DEV Community: Seyhun Akyürek

Book: AI at Work: Future-Proofing Your Career in the Age of Automation

Seyhun Akyürek — Sun, 02 Nov 2025 13:56:35 +0000

Artificial Intelligence isn’t coming for your job — it’s already sitting in your inbox, joining your meetings, and quietly reshaping the way you work. Whether you notice it or not, automation has entered nearly every profession — from marketing to law, from design to finance. The real question isn’t “Will AI change my career?” It’s “Will I lead it, or be replaced by someone who does?”

That question sits at the heart of my new book, AI at Work: How to Future-Proof Your Career in the Age of Automation — a practical guide to working smarter, not harder, with AI.

Why I Wrote This Book

In conversations with professionals across industries, one theme kept surfacing: people felt overwhelmed. They saw the explosion of AI tools — ChatGPT, Claude, Copilot, Midjourney — but didn’t know how to translate that into real productivity or value. Many feared becoming obsolete.

I wanted to cut through that noise and create something different — a roadmap for everyday professionals who want to stay indispensable in this new era.

This book is not a technical manual. You don’t need to be a programmer or data scientist. Instead, it shows you how to integrate AI into your daily workflow — your emails, your strategy sessions, your reports, your creative brainstorming — without the jargon or hype.

Inside the Book
Each chapter focuses on a practical dimension of AI-powered work:

Reclaiming time: How to automate repetitive tasks and focus on higher-value thinking.

Thinking smarter: How to use AI as a strategic partner for decision-making, not just a typing assistant.

Creative leverage: How to turn AI into a tool for ideation, storytelling, and innovation.

Building resilience: How to adapt your career to technological change — not by chasing every new tool, but by learning how to think with them.

By the end, readers gain a framework for continuous adaptation — the mindset and methods needed to thrive in an AI-driven workplace.

Who It’s For
If you’re a manager, freelancer, or business owner navigating this technological shift, this book is written for you. It will help you:

Stay relevant as automation accelerates.

Build a hybrid skillset — human judgment amplified by machine intelligence.

Lead with confidence in an era of constant disruption.

Whether you’re leading teams or building your personal brand, the goal is simple: make AI your career co-pilot, not your competitor.

Why You Should Read
Because the world of work is changing faster than ever — and you can’t afford to stand still.

AI isn’t just transforming industries — it’s redefining what valuable work means. Whether you’re a manager, freelancer, or business owner, the question is no longer “Will AI change my job?” but “Will I lead with it — or be replaced by someone who does?”

This book helps you stay on the right side of that shift.

Here’s what you’ll gain:

Clarity — Understand how automation is reshaping your industry and where your unique human edge still matters.

Confidence — Learn how to work with AI tools like ChatGPT, Copilot, and Midjourney without needing to be technical.

Practical systems — Step-by-step frameworks to save hours every week, sharpen decisions, and enhance creativity.

Future readiness — A mindset and strategy for staying indispensable — no matter how fast technology evolves.

No fluff, no hype — just real-world insights for people who want to lead, not lag behind.

If you’ve ever wondered how to make AI work for you instead of against you — this book is your starting point.

The Big Idea
AI won’t replace humans. But humans who understand AI will replace those who don’t.
This isn’t about chasing every shiny tool; it’s about learning how to use technology strategically — to enhance your creativity, clarity, and capability.

Automation may change the tools we use, but it doesn’t change what matters most: curiosity, adaptability, and the courage to keep learning.

Take control of your career before AI does.
Get your copy of AI at Work: How to Future-Proof Your Career in the Age of Automation today and start turning technology into your advantage.

👉 Buy now on Amazon Kindle

AI at Work: How to Future-Proof Your Career in the Age of Automation. By Seyhun Akyürek

Thank you.

Book: Modern Fintech & Banking Transformation: A Comprehensive Guide

Seyhun Akyürek — Sun, 02 Nov 2025 13:53:16 +0000

Whether you’re a fintech founder, banking executive, compliance officer, or tech architect, this book offers a complete blueprint for transformation in the digital financial era.

I decided to wrote a book offers a definitive guide for professionals, innovators, and institutions navigating the rapidly evolving landscape of fintech and modern banking. With financial services undergoing unprecedented digital disruption, the book provides a holistic framework to build resilient, compliant, customer-centric, and future-ready financial institutions.

Press enter or click to view image in full size

Chapter 1 — Business Domain Guidelines and Frameworks for Fintech/Banking Transformation
This chapter lays the foundation by outlining the core business domains crucial to fintech and banking transformation. Readers are introduced to strategic models and transformation frameworks that align business goals with digital capabilities. It explores the convergence of finance and technology, regulatory influences, and customer behavior as a basis for setting up modern financial ecosystems.

Chapter 2 — Comprehensive Operational Excellence, Service Management, and Process Optimization
Focusing on delivering excellence in service and operational performance, this chapter dives into methodologies like Lean, Six Sigma, and ITIL tailored for the financial industry. It details how financial institutions can streamline operations, eliminate inefficiencies, and elevate service quality through intelligent process design and performance measurement.

Chapter 3 — Security and Compliance in Fintech: Risk Management and Regulatory Frameworks
Security, trust, and compliance are non-negotiable in financial services. This chapter provides a robust overview of regulatory expectations (e.g., GDPR, PSD2, SOX), threat landscapes, and best practices in cybersecurity. It also explores risk management models that protect consumer data and institutional integrity in a dynamic digital environment.

Chapter 4 — Modern Financial Products and Services: Development and Delivery
This chapter serves as a practical training guide on modern banking products, including payments, lending, neobanking, and digital wealth platforms. It explains the lifecycle of product development — from ideation and compliance vetting to agile delivery and customer feedback loops — geared toward building innovative, scalable financial solutions.

Chapter 5 — Organizational Structure and Leadership in Financial Services
Effective leadership and agile governance are critical to successful transformation. This chapter discusses modern organizational design principles for banks and fintechs, including cross-functional teams, decentralized decision-making, and executive sponsorship. It also outlines leadership competencies needed in the age of AI, open banking, and digital-first strategies.

Chapter 6 — Technical Implementation Guides and Methodologies
Bringing it all together, the final chapter provides hands-on implementation guides. Topics include cloud-native architectures, API strategies, DevSecOps, data platforms, and integration approaches. It also addresses technical debt, vendor management, and change management strategies to ensure sustainable innovation and compliance.

In summary, Modern Fintech & Banking Transformation equips readers with the strategic insight, operational playbooks, compliance knowledge, leadership models, and technical know-how required to build and scale successful financial service organizations. It is not only a reference manual but a call to action for professionals shaping the future of finance.

Available to buy from Amazon Kindle store

https://www.amazon.com/dp/B0FCW8CDNV

Thank you for reading.

Book: Invisible Colleagues: Redefining Work in the Age of AI

Seyhun Akyürek — Sun, 02 Nov 2025 12:33:48 +0000

The office has changed, but not in the ways we imagined. Walls have disappeared, meetings have gone virtual, and somewhere between our calendars and our codebases, new colleagues have quietly appeared
These colleagues don’t drink coffee, take breaks, or celebrate birthdays. Yet they influence nearly every decision we make. They prioritize our tasks, analyze our data, and even suggest the words we write.

They are algorithms, AI agents, and artificial minds — shaping our workday just as much as the teammates who sit across from us.

This is the world explored in Invisible Colleagues: Rethinking Collaboration in the Age of AI by me (Seyhun Akyurek), this book that goes beyond technology to examine the evolving relationship between humans and the systems we’ve built to think alongside us.

The New Ecology of Work
Artificial intelligence is no longer just a background tool. It is a collaborator. As AI moves from support to co-creator, the boundaries of teamwork are dissolving. Today, collaboration isn’t just about humans coordinating tasks; it’s about sharing intentions, values, and sometimes trust, with entities that aren’t alive, conscious, or human — yet still profoundly shape outcomes.

The book invites readers to consider:

What does trust mean when one member of your team is a machine?
How do ethics apply when AI makes decisions that affect humans?
How can workflows balance human intuition with machine precision?

Through engaging storytelling and practical insight, Akyürek illustrates how our invisible colleagues are transforming the psychology of work. He encourages us to see AI not as a threat or a replacement, but as a partner — one that can extend our abilities and open new possibilities.

Why Professionals Should Read This Book
Whether you are a leader, engineer, designer, or creative professional, your workday is already influenced by invisible systems. Ignoring this shift is no longer an option. This book helps you:

Understand AI collaboration — move beyond the hype and fear to grasp the practical realities of working with intelligent systems.
Build trust and ethics — learn how to foster responsible, human-centered collaboration with algorithms.
Redefine your role — discover how to augment your skills and influence in a workplace where human and machine co-create.
Design better workflows — balance human judgment and machine precision to maximize productivity and innovation.

