The AI coding workflow your team will actually keep using.

Hi, I’m Emran Online or on-site, I walk your engineers through real, working examples on your own stack using AI coding agents — and set up the workflows so your team keeps shipping this way after I leave.

Let’s talk How it works

Covers

Claude CodeContext BuildingCLAUDE.mdPlan ModeMCPsSkillsSubagentsSpec-Driven WorkflowRefined SDLCCI/CD PipelinesCode Review

What founders say

“Emran sat with our dev team, understood how we work, and tweaked our entire process around AI tooling. He has a rare ability to cut through the noise and deliver something that actually works.”

Parvez Akther

Founder & CEO, ThriveDesk

“Emran is one of the frontiers in AI-based development in our local tech scene. Working with him was a great experience. Would highly recommend.”

M. Mahbubur Rahman

Co-Founder & CTO, iViveLabs

“What sets Emran apart is his deep understanding of real-world software development. He doesn’t just talk about AI, he shows you how to ship with it.”

Eng. Ahmad Naser

Founder & CEO, Crebsol

The problem

Your team has AI tools. But nothing has changed.

Copilot is installed. ChatGPT tabs are open. But your team is not shipping faster — and they know it.

Everyone prompts differently

No shared patterns, no consistent output. Each engineer gets different results from the same tools, and nobody trusts what comes out.

AI made things slower

Review cycles doubled. Debugging AI-generated code takes longer than writing it from scratch. The speed promise didn’t land.

Impressive demos, broken production

The AI demo looked great. Then it hit real code, real edge cases, and real users. What works in a playground breaks in production.

The shift

Here’s what changes.

Before

Each engineer prompts their own way
AI experiments that never reach production
No review process for AI-generated code
Different results from the same tools
More time debugging AI output than writing code

After

One shared workflow the whole team follows
AI agents that ship real features, not prototypes
Review gates that catch problems before merge
Consistent output across the entire team
Engineers who choose AI because it’s faster

How it works

From first call to working system.

Phase 1

Discovery

I learn your stack, understand how your team works, and we decide what to demo during the workshop.

30-minute call

Phase 2

Workshop

Online or on-site with your team. I walk through real, working examples on your stack with AI agents.

Full day on-site · 5h online

Phase 3

SDLC Playbook

You get a documented dev process your team can follow independently, adapted to how you already work.

Custom for your team

Phase 4

Follow-Up

Post-workshop check-ins to ensure adoption sticks. Direct access for real questions.

2 weeks included

Deliverables

What you leave with.

01 · Shipped

Real, working examples

I demo 1–2 end-to-end examples on your stack during the workshop, so your team sees AI agents working in the same world they ship in — not a sandbox.

02 · Playbook

AI-powered SDLC playbook

A documented process your team can follow the next day. How to plan, generate, review, test, and deploy, all with AI agents wired in.

03 · Your Team

Engineers who know the workflow

After the workshop your team knows how to manage context windows, steer agents with AGENTS.md, and set up quality gates — practiced on real code, so it sticks.

Is this for you?

For builders, not browsers.

If you’re looking for an inspirational AI keynote, this isn’t it. This is a working session where we write code and build systems together.

1
You run a software company and your team writes code every day
2
You want to ship faster, not just talk about AI
3
Your team tried Copilot or ChatGPT but nothing stuck
4
You learn better by building than by watching presentations
5
You want a process your team follows after the workshop ends

Capabilities

Skills your team keeps.

Managing Context Windows

AI agents lose track in large codebases. The Plan / Execute / Clear loop keeps them focused and useful.

Steering AI Agents Reliably

AGENTS.md files, custom skills, and progressive disclosure give you control over what the agent does and doesn’t do.

Planning with PRDs

Break features into chunks that fit a context window. Validate the architecture with a tracer bullet before writing the rest.

Integrating AI into CI/CD

Your pipeline can run AI-powered tests, reviews, and checks automatically. We set that up during the workshop.

Running Autonomous Loops

Let agents code on their own while you review at checkpoints. Useful for large refactors, test generation, and boilerplate.

Preparing the Codebase

Most repos aren’t set up for AI agents. Small structural changes make a big difference in what the agent can do.

Investment

Two ways to run it.

Same workshop. Same outcome. Pick the format that fits your team.

Online · Live

Remote Workshop

$699

up to 5 hours, anywhere in the world

Same workshop, run live over video. Recorded for the team to revisit.

Up to 5 hours, live with your team
1–2 working examples on your stack
AI-powered SDLC playbook, customized
Session recording + shared doc
2 weeks of follow-up over chat

Let’s talk

On-site · In-person

On-site Workshop

$1,299

+ travel & accommodation, billed at cost

I come to your office. Whiteboards, pair sessions, side conversations — the works.

Full day, on-site at your office
Whiteboard + breakout time with leads
1–2 working examples on your stack
AI-powered SDLC playbook, customized
Pre-workshop discovery & stack review
2 weeks of follow-up over chat