, documents and workflows. Two tracks — corporate teams and students — one standard: by the end, people ship with AI, safely.

16 sessions · labs · capstone4 evenings or 2 daysOnline or on-site10–25 per batchParticipants' own stack
Enquire for your team See the curriculum
Two tracks

Corporate teams and student cohorts.

Track 1 · Corporate teams · "Ship with AI agents"

Developers, product, QA and business users build, review, test and release with an AI agent — safely.

Participants work on their own project from the first hour — with permissions, hooks and review gates so it is safe for real work. Delivered for a fintech company's developer team in November 2026.

Who
Teams of 10–25; mixed roles work well
Format
Four evenings (3 h each) or two full days; online or at your office
Outcome
A working project per team, team conventions v1, each developer's own agent setup
Tools
The team's own stack and AI accounts — nothing to install on our side
Track 2 · Students · "AI for real work"

Final-year and early-career cohorts learn to do real work with AI — and show it.

Coding, research, documents and small agents, on real tasks — ending in a portfolio project built during the programme that candidates can show in interviews.

Who
Engineering, commerce and management students; college cohorts
Format
Short intensive (2 days) or weekly sessions; online or on campus
Outcome
A portfolio project, working habits with AI, interview-ready evidence
Next
Cohort dates are announced on our LinkedIn page
Curriculum · corporate track

Sixteen sessions. Every one is a lab.

Each session: ten minutes of method, a live demonstration with the exact prompts, then the lab on the participants' own project, then review. This is the programme delivered in November 2026.

16sessions
4evenings (or 2 days)
1capstone per team
10–25participants per batch
Evening 1

Working with an AI agent

  • Setting up the agent on the team's own project: plan mode, context files, conventions
  • Building a feature end-to-end with the agent — including a UI designed live
  • How to read, question and correct what the agent produces
Evening 2

Knowledge, safety and review

  • RAG over the team's own documents
  • Finding a planted legacy bug with the agent
  • Prompt-injection attack, permissions and a secret-protection hook
  • Reviewing a deliberately bad diff
Evening 3

Agents that fit your workflow

  • Hooks; the team's own MCP tool server
  • A reviewer agent and a custom review command
  • Headless automation from the command line
  • A backward-compatible API change driven by a failing test; quality tools as a reusable skill; version-control integration
Evening 4

Build, release and the capstone

  • Reproducible build; an eight-gate release script including an AI quality gate
  • Release, tag, hotfix and rollback
  • Capstone: a real fix with an evidence folder
  • Team conventions v1 and each developer's own agent setup
Why teams choose this

Practical, on your code, with a result at the end.

  • No slideware — labs from the first hour
  • Your stack, your repositories, your documents
  • Safety built in: permissions, hooks, review gates
  • Something working at the end: a project, conventions, each person's setup
  • The same methods we use to build and run our own platforms
Who teaches

The engineer who builds and operates our platforms.

Trading systems used by thousands of traders, AI agents in production, a test-automation platform delivered to a fintech client — everything taught is in daily use.

Lead trainer: Pawan Matade — senior fintech product engineer, DeMatade Algo Technology Solutions.

Enquire

Tell us about your team or cohort.

We reply within one working day with a proposed format and dates. No prices on this page by design — every programme is scoped to the team.

+91 93214 46611 · support@dematadesolution.com · pawan.matade@dematadesolution.com
Navi Mumbai, India · online anywhere
Your details are used only to respond to this enquiry — see our Privacy Policy.
FAQ

Common questions

Do participants need to install anything?
No. Participants use their own laptops, their own project and their organisation's AI accounts. We send a short setup note a few days before.
Which AI tools do you teach?
Agentic coding tools (we use Claude Code), LLM APIs, retrieval (RAG) and MCP tool servers — chosen for what the team actually works on. The methods carry over to other tools.
Can non-developers join?
Yes. Product, QA and business users join the same labs with their own tasks: documents, test plans, analysis and automation. Mixed teams get the most out of it.
Online or on-site?
Both. Four evenings online works well for working teams; two full days on-site for cohorts and colleges.
How is it priced?
Per participant, with a minimum batch size, GST extra. Send an enquiry with your team size and we reply with a proposal.