Invisible Colleagues is not a technical manual, nor a prophecy of AI takeover. It is a guide to the future of work, offering a lens to understand the subtle yet profound ways AI is changing collaboration, creativity, and meaning in professional life.

Who Should Read
What sets this book apart is its storytelling. I am walking the reader through real-world examples, thoughtful reflections, and ethical dilemmas that arise when AI becomes a coworker. It’s a narrative that resonates with both seasoned professionals navigating AI in their organizations and general readers curious about how technology shapes daily life.

By humanizing the invisible and revealing the machinery behind modern workflows, the book shows that learning to collaborate with AI can also deepen our own human capacities — empathy, adaptation, and creativity.

For Whom This Book Is
Professionals seeking to thrive in AI-augmented workplaces.

AI enthusiasts eager to understand the societal and psychological impact of intelligent systems.

General readers curious about how technology is changing the way we think, decide, and work.

If you want to understand not just AI technology, but a new kind of teamwork it creates, Invisible Colleagues is an essential read.

What makes Invisible Colleagues particularly compelling is its balance between storytelling and insight. I doesn’t just present theory; I paint vivid scenarios of modern work life — meetings where suggestions pop up mid-conversation from unseen systems, projects where AI partners highlight blind spots, and workplaces where the line between human and machine decision-making blurs.

Each chapter invites you to reflect: what does teamwork mean when one member isn’t human, isn’t conscious, but can shape outcomes just as decisively?

For professionals, this book is a roadmap to staying relevant in a workplace that’s increasingly augmented. For general readers, it’s an eye-opening look at how technology silently guides our daily lives. For AI enthusiasts, it’s a rare exploration of the ethical, psychological, and practical dimensions of human-machine collaboration.

Invisible Colleagues isn’t about fearing AI or succumbing to hype. It’s about seeing it as part of a new ecology of work — one where human adaptability, empathy, and creativity remain central, even as our unseen colleagues grow ever more capable.

Step into the future of work. Meet your invisible colleagues. And learn how to work with them, not against them. Because in this new era, understanding the AI alongside you isn’t just advantageous — it’s essential.

Step into the future of work and learn how to collaborate with AI as your invisible colleague. Understand the psychology, ethics, and practical workflows that define human-AI teamwork.

Language: English | Format: Kindle Edition

👉 Buy the Kindle Edition Now for $19.99

Thank you for the reading.

My Journey: Demystifying Core Software Engineering Concepts

Seyhun Akyürek — Wed, 15 Oct 2025 11:58:50 +0000

I am representing a archetype of technology leader: one who combines two decades of experience delivering secure, scalable platforms for regulated enterprise banking with the agile, founder-level mindset required to pioneer cutting-edge AI solutions till 20 years of experience. My career demonstrates a strategic evolution from ensuring stability at scale to driving disruptive innovation.

This unique duality forms my core value proposition, positioning me as a leader who not only translates vision into production-ready reality but also builds the high-performance cultures necessary to sustain it.

Introduction: From First Code to Leading Teams
Welcome to a practical roadmap for aspiring developers. If you've ever wondered what separates writing a simple program from building a robust, real-world application, this guide is for you. We'll explore the essential pillars of modern software engineering by breaking down the core concepts that professionals use every day.
To make these ideas tangible, we'll draw on the experience of me a passionate developer to team leader with a knack for turning ideas into reality. Myjourney provides a perfect lens through which to understand how fundamental skills connect to create impactful technology.

My journey in tech has taken me from writing my first line of code to leading teams in building impactful digital products.

Before drafting about me
I recommend to read "The Manager's Code: Crafting Cultures of Engineering Excellence" by me, which is based on the twenty years of experience in software development and leadership. The book acts as a guide for engineering managers and leaders, focusing on principles required to cultivate high-performing software teams and achieve technical superiority. It systematically explores how to establish a values-driven engineering culture, design scalable and sustainable software architecture, and manage technical complexities, such as technical debt and codebase scaling.

Furthermore, the book details strategies for fostering engineering creativity within Agile processes, implementing continuous feedback loops and retrospectives, and scaling engineering excellence across an entire organization while balancing speed with long-term quality and meeting critical Service Level Agreements (SLAs).

Download from Amazon - Kindle version
The Manager's Code: Crafting Cultures of Engineering Excellence
This is the book basis from my past experience of crafting software and engineering with the proven excellence of…www.amazon.com

Gumroad
The Manager's Code: Crafting Cultures of Engineering Excellence Kindle Edition

This is the book basis from my past experience of crafting software and engineering with the proven excellence of…seyhunak.gumroad.com

About me

My primary areas of expertise include:

Product Strategy: Designing and executing AI-driven roadmaps that align with business outcomes - from ideation to scalable deployment.
Technical Leadership: Building and mentoring high-performance engineering teams with a focus on velocity, robust architecture, and strategic impact.

Systems Design: Architecting resilient, cloud-native platforms, from infrastructure to user experience, designed to serve millions of users reliably.

Leadership Philosophy and People Management: For any senior management position, my leadership style and ability to positively influence engineering culture are paramount. Technical skill alone is insufficient; my approach is to inspire, mentor, and create an environment where teams can thrive.

In this post, I will explore these four pillars - Agile (how I build), programming language(what I build with), DevOps (how I ship), and AI (what I build next) - using my journey to show how they connect to form the bedrock of a successful engineering career.

The 'How': Agile Methodologies for Building Better Software

What is Agile?
Agile is a modern approach to building software that emphasizes flexibility and collaboration. Instead of creating a rigid, long-term plan, Agile teams work in small, iterative cycles. This allows them to respond to change, get feedback early, and deliver value to users faster. This philosophy is brought to life through specific practices like Scrum, Extreme Programming (XP), and Test-Driven Development (TDD), all of which are key skills for modern engineering teams.

Agile in Action: A Real-World Impact
My major accomplisments are in roles of Mobile Chapter Lead at Azərbaycan Beynəlxalq Bank Cultural Transformation & Performance / Delivery and Team Leader role at Commercial Bank of Dubai exceled Enterprise Delivery & Stability

Agile isn't just a theory; it delivers measurable results. During time as he implementation done by Agile Office and Agile methodologies helped me to implement robust coding standards led to a dramatic turnaround in the engineering culture and product quality.

90% reduction in system outages through the implementation of new Change Advisory Board (CAB) and release protocols during my work in CBD - Commercial Bank of Dubai

100% on-time feature delivery for critical, high-volume digital banking applications.
30% increase in team productivity through process optimization.

Ensured full compliance with KYC, AML, ODD, and PCI DSS regulations across all digital channels.

I demonstrated ability to deliver mission-critical applications within a highly regulated financial environment. My leadership was pivotal in enhancing platform stability, ensuring compliance, and increasing team productivity scope of Personal Banking of Mobile Channels

Improved Quality
I rather focusing on best practices, the my teams boosted unit test coverage from a starting point of 0% to 76% in just 6 months then reached tip point. This means the code was more reliable and easier to maintain.

Enhanced Stability
I focus on quality directly impacted the user experience, elevating mobile app crash-free rates from a problematic 60% to an exceptional 99.9% within only 3 months.

Why This Matters for You (The "So What?")
For an aspiring developer, working in an environment means you're part of a collaborative team focused on writing high-quality, stable code. It's a system designed to help you and your team succeed by building the right thing, the right way, and delivering it to users quickly and reliably.

This disciplined methodology for how to build software naturally leads to the question of whatyou build it with.

Moving to Python's Power and Versatility
What is Python?

Python is a powerful, high-level programming language famous for its clean, readable syntax. It's often recommended for beginners but is also trusted by the world's largest companies for complex applications. Its versatility is its greatest strength, making it a go-to language for everything from web development and data science to artificial intelligence. Seyhun's profile highlights this, noting "Python and Django 90%" proficiency and foundational knowledge from Harvard's CS50 course.

Python in Action: From AI Platforms to Command-Line Tools
A look at my projects reveals just how broadly Python can be applied. It's not just for one type of task; it's a multi-purpose tool for solving different kinds of problems.

Crafted AI Framework: A multi-agent collaboration AI platform. - Python, Django, Redis, PostgreSQL, CrewAI, OpenAI, Azure OpenAI, AWS
Invy: An AI-powered stock analysis and trading assistant. Python, Yahoo Finance
Metd: A simple Command Line Interface (CLI) to dump and load Python functions to the cloud. - Python, Cloud Storage SDK

Why This Matters for You (The "So What?")
Learning a versatile language like Python opens up a vast landscape of opportunities. As these examples show, a single language can be your entry point into building complex AI systems, creating useful financial tools, or even developing simple utilities that make other developers' lives easier.

Once you've written the code, the next challenge is getting it into the hands of users efficiently and reliably.

The 'Where': DevOps for Faster, More Reliable Delivery
What is DevOps?

DevOps is a culture and set of practices that aims to shorten the development lifecycle and provide continuous delivery with high software quality. It breaks down the traditional silos between software development (Dev) and IT operations (Ops), enabling them to work together through automation.

Key technologies that power this culture include version control systems like Git, containerization with Docker, and cloud platforms like AWS and Azure. At the heart of DevOps is the CI/CD (Continuous Integration/Continuous Delivery) pipeline - an automated process that builds, tests, and deploys code whenever a change is made.
Think of the CI/CD pipeline as the automated assembly line for software. It takes raw code from a developer, runs it through automated quality checks and tests, and delivers the finished product to users, all without manual intervention.

DevOps in Action: Measurable Speed and Stability
The goal of DevOps is to make the process of releasing software faster, safer, and more predictable. Real-world metrics demonstrate its impact:

At Crafted, streamlining CI/CD processes using Docker and GitHub Actions reduced deployment time by 70%, allowing the team to deliver features and fixes much faster.

At ABB, the adoption of lean CI/CD practices reduced release cycles by 30% more, accelerating the time-to-market for new mobile banking features.

Why This Matters for You (The "So What?")
For a new developer, a strong DevOps culture is a huge advantage. It means you can spend more of your time focused on what you do best - building features and solving problems - and less time worrying about the complex, manual steps of deployment. It creates a safety net that ensures the code you ship is stable and reliable for users.

As the process of shipping software becomes more efficient, it enables teams to build and deploy more advanced technologies.
The 'Future': Artificial Intelligence in Modern Applications

What is AI in Software Today?
Today, Artificial Intelligence, especially Generative AI and Large Language Models (LLMs), is moving from a niche field to a core component of modern applications. Instead of just following pre-programmed rules, AI-powered software can understand language, generate content, and even collaborate on complex tasks.
My work as the "Crafted AI Framework" and deep focus on this domain - evidenced by advanced certifications in areas like Retrieval Augmented Generation with LangChain and Building GenAI Apps with Amazon Bedrock - highlights the shift of AI to a core engineering discipline.

AI in Action: Building Intelligent Tools
AI is not just an abstract concept; it's a tool being used to create entirely new kinds of user experiences and solve problems that were previously out of reach for software.

Crafted AI Framework: An advanced platform that allows businesses to build and run custom AI agents that collaborate on business processes.
MentorCraft: An AI-powered career simulator where users can practice real-world job tasks and get feedback from an AI mentor.
LetsTalk: An AI language tutor that enables users to have live, real-time speaking practicewith an AI tutor in over 30 languages. Why This Matters for You (The "So What?") Understanding the fundamentals of AI is becoming essential for the modern developer. It represents a powerful new toolkit for creating smarter, more helpful, and more personalized products. Learning how to integrate AI opens the door to working on the next generation of software and tackling some of the most interesting challenges in technology today.

Conclusion

Journey Ahead

I have covered four interconnected concepts that form the foundation of a modern software engineering career:
• Agile is how you work - collaboratively, iteratively, and with a focus on quality.
• Programming is an example of what you build with - a versatile tool for a huge range of applications.
• DevOps is how you ship - reliably and efficiently, through automation and teamwork.
• AI is the new frontier - a powerful capability for building the intelligent applications of the future.

Mastering these core areas is the key to building an impactful and rewarding career in technology. Just as my journey demonstrates, combining a strong methodology, versatile tools, efficient processes, and forward-looking technology is the formula for turning great ideas into reality.
The principles and tools are clear. Now it's your turn to start building.

Crafted AI Framework

Seyhun Akyürek — Tue, 14 Oct 2025 12:24:49 +0000

Hello, I’m Seyhun, a Senior Engineering Leader with 20+ years of experience building scalable platforms in fintech and banking. I’ve led globally distributed engineering teams, driving secure software development while championing AI, DevOps, CI/CD, XP, and TDD practices. I’m also the Founder of the Crafted AI Framework, empowering enterprises with orchestrated, agentic intelligence.

A Journey from Code to Crafted

Thanks for reading Seyhun's Substack! Subscribe for free to receive new posts and support my work.

I am introducing myself as a Senior Engineering Leader with deep expertise in fintech, banking, and artificial intelligence. In my Seyhun Akyürek Portfolio my trajectory has taken him from hands-on software work (front-end, back-end, mobile) to steering teams, shaping strategy, and defining how AI agents can be embedded into business workflows.

My skill profile is broad: modern web stacks. AI/ML technologies, backend systems (Python, Django, PostgreSQL, Redis), DevOps & cloud. I emphasizes leadership competencies: guiding cross-functional teams, aligning business and tech goals, and creating high-impact delivery models

The Crafted AI Framework: A Platform for Agentic Intelligence

Crafted AI Framework founded multi-agent collaboration AI platform that leverages LLMs (large language models), and other cutting-edge technologies. The vision: let businesses assemble, deploy, and orchestrate AI agents tailored to their processes. In effect, it’s a platform that not only encapsulates AI models, but gives them structure, coordination, and operational capability.

Some key facets worth highlighting:

Agent orchestration & collaboration: Rather than isolated models, the system enables agents to interact and cooperate.
Scalable architecture: It’s built to handle enterprise scale, with robust infrastructure and orchestration layers.
Domain specialization: While generically useful, Crafted is especially positioned to solve problems in fintech, banking, and business operations.

Integration with AI stacks: The platform leverages few LLM models, and related tools to harness the latest in AI capabilities.
There is a roadmap ahead: more plug-and-play domain agents (e.g. for compliance, risk, customer support), tighter integrations with enterprise systems (ERP, CRM, core banking), monitoring & governance infrastructure, and emergent behaviors via agent networks.

Highlighted Projects & Innovation Themes

Beyond Crafted, my portfolio reflects ambitious, real-world work:

Vibe: A real-time alerting & notification app built with Flutter and Firebase
MentorCraft: An AI-driven simulator for real job roles, enabling users to simulate decisions, tasks, and communications.
LetsTalk: A language tutor using voice AI, enabling live conversational practice.
Invy: An AI-powered stock analysis & trading assistant. Seyhun Akyürek Portfolio
These projects reinforce recurring themes in Seyhun’s work: real-time systems, AI augmentation, domain orientation, and a drive to deliver tools people can use directly.

I published books such as AI for Fintech with Crafted AI Framework (2024) and Modern Fintech & Banking Transformation. My writing signals a commitment not just to building, but to sharing theory, frameworks, and best practices.

Forward-Looking Lens: What Comes Next?

My orientation and his existing momentum, here’s how I anticipate his trajectory (and broader trends) will unfold — a “forward-thinking” preview:

Vertical AI Agents for Banking & Finance
As regulation, risk, and domain specificity matter heavily in banking, crafted agents specialized in compliance, fraud detection, risk scoring, and customer onboarding will likely emerge. The framework could evolve into a marketplace of certified agents for financial institutions.

Embedded Autonomy in Enterprise Workflows
Rather than AI as a separate add-on, Crafted might push toward deeply embedded autonomy: agents that are triggerable from inside CRMs, core systems, data pipelines, and ERP systems. That way business logic and AI behavior work in tight harmony.

Governance, Explainability, & Safety
As agentic systems grow more powerful, oversight becomes crucial. I expect extensions for audit trails, safe fallback behaviors, model versioning, human-in-the-loop control, and counterfactual explanations to be prioritized.

Cross-Agent Emergence & Ecosystem Effects
Multi-agent systems can generate emergent behaviors when agents interact. If designed well, this could lead to agent ecosystems where new capabilities arise from interactions, rather than each agent being hand-engineered in isolation.
AI as Organizational Fabric

Over time, AI agents may become a core operating fabric in companies rather than point tools. Teams might deploy agent fleets that enforce policies, manage processes, monitor anomalies, and accelerate execution — akin to “digital crew members” inside organizations.

Given base in Dubai / UAE and my work in fintech, there’s scope to partner across regions (ME, Asia, Africa) where banking transformation is accelerating. Also opportunities to collaborate on open standards for agent interoperability.

Why this Story Matters

My arc is emblematic of a new generation of technologists: blending domain fluency (banking/fintech), engineering rigor, leadership, and AI. The Crafted AI Framework is his bet on where the frontier lies — not in isolated AI models, but in structured, orchestrated, agentic intelligence that plugs into business.

For those building in AI, this is fertile ground. The questions his work is raising — how to coordinate agents, how to govern them, how to scale them in regulated systems — are among the most important in the next phase of AI adoption.

Crafted AI Framework Introducing new Feature "Instruct"

Seyhun Akyürek — Thu, 04 Sep 2025 09:43:11 +0000

When we launched the Crafted AI Framework, our mission was clear: Deploy intelligent agents at scale with speed, security, and flexibility.

What it is: “Instruct” is a task-driven mode where you tell the agent what to do, and it executes with structured reasoning and tools — no manual routing.

Instead of asking for raw answers, you give an instruction (e.g., “Audit my landing page for CRO improvements”), and the agent breaks it into steps, runs audits, merges outputs, and returns an actionable report.

🔑 How It Works
Instruction Capture — You send an input (via Crafted AI Framework with CopilotKit, using our API).
Agent Reasoning — The AI determines what steps are needed (e.g., scrape → analyze → recommend) and decide to use N8N workflow which fits.
Auto Tool Routing — N8N + Crafted Layer automatically call the right nodes by selecting workflow.
Result Formatting — Outputs are merged, cleaned, and delivered as structured recommendations.

⚡ Why It’s Powerful
Socratic reasoning → AI questions assumptions before acting.
Consistent outputs → Results follow templates (Analysis + Recommendations).
Autonomous orchestration → No need to predefine toolchains manually.
Reusable patterns → Same flow works for SEO audits, fraud detection, incident triage, etc.

🎯 Use Case — Landing Page CRO + SEO Agent
When if you ask:
“Please analyze my landing page to suggest improvements for conversion rate optimization and explain how it works.”
Here’s how the Crafted AI Framework + N8N + CopilotKit makes it happen.

⚡ The Flow
🔹 Webhook — Captures the request with landing page URL.
🔹 Scrapes Website — Extract HTML + content.
🔹 Technical Audit (Agent) — On-page SEO checks (critical issues, quick wins, improvements).
🔹 Content Audit (Agent) — Content quality, keyword analysis, readability, recommendations.
🔹 Merge + Aggregate — Combine both audits.
🔹 Markdown → HTML — Clean, formatted output.
🔹 Format Output → HTTP Request — Deliver result to Crafted AI agent interface in realtime using SSR

🖼 Demo Screenshots

👉 Screenshot 1: N8N Workflow (visual pipeline of nodes)

👉 Screenshot 2: Agent Output in CopilotKit (audit report nicely formatted)

👉 Screenshot 3: Rendered markdown (landing page snippet + recommendations applied)

🧠 How It Works Behind the Scenes

Crafted AI Layer → Provides reasoning + audit prompts with gpt-oss models.
N8N Orchestration → Automates data collection, flow execution, and merging.
CopilotKit Frontend → Displays results in a chat-style interface for end-users.
Vector DB (Redis + FAISS) → Stores past audits for trend analysis + reuse.

🚀 Why This Matters
Automated, expert-level audits in minutes
Actionable, structured output (critical issues, quick wins, opportunities)
Works across any website URL with zero manual setup
Ready to plug into customer-facing support bots or internal SEO teams

✅ Kickoff Action
Type /kickoff to spin up your own Landing Page CRO + SEO Audit Agent or any kind of agents you may instruct to run.

Plans for Everyone

Starter ($49/month): Ideal for solo developers and small teams.
Standard ($99/month): Priority support and integration features for scaling teams.
Enterprise ($499+): Custom dev, SLA, and premium onboarding.

Get Started Now

→ Start Free Trial — Deploy your first vector database in minutes with Crafted AI Framework
→ Explore Crafted AI Framework — Power agents with built-in intelligence and our vector DB is bundle and free-of-charge instance.
→ Talk to Sales — Enterprise use case? Custom integrations? We’ve got you
→ View on Toolify — Discover and share how you use it
→ Support on Product Hunt — Show love, leave feedback, and join our launch
→ Contact Us — Questions or partnership inquiries? Let’s connect

Built with ❤️ by the Crafted

Unlock Your Professional Potential with AI using MentorCraft

Seyhun Akyürek — Sun, 20 Jul 2025 11:05:40 +0000

MentorCraft is your personal career training companion, offering realistic, AI-powered simulations for roles whether you’re preparing for interviews or building real-world skills, MentorCraft provides intelligent guidance anytime you need it.

MentorCraft is your personal career training companion, offering realistic, AI-powered simulations for roles such as Digital Lead, Cloud Architect, Cybersecurity Analyst, and 100+ professional AI mentors that are ready to boost your skills. Whether you’re preparing for interviews or building real-world skills, MentorCraft provides intelligent guidance anytime you need it.

AI-Powered Conversations
Engage with virtual mentors who offer industry-specific insights and realistic dialogue tailored to your selected role.

Choose Your Role
Explore a variety of career paths including:
AI Product Manager
Sales Director
Cybersecurity Analyst
Cloud Architect
And 100+ more mentors

Multiple Training Modes
Professional Chat: Learn about roles, industry trends, and strategies
Mock Interviews: Practice responding to real interview questions
Work Scenario Simulations: Solve realistic on-the-job challenges
Email Writing Simulations: Improve your professional communication
Decision-Making Drills: Practice critical thinking under pressure
Case Study Challenges: Analyze and present solutions effectively

Track Your Progress
Review your session history and receive role-specific feedback to help you grow over time.

Free Plan — Includes up to 25 AI chats maximum.
Pro Plan — Includes all in free plan and unlocks un-limited chat sessions with a subscription.

Download free today View on App Store https://apps.apple.com/us/app/mentorcraft/id6748411626

Effects in long term of AI Technology and Impact of Software Development Industry

Seyhun Akyürek — Sat, 26 Oct 2024 15:37:42 +0000

By Seyhun Akyurek — 26/Oct/2024

Table of Contents
Summary
Historical Context
Long-term Effects of AI Technology
Economic Growth and Productivity
Labor Market Dynamics
Challenges and Policy Considerations
Impact on Software Development Industry
AI-Driven Development Practices
Changing Roles and Skills
Long-term Economic Implications
Future Projections
Economic Shifts
Technological Integration
Workforce Evolution
Challenges and Considerations

Summary
Artificial Intelligence (AI) technology is transforming industries worldwide, with profound long-term effects anticipated in the software development sector and broader economic landscape. Since the term was coined in 1955, AI has evolved from a theoretical concept to a pivotal driver of innovation and efficiency, especially in software development practices. With advancements in generative models and automated processes, AI is significantly enhancing productivity, enabling organizations to optimize workflows and improve software quality while potentially tripling its economic impact by 2030.[1][2][3].

AI’s integration into the software development lifecycle is reshaping job roles and skill requirements. Traditional coding tasks are increasingly automated, leading to the emergence of new roles, such as prompt engineers, who facilitate interactions with AI tools. However, this shift raises concerns about job displacement, particularly for roles focused on routine tasks, which could exacerbate income inequality and polarize the labor market.[4][5][6].
While AI is set to enhance overall productivity, the dual nature of its impact necessitates careful consideration of workforce implications and the need for ongoing education and re skilling initiatives.[4][7].

Moreover, the ethical and regulatory challenges posed by AI’s rapid adoption underscore the importance of public discourse around its societal implications. Policymakers are tasked with ensuring that the benefits of AI are equitably distributed while addressing potential harms associated with its deployment, including privacy and security concerns.[8][9]. As AI continues to evolve, its long-term effects on the software development industry and broader economy will require ongoing analysis and proactive measures to foster a sustainable and inclusive future.[10][9].

Historical Context
Artificial intelligence (AI) has evolved significantly since its inception in the mid-20th century. The term “artificial intelligence” was first coined in 1955 by computer scientist John McCarthy[1]. Over the decades, AI research has undergone numerous shifts in focus and methodology, leading to breakthroughs that have transformed various industries, including software development.

The last decade has seen an unprecedented acceleration in AI technology, characterized by the development of innovative frameworks like generative adversarial networks and large language models (LLMs) like ChatGPT[1][2]. These advancements have made it possible for AI to perform complex tasks such as automating code generation, optimizing testing, and even creating real-time historical simulations for educational purposes[11][12][2].

In the context of software development, AI has begun to reshape traditional practices by improving productivity and driving innovation. According to a Gartner report, nearly half of organizations are now experimenting with AI in their development processes, highlighting its growing impact on efficiency and code quality[12].

Furthermore, a McKinsey study indicates that AI could enhance productivity in software development by up to 40%[12].
This historical trajectory illustrates a shift from AI being viewed merely as a theoretical concept to becoming an integral part of everyday applications. AI technologies, such as virtual assistants and autonomous systems, have now permeated various sectors, including healthcare, finance, and manufacturing, underscoring the technology’s versatility and transformative potential[13][14].
The integration of AI into the software development lifecycle is not merely a trend but a fundamental change that reflects deeper understanding of how technology can drive progress and innovation in the industry[2][15].

Long-term Effects of AI Technology
The long-term effects of artificial intelligence (AI) technology are expected to be profound and multifaceted, impacting economic growth, labor markets, and societal structures. As AI continues to develop, its contributions to productivity and economic activity are likely to build up significantly over time, potentially tripling by 2030 compared to its current impact. This pattern resembles an S-curve, where initial slow adoption gives way to rapid acceleration as firms and sectors increasingly integrate AI into their operations[4][3].

Economic Growth and Productivity
AI is poised to play a crucial role in addressing the challenges of low productivity growth that have plagued many advanced economies for decades. By augmenting the capabilities of workers and enabling more efficient processes, AI technologies
could lead to a notable increase in output per unit of input. The

McKinsey Global Institute projects that global economic activity could see an additional $13 trillion by 2030, representing a 16% increase in cumulative GDP compared to current levels[3]. This economic boost can make addressing social issues, such as poverty and healthcare, more manageable, thereby improving living standards overall[5].

Labor Market Dynamics
While AI has the potential to create new job opportunities, it may also lead to significant disruptions in the labor market. The transition to AI may widen the gap between countries, companies, and workers, leading to uneven distribution of economic benefits. Jobs that involve routine tasks are at high risk of being automated, which could increase income inequality and polarize the labor market into high-skilled elites and low-paying service jobs[4][5].
Historical trends suggest that new jobs generated by AI could lead to a net employment increase of about 5% by 2030, while total productivity gains could contribute positively to employment by around 10%[4].

Challenges and Policy Considerations
The transition to an AI-driven economy poses several challenges, including the need for skilling and re-skilling workers to adapt to new job requirements. Policymakers must take bold actions to mitigate the discomfort associated with job displacement due to automation. This involves creating frameworks for education and training that equip individuals with the skills necessary to thrive in a rapidly changing job landscape[4][7].

Additionally, societal understanding of AI’s dual-use nature — its potential for both beneficial and harmful applications — requires ongoing public discourse and regulatory measures. The ethical deployment of AI technologies will be essential in shaping their long-term effects on society[8].

Impact on Software Development Industry
The advent of artificial intelligence (AI) has fundamentally transformed the software development industry, shaping its practices, tools, and workforce dynamics. As AI technologies continue to evolve, their influence is expected to expand further, leading to significant changes in how software is designed, built, and maintained.

AI-Driven Development Practices
AI’s integration into software development has ushered in several innovative practices. One notable trend is automated code generation, where AI models can interpret written descriptions and produce functional code autonomously. This shift reduces reliance on manual coding and allows developers to focus on higher-level design and architectural tasks[16]. Additionally, smarter bug detection tools are now prevalent, employing AI algorithms to analyze code for potential vulnerabilities before deployment, which enhances software reliability and security[16].

The DevOps movement, which emphasizes collaboration between development and operations teams, has also been bolstered by AI. With tools that facilitate Continuous Integration (CI) and Continuous Delivery (CD), AI aids in automating testing and deployment processes, enabling faster software delivery without compromising quality[17]. This streamlined approach supports organizations in meeting rapid market demands.

Changing Roles and Skills
As AI technologies become more integrated into the development process, the roles within software teams are also evolving. Traditional positions such as requirements engineers are now complemented by emerging roles like prompt engineers, who specialize in crafting queries and commands that guide AI systems to achieve desired outcomes[6]. This change necessitates new skills, as developers must now balance coding expertise with the ability to communicate effectively with AI tools.

Moreover, while AI can assist with routine tasks, complex problem-solving, creativity and ethical considerations still require human oversight.

Software engineers are tasked with ensuring that the products remain ethical, compliant, and free of bias emphasizing the importance of human judgment in AI-enhanced environments[18].

Long-term Economic Implications
The long-term economic impact of AI on the software development industry is profound. The demand for software developers is projected to grow significantly, fueled by the increasing digitization of various sectors and the rising need for sophisticated software solutions[19]. As AI drives down certain operational costs and automates routine tasks, organizations can allocate resources more efficiently, potentially increasing the overall demand for skilled developers.

However, the widespread adoption of AI tools presents challenges, such as the risk of job displacement for certain roles. While routine tasks may become automated, the demand for creative, strategic, and complex problem-solving capabilities remains high, ensuring that software development careers continue to evolve rather than vanish[18][16].

Future Projections
The trajectory of artificial intelligence (AI) technology indicates significant changes across various sectors, particularly in software development and the broader work-force. As organizations increasingly adopt AI, the landscape of employment and productivity is poised for transformation.

Economic Shifts
Over the past few decades, the growth in the global workforce has shown a marked decline, influenced by factors such as aging populations and evolving job requirements. Between 2012 and 2022, the compound annual growth rate in employment fell to just 0.8% compared to 2.5% from 1972 to 1982[20]. This decline coincides with slowing productivity growth, which had previously driven economic expansion.
Projections suggest that between a quarter and a third of work activities could undergo significant changes within the next decade as companies integrate AI into their operations[20].

Technological Integration
The pace of AI advancement has led to its widespread incorporation into daily life and industry. From virtual assistants to applications in healthcare and finance, AI’s capabilities continue to expand[13]. Generative AI, in particular, is anticipated to revolutionize software development, enhancing productivity and innovation[12].
Current tools, like GitHub Copilot and IBM Watson Code Assistant™, exemplify how AI is streamlining coding processes, reducing errors, and expediting development timelines[2].

Workforce Evolution
As AI becomes increasingly integral to business operations, the demand for skilled professionals who can harness AI technologies is on the rise. The ability to understand and apply AI tools will likely create diverse career pathways ranging from AI ethics to advanced programming roles[13]. Educational institutions will need to adapt their curriculums to ensure students are well-equipped with both technical and soft skills necessary for an AI-enhanced workforce[13][12].

Challenges and Considerations
While the benefits of AI integration are substantial, several challenges remain. The Gartner Hype Cycle positions Generative AI at the “Peak of Inflated Expectations,” suggesting an impending transition into a phase of disillusionment as organizations grapple with its limitations and the real-world impacts of these technologies[10].
Furthermore, responsible development and deployment of AI systems is critical, as concerns about privacy, security, and ethical implications continue to mount[9].

References
[1]: Modern AI evolution timeline shows a decade of rapid progress
[2]: AI in Software Development — IBM
[3]: Preparing Students and Teachers for a Future with AI
[4]: AI in Software Development: A Comprehensive Guide — Scaler
[5]: Preparing Students For A Tech-Driven World — The Importance Of AI …
[6]: How AI impacts software development | Google Cloud Blog
[7]: The Growing Impact of AI on Software Development | Adeva
[8]: Modeling the global economic impact of AI | McKinsey
[9]: How Will Artificial Intelligence Affect Jobs 2024–2030
[10]: The Macroeconomics of Artificial Intelligence — IMF
[11]: Ethical concerns mount as AI takes bigger decision-making role
[12]: The brief history of artificial intelligence: the world has changed …
[13]: Requirements and Prompt Engineering in AI-Driven Software Development
[14]: Charting the Roadmap: Top 10 Software Development Trends Shaping 2024
[15]: Unleashing developer productivity with generative AI — McKinsey & Company
[16]: How Will AI Affect Software Development? — Beetroot
[17]: How AI-powered software development may affect labor markets — Brookings
[18]: Economic potential of generative AI | McKinsey — McKinsey & Company
[19]: The Top Artificial Intelligence Trends — IBM
[20]: AI Index Report 2024 — Artificial Intelligence Index

Book: Mastering Financial APIs: Building Advanced Trading Systems and Integrating Modern Banking Solutions

Seyhun Akyürek — Sat, 12 Oct 2024 16:37:06 +0000

In today's rapidly evolving financial landscape, the demand for advanced trading technologies has never been greater. I decided to write and designed picture for aspiring traders, software developers, and financial professionals whom are looking to deepen their understanding of the architecture and technologies that underpin successful trading platforms.

Subjects are starting from algorithmic trading to the integration of machine learning, decentralized finance (DeFi), and open banking solutions, this book covers a wide array of topics essential for constructing high-performance trading systems.

Each chapter delves into the critical components of trading technologies, offering practical insights, case studies, and hands-on examples that equip readers with the skills to build and scale their own trading applications.

As the finance industry continues to embrace digital transformation, mastering these concepts will be crucial for anyone seeking to navigate the complexities of modern trading. Whether you're building a retail trading app or designing institutional-grade systems, this book serves as your roadmap to success in the dynamic world of trading technology.

This book, "Mastering Financial APIs" (in short) provides a comprehensive guide to building and integrating advanced financial systems using APIs. It covers a wide range of topics, from understanding different API types and standards to implementing stock trading systems, algorithmic trading strategies, options trading integration, and building brokerage services. The book also explores the use of machine learning and AI in trading, high-performance trading systems, institutional-grade trading systems, banking-as-a-service (BaaS) platforms, real-time payments and digital wallets, DeFi, and blockchain-based banking.

Book to be available on Amazon Kindle and Apple Books, by the time you match catch up about the book within podcast from the SoundCloud.

https://on.soundcloud.com/nxZBrnDRqQfokMo78

Here you may find the link from Amazon to get the book.

https://www.amazon.com/dp/B0DJZ7J1LZ/ref=sr_1_1?crid=3Q0PUOWNDH4Q7&dib=eyJ2IjoiMSJ9.6GtTSbC9m4xZYS1J4OGYjUSSoRkAxYSFeVRK-eU_xMWLV-GPjpsUXeMoZJnFMVye.PBiKY8a5JFOCfnJsO2Q_8_mYC53Pfap7ueIdgLGGNL0&dib_tag=se&keywords=Mastering+Financial+APIs%3A&qid=1728814271&sprefix=mastering+financial+apis+%2Caps%2C296&sr=8-1

Thank you

Book: The Manager’s Code: Crafting Cultures of Engineering Excellence.

Seyhun Akyürek — Mon, 30 Sep 2024 14:46:15 +0000

This book explores how to create and maintain a culture of engineering excellence within software development teams, even as organizations grow and face new challenges. The book argues that technical expertise alone is not enough; success relies on a multifaceted approach that balances technical practices, strong leadership, clear communication, and a commitment to continuous improvement.

My book published and shortly to be available on Amazon.com on sale as ePUB and Amazon Kindle readers.

Here please find some of the key themes and takeaways from the book:

Engineering Excellence Begins with Culture: The book emphasizes that a strong engineering culture is the foundation for building high-performing teams and delivering high-quality software. [1, 2] This involves fostering collaboration, embracing accountability, encouraging continuous learning, and creating a safe space for experimentation and risk-taking. [2–5]

Architecting for Success: A well-designed and scalable architecture is crucial for long-term success. [6, 7] The book highlights principles like modularity, separation of concerns, and loose coupling as essential for building maintainable and flexible systems. [8, 9]

It also stresses the importance of balancing the adoption of cutting-edge technologies with maintainability and long-term support. [10]

Scaling Codebases with Elegance: As codebases grow, managing complexity and technical debt becomes critical. [11] The book recommends strategies like Gitflow for branch management, continuous integration and continuous delivery (CI/CD) for automating testing and deployment, and modular code architecture for creating reusable and maintainable components. [12–15]

Fostering Engineering Creativity: Innovation thrives in environments where engineers feel safe to experiment and take risks. [16] The book explores ways to encourage experimentation, integrate innovation into agile processes, and create a culture where failure is seen as a learning opportunity. [17–20]

Building High-Performance Engineering Teams: The book outlines the characteristics of high-performing teams, such as shared vision, strong collaboration, autonomy with accountability, and a commitment to continuous learning. [21–23]

It also provides guidance on leadership techniques to foster these qualities, emphasizing the importance of leading by example, empowering decision-making, and providing continuous feedback. [24–27]

Driving Excellence with Feedback and Retrospectives: Continuous feedback and regular retrospectives are essential for ongoing improvement. [28, 29] The book encourages creating a feedback-driven culture, using structured feedback frameworks, and leveraging data to make informed decisions. [29–32]

Scaling Engineering Excellence: As organizations grow, maintaining engineering excellence requires a deliberate approach to scaling leadership, processes, communication, and culture. [33, 34] The book recommends establishing clear engineering principles, standardizing development processes, building a scalable architecture, and empowering autonomous teams. [34–37]

Building a Legacy of Engineering Excellence: This involves aligning engineering efforts with business demands while maintaining high standards of quality and reliability. [38, 39] The book emphasizes the importance of engaging early with product and business teams, managing production incidents effectively, meeting service level agreements (SLAs), and implementing a robust Quality Assurance (QA) process. [40–43]

The book aims to provide engineering managers, leaders, and teams with practical strategies and real-world examples to navigate the complexities of modern software development and establish a lasting culture of engineering excellence. [44, 45]

Podcast about the my new book in summary available for listening.

Thank you.

Understanding In-App Provisioning and Digital Tokenization with Visa

Seyhun Akyürek — Sat, 28 Sep 2024 11:27:52 +0000

In-app provisioning and digital tokenization are two crucial concepts in the realm of mobile payments, and Visa, a leading payment technology company has developed innovative solutions to facilitate these processes.

In this explanation, I will dive into the world of in-app provisioning and digital tokenization, exploring their significance, benefits and how Visa's solutions can enhance the mobile payment experience.

In-App Provisioning

In-app provisioning is the process of adding a digital card to a mobile wallet, such as Apple Pay, Google Pay, or Samsung Pay, directly from app. This process enables users to easily add their credit or debit cards to their mobile wallets, allowing them to make contactless payments online or in-store. Visa offers two solutions to facilitate in-app provisioning: Visa Digital Enablement SDK and Visa In-App Provisioning API.

Visa Digital Enablement SDK

The Visa Digital Enablement SDK is a software development kit that enables developers to integrate in-app provisioning capabilities into their mobile apps. This SDK provides a seamless and secure method for cardholders to pass their credentials from the app to the digital wallet, eliminating the need to enter card information separately. The SDK supports both iOS and Android platforms and is designed to reduce the complexity and expense of multiple integration efforts for mobile app providers.

Visa In-App Provisioning API

The Visa In-App Provisioning API is a RESTful API that enables developers to generate an encrypted card data payload that can be passed to Apple Pay, Google Pay, or Samsung Pay for tokenization. This API eliminates the need for backend software development complexity and expensive server infrastructure to store encryption keys. The API provides a secure and efficient way to provision digital cards to mobile wallets, reducing the time and effort required for integration.

Digital Tokenization

Digital tokenization is the process of replacing sensitive card information, such as the primary account number (PAN), with a unique digital identifier, known as a token. This token is used to identify the cardholder and facilitate transactions, ensuring that sensitive information is not exposed. Visa Token Service (VTS) is a tokenization platform that enables the creation, management, and distribution of tokens.

Visa Token Service (VTS)

VTS is a cloud-based tokenization platform that provides a secure and scalable way to manage tokens. The platform enables issuers, acquirers, and merchants to tokenize card information, reducing the risk of fraud and improving the overall payment experience. VTS supports multiple tokenization schemes, including EMVCo, and is compatible with various payment systems, including Apple Pay, Google Pay, and Samsung Pay.

Benefits of In-App Provisioning and Digital Tokenization

The combination of in-app provisioning and digital tokenization offers several benefits, including:

Enhanced security: Tokenization replaces sensitive card information with a unique digital identifier, reducing the risk of fraud and data breaches.
Improved user experience: In-app provisioning enables users to easily add their cards to mobile wallets, streamlining the payment process.
Increased adoption: By simplifying the provisioning process, more users are likely to adopt mobile payments, driving growth and revenue for merchants and financial institutions.
Reduced complexity: Visa's solutions reduce the complexity and expense of multiple integration efforts, making it easier for developers to implement in-app provisioning and digital tokenization.

How Visa Offers Two Ways to Include In-App Provisioning in an App

As we discussed earlier, in-app provisioning is the process of adding a digital card to a mobile wallet, such as Apple Pay, Google Pay, or Samsung Pay, directly from app. Visa, a leading payment technology company, provides two solutions to facilitate in-app provisioning: Visa Digital Enablement SDK and Visa In-App Provisioning API.

How Visa Digital Enablement SDK Works

The Visa Digital Enablement SDK is a software development kit that enables developers to integrate in-app provisioning capabilities into their mobile apps. This SDK provides a secure and seamless method for cardholders to pass their payment credentials from the client's mobile application to the mobile or digital wallet of their choice, eliminating the need to enter their payment credentials separately.

The SDK manages integration with wallet APIs, such as Apple Pay, Google Pay, and Samsung Pay, and performs the required "Pay" Token Eligibility validations. It also encrypts the card using the Visa In-App Provisioning API, removing the need for the mobile app provider to interface directly with the "Pays" to provision a card directly from their app.

Visa In-App Provisioning API

The API provides a secure method for cardholders to provision their cards to mobile wallets, reducing the risk of fraud and improving the overall payment experience. It is the client's responsibility to build and maintain direct integration with multiple wallet APIs to perform eligibility checks and securely pass the encrypted payload to them.

Regional Availability

The Visa In-App Provisioning SDK and API are available in various regions, including North America, Asia-Pacific, Europe, CEMEA, and LAC. The regional availability may vary depending on the specific product and service.

Implementation

To implement in-app provisioning, developers can use the Visa Digital Enablement SDK or Visa In-App Provisioning API. The SDK is designed to be embedded within the mobile application(s) by the team responsible for the mobile app development, which may be the client or a party licensed by the client to provide their mobile solution.

The API, on the other hand, requires the client to build and maintain direct integration with multiple wallet APIs to perform eligibility checks and securely pass the encrypted payload to them.

The provided Mermaid sequence diagram illustrates the step-by-step process of implementing in-app provisioning using Visa's solutions within a mobile application. This process enables a user to add their payment card to a mobile wallet (such as Apple Pay, Google Pay, or Samsung Pay) directly from their app securely and efficiently. Below is a detailed explanation of each component and interaction in the diagram.

Participants in the Diagram

User: The individual who wishes to add their payment card to a mobile wallet using their app.
Application: The mobile application provided by the user's financial institution.
VisaSDK (Visa SDK/API): Represents Visa's Digital Enablement SDK or In-App Provisioning API used within the app to facilitate secure card provisioning.
MobileWallet: The digital wallet application (Apple Pay, Google Pay, or Samsung Pay) where the user wants to add their card.
VisaVTS (Visa Token Service): Visa's cloud-based tokenization platform that handles the creation and management of payment tokens.

How Apple, Samsung, and Google Wallets Work with Visa Enablement SDK

As we discussed earlier, Visa Enablement SDK is a software development kit that enables developers to integrate in-app provisioning capabilities into their mobile apps. This SDK provides a secure and seamless method for cardholders to pass their payment credentials from the client's mobile application to the mobile or digital wallet of their choice, eliminating the need to enter their payment credentials separately.

Apple Wallet (Apple Pay)

Apple Wallet, also known as Apple Pay, is a mobile payment and digital wallet service by Apple Inc. that allows users to make payments using their iPhone, Apple Watch, iPad, or Mac. To integrate Apple Wallet with Visa Enablement SDK, developers can use the Visa In-App Provisioning API to generate an encrypted card data payload that can be passed to Apple Wallet for tokenization.

The Visa In-App Provisioning API provides a secure method for cardholders to provision their cards to Apple Wallet, reducing the risk of fraud and improving the overall payment experience. The API eliminates the need for backend software development complexity and expensive server infrastructure to store encryption keys.

Samsung Wallet (Samsung Pay)

Samsung Wallet, also known as Samsung Pay, is a mobile payment service by Samsung Electronics that allows users to make payments using their Samsung Galaxy devices. To integrate Samsung Wallet with Visa Enablement SDK, developers can use the Visa In-App Provisioning API to generate an encrypted card data payload that can be passed to Samsung Wallet for tokenization.

The Visa In-App Provisioning API provides a secure method for cardholders to provision their cards to Samsung Wallet, reducing the risk of fraud and improving the overall payment experience. The API eliminates the need for backend software development complexity and expensive server infrastructure to store encryption keys.

Google Wallet (Google Pay)

Google Wallet, also known as Google Pay, is a digital wallet service by Google LLC that allows users to make payments using their Android devices. To integrate Google Wallet with Visa Enablement SDK, developers can use the Visa In-App Provisioning API to generate an encrypted card data payload that can be passed to Google Wallet for tokenization.

The Visa In-App Provisioning API provides a secure method for cardholders to provision their cards to Google Wallet, reducing the risk of fraud and improving the overall payment experience. The API eliminates the need for backend software development complexity and expensive server infrastructure to store encryption keys.

How it Works

The process of integrating Apple Wallet, Samsung Wallet, or Google Wallet with Visa Enablement SDK involves the following steps:

The user initiates the provisioning process from within the mobile app.
The Visa In-App Provisioning API generates an encrypted card data payload that can be passed to the wallet of choice (Apple Wallet, Samsung Wallet, or Google Wallet).
The encrypted payload is passed to the wallet, which then tokenizes the card information.
The tokenized card information is stored securely in the wallet, eliminating the need for the user to enter their payment credentials separately.

Conclusion

In conclusion, Visa offers two ways to include in-app provisioning in an app: the Visa Digital Enablement SDK and the Visa In-App Provisioning API. Both solutions provide a secure and efficient way to facilitate in-app provisioning, reducing the complexity and expense of multiple integration efforts for mobile app providers.

By understanding the benefits and mechanisms of these solutions, developers, financial institutions, and merchants can create a seamless and secure payment experience for users, driving growth and innovation in the mobile payment industry.

Key Takeaways

Visa offers two solutions for in-app provisioning: Visa Digital Enablement SDK and Visa In-App Provisioning API.
The SDK provides a secure method for cardholders to pass their payment credentials to mobile wallets, eliminating the need to enter their payment credentials separately.
The API generates an encrypted card data payload that can be passed to Apple Pay, Google Pay, or Samsung Pay for tokenization.
Both solutions reduce software development complexity, eliminate encryption key management costs, and improve the user experience.
The regional availability of the SDK and API may vary depending on the specific product and service.
In-app provisioning enables users to add their cards to mobile wallets directly from apps.
Digital tokenization replaces sensitive card information with a unique digital identifier, reducing the risk of fraud and data breaches.
Visa's solutions, including the Visa Digital Enablement SDK and Visa In-App Provisioning API, provide a secure and efficient way to facilitate in-app provisioning and digital tokenization.
The combination of in-app provisioning and digital tokenization offers several benefits, including enhanced security, improved user experience, increased adoption, and reduced complexity.

Buy Now, Pay Later (BNPL) - How It Works, Benefits and Design

Seyhun Akyürek — Sat, 13 Jul 2024 07:55:37 +0000

Buy Now, Pay Later (BNPL) is a form of digital lending. BNPL services offer customers a way to finance their purchases by splitting the cost into smaller, manageable installments, typically without requiring an upfront payment. This digital lending model involves assessing the customer’s creditworthiness, approving the loan, and managing repayments, all through online or mobile platforms. BNPL leverages digital technology to provide a seamless and convenient borrowing experience, making it a subset of the broader digital lending ecosystem.

Buy Now, Pay Later (BNPL in short) services provide a convenient payment option for customers, allowing them to make purchases and pay for them over time.

Here’s a detailed breakdown of how BNPL works, I like to explain in step by step both in business and technical perspective.

Journey

Customer Makes a Purchase

The process begins when a customer selects items they want to purchase and proceeds to the checkout on a merchant’s website or physical store. At the checkout stage, the merchant offers BNPL as one of the payment options. The customer then selects the BNPL option to split the cost into manageable installments.

Customer Signs Up or Signs In

Once the BNPL option is selected, the customer is prompted to sign up for the BNPL service if they don’t already have an account, or to sign in if they do. Signing up involves providing personal information and agreeing to the terms and conditions of the service. This step ensures that the service provider has the necessary details to perform credit and identity checks.

Instant e-KYC and Credit Risk Analysis

To ensure the customer’s eligibility, the BNPL service provider performs an instant electronic Know Your Customer (e-KYC) verification and credit risk assessment. This involves checking the customer’s identity and evaluating their creditworthiness based on various data points, including credit history and financial behavior. This step is crucial for minimizing the risk of defaults.

Approval and Payment

Based on the results of the e-KYC and credit risk analysis, the BNPL service provider decides whether to approve the transaction. If approved, the BNPL provider pays the merchant on behalf of the customer, allowing the customer to complete the purchase without paying the full amount upfront. This immediate payment to the merchant helps ensure a smooth transaction and quick delivery of goods.

Product Delivery

With the payment process completed, the merchant proceeds to ship the product to the customer. The customer receives the product just as they would if they had paid in full at the time of purchase. This seamless experience enhances customer satisfaction and encourages repeat business.

Repayment Schedule

After the purchase, the customer is provided with a repayment schedule outlining the installment amounts and due dates. The repayment period and frequency of installments can vary depending on the terms set by the BNPL provider. This schedule helps customers manage their finances by spreading the cost over time.

Customer Makes Repayments

The final step involves the customer making payments according to the provided schedule. Payments can be automatically deducted from the customer’s bank account or made manually through the BNPL platform. These installments are usually interest-free if paid on time, though late payments may incur additional fees.

Key Players and Their Roles
The key players in the BNPL ecosystem include the customer, the merchant, and the BNPL service provider. The customer benefits from flexible payment options, allowing them to manage their finances better. The merchant benefits from increased sales and reduced cart abandonment rates, as BNPL options can attract a wider range of customers. The BNPL service provider facilitates the transaction, pays the merchant upfront, and manages the repayment process, generating revenue through interest, late fees, and merchant fees.

Benefits of BNPL
For customers, BNPL services provide financial flexibility, enabling them to acquire products without paying the full price upfront. This can be particularly useful for budgeting and managing high-value purchases. For merchants, offering BNPL can lead to higher conversion rates and average order values, making it an attractive option to increase sales. Lastly, BNPL providers benefit from building a customer base and generating revenue through various fees.

This detailed explanation highlights how BNPL services work, detailing each step of the process and the roles of the key players involved, providing a comprehensive understanding of the BNPL ecosystem.

The provided diagram titled “How Does Buy Now Pay Later Work?” outlines the sequential steps involved in a Buy Now Pay Later (BNPL) process.
Now lets find out, with simple explanation of each step in the diagram:

Customer makes an online purchase at a merchant site: The process begins with a customer selecting products and making an online purchase on a merchant’s website.
Merchant offers BNPL as a payment option at checkout: At the checkout stage, the merchant provides the customer with the option to choose BNPL as a payment method.
Customer signs up/signs in to the BNPL service providing platform: The customer either signs up for a new account or signs in to an existing account on the BNPL service provider’s platform.
Payment is debited from the BNPL platform: Once the BNPL option is selected and approved, the payment for the purchase is debited from the BNPL platform. This means the BNPL provider pays the merchant on behalf of the customer.
Product is delivered to the customer: The merchant processes the order and delivers the product to the customer.
Instant e-KYC and credit risk analysis is done by the BNPL service provider: The BNPL service provider performs an electronic Know Your Customer (e-KYC) process and conducts a credit risk analysis to assess the customer’s creditworthiness.
BNPL service provider approves the credit: Based on the results of the e-KYC and credit risk analysis, the BNPL service provider decides whether to approve the credit. If approved, the customer can proceed with the BNPL payment plan.
Customer pays the balance to the BNPL service provider at the end of credit period: The final step involves the customer repaying the BNPL service provider. The customer pays the outstanding balance as per the agreed credit terms at the end of the credit period.
Business Use-Cases for Buy Now, Pay Later (BNPL) Systems
Buy Now, Pay Later (BNPL) systems offer versatile financing solutions across various industries, enhancing customer satisfaction and driving sales.

In e-commerce platforms, BNPL increases conversion rates and average order values by providing flexible payment options. Retail stores can enhance customer loyalty and attract budget-conscious shoppers by offering BNPL at the point of sale.

The travel and hospitality sector benefits from increased bookings and revenue by making travel more accessible through installment payments.

Healthcare services can improve access and manage cash flow by allowing patients to finance medical procedures. Educational institutions can boost enrollment and retention by enabling students to pay tuition fees in installments.

Subscription services, luxury goods, automotive industry, home improvement, and event ticketing also see significant benefits. BNPL reduces upfront costs, making products and services more attainable, driving sales, and fostering customer loyalty.

System Design To Incorporate In Architecture
To design a comprehensive BNPL system architecture and incorporating best practices for modern, scalable, and secure systems, lets create a detailed architecture. This system will include various components and services, focusing on modularity, event-driven architecture, and robust integration.

Full Version

Mermaid Diagram

Key Components:
Frontend Components
The Customer Portal is the interface through which customers can browse products, sign up for BNPL services, apply for loans, and manage their repayments. Technologies: React.js (for building the user interface), Redux (for state management), Tailwind CSS (for styling), and Next.js (for server-side rendering and static site generation).

The Merchant Portal allows merchants to integrate BNPL services into their checkout process, manage transactions, and view analytics. Technologies: React.js, Redux, Tailwind CSS, Next.js are scalable options.

The Admin Portal is used by administrators to manage the BNPL system, monitor performance, handle customer and merchant queries, and perform configurations. Technologies: React.js, Redux, Tailwind CSS, Next.js. Backend and Microservices components are involved.

Loan Origination System (LOS)
Manages the loan application processwa, including customer sign-ups, application submission, and initial verification. Technologies: Node.js (runtime environment), Express.js (web application framework).

Decision Engine evaluates loan applications using predefined business rules and machine learning models to perform instant credit decisioning. Technologies: Node.js, Express.js.

Loan Management System (LMS) Manages active loans, including disbursements, repayment schedules, and the overall loan lifecycle. Technologies: Node.js, Express.js.

Collections Service Handles payment collections, sends reminders, and manages overdue payments. Technologies: Node.js, Express.js.

Product Service Maintains a catalog of BNPL products, including terms, repayment schedules, and interest rates. Technologies: Node.js, Express.js.

Consumer Service manages customer profiles, including KYC (Know Your Customer) data and credit information. Technologies: Node.js, Express.js.

Partner Onboarding Service registers new merchants, manages their profiles, and facilitates their integration with BNPL services. Technologies: Node.js, Express.js.

Paylater Service Provides core BNPL functionalities during the checkout process, including initiation and approval. Technologies: Node.js, Express.js.

Notification Service sends notifications to customers and merchants about application status, payment reminders, and other updates. Technologies: Node.js, Express.js. Cloud Services (AWS)

Technology Stack
In this study, selection of tools to be incorporated via dedicated Amazon Services to simulate ideal infrastructure and tools. Lets list down the required components of technical stack.

API Gateway manages API requests, providing API management functionalities and integration with AWS services and AWS Lambda executes serverless functions for various backend operations, reducing infrastructure management overhead.

Amazon DynamoDB provides a NoSQL database for storing transaction data with fast and predictable performance and Amazon RDS (PostgreSQL) manages relational database operations for transactional data that require complex queries.

Amazon S3 offers object storage for storing documents, reports, and other static content.

Amazon EventBridge facilitates event-driven architecture by managing events and enabling services to communicate via events.

Amazon SQS provides message queuing for decoupling services and ensuring reliable communication.

AWS Fargate runs containerized applications without managing the underlying servers.

AWS WAF protects web applications by filtering and monitoring HTTP requests.

AWS Secrets Manager securely stores and manages sensitive information like API keys, database credentials, and other secrets.

AWS IAM manages identity and access control for AWS resources.

Integration Layer
In this study, IBM API Connect is chosen for its comprehensive API management, advanced security and compliance features, scalability, and performance. It seamlessly integrates with various backend systems, provides robust analytics and monitoring tools, and supports developer engagement through an easy-to-use portal. Its flexibility in deployment (on-premises, cloud, or hybrid) and cost-efficient API monetization and management make it ideal for the complex needs of financial services and digital lending systems.

IBM API Connect manages and exposes APIs to external partners, providing API lifecycle management.

Enterprise Service Bus (ESB) integrates with on-premises core banking systems, handling legacy SOAP/XML communication.

On-Premises Core Banking Services
Finacle API is chosen for this study, per it is robust banking capabilities, seamless integration with core banking systems, and advanced security features. It offers high scalability, performance, and compliance with financial regulations. Additionally, Finacle API provides comprehensive analytics, easy developer onboarding, and flexibility in deployment options, making it ideal for modern banking needs.

Finacle provides core banking functionalities such as account management and transaction processing. Technologies: Finacle API.

KYC Services
KYC (Know Your Customer) services are essential for compliance with legal and regulatory requirements, preventing money laundering and fraud. They help financial institutions assess and manage customer risk, enhancing overall security by verifying customer identities. Ensures customer verification and compliance with regulatory requirements.

Additional Tools and Services
Docker containerizes applications, ensuring consistency across development, testing, and production environments. Technologies: Docker.

Kubernetes orchestrates containerized applications, managing deployments, scaling, and operations. Technologies: Kubernetes.

Terraform manages infrastructure as code (IaC), ensuring consistent and reproducible infrastructure deployment. Technologies: Terraform.

Jenkins facilitates continuous integration and continuous deployment (CI/CD), automating the build, test, and deployment processes. Technologies: Jenkins.

Grafana and Prometheus provides monitoring and alerting capabilities, offering insights into application performance and system health. Technologies: Grafana, Prometheus.

These components collectively ensure a robust, scalable, and secure BNPL system, leveraging modern cloud infrastructure and best practices in software architecture.

Conclusion
This BNPL system architecture ensures a robust, scalable, and secure solution by integrating modern cloud services with legacy on-premises systems. Key components include customer, merchant, and admin portals, various microservices for loan processing and management, and essential AWS services for API management, data storage, and security.

The integration layer and core banking services ensure seamless operation and compliance, providing a comprehensive, efficient BNPL solution.