About Me
I’m an AI engineer with 7+ years of software engineering experience. For the past 2 years, I’ve focused on building AI products and production agents, along with the evals that keep them reliable. Product teams at some of the world’s largest enterprises trust these agents with their data and use their answers to make product decisions.
I start with the problem, who it matters to and whether it is worth prioritising.
I move quickly, get working software in front of users early and improve it from real feedback. I’ve worked across multiple teams to accelerate AI adoption through hands-on delivery.
In my free time you can find me running, climbing, cooking and building tools and games.
Experience
Product experience platform that helps companies make product intelligence actionable at speed and scale.
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Core engineer on Pendo's AI agent, working end-to-end across multi-agent orchestration, skills, MCP tooling and eight workflows. Averaged 67 merged PRs per month.
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Built Pendo’s internal agent evaluation tool from scratch, combining LLM-as-a-Judge, repeatable test suites, trace-based debugging and multi-backend comparison. It enabled engineers and PMs to make eval-driven decisions on model migrations, MCP tooling and launches.
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Led model strategy and regional deployment architecture for Pendo’s AI agent, delivering its model migration and expansion to Japan. Owned implementation and coordination with Legal and Platform Ops.
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Improved agent reliability through trace-led debugging, hallucination guardrails and tool/context fixes. Synthesised traces, logs, analytics and user feedback into recurring AI-assisted gap analyses that surfaced high-impact improvements.
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Accelerated Pendo’s AI transformation through hands-on delivery and onboarding across multiple teams. Named Pendo's AI MVP for Q2 2026.
The only project management platform built specifically for client work.
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Designed and built an AI onboarding flow that generated customised project plans, prioritised tasks and assigned work from user input, doubling onboarding completion rates.
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Built Teamwork’s AI Profitability Forecaster with TinyTimeMixer and Prophet, turning historical data into one-click revenue, cost and profit predictions on AWS.
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Ran full-stack growth experiments in Vue.js and Go, using LaunchDarkly for controlled rollouts and Pendo, HubSpot and Hotjar to measure impact.
London-based fintech startup. ePOS app that turns tablets and smartphones into powerful cash registers.
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Joined at the earliest stage and built the company’s first merchant onboarding integration, working directly with the partner bank from technical discussions through implementation.
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Shipped a React, TypeScript and Ionic POS app used by real customers, including custom Capacitor plugins that connected phones to the bank’s payment terminals.
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Built Go and gRPC microservices, containerised with Docker and deployed on Google Kubernetes Engine.
Software consultancy in Izmir, Turkey. Strong culture of learning and exploring new technologies.
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Built large-scale Scrapy and Splash pipelines that collected gigabytes of web data daily, then cleaned and prepared datasets in Python and Pandas for model training.
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Analysed large industrial datasets with Pandas, Elasticsearch and Kibana, turning raw operational data into actionable insights for researchers.
Notable
Book Chapter Author
40-page chapter · 2024
Sole author of “Makine Öğrenmesi ve Sağlık Alanındaki Çalışmalarda Kullanımı”, covering machine learning, generative AI and Python applications in health research.
Speaker
Minicon XII 2026
“How to Train Your (Coding) Agent”: Explored the current state of LLM capabilities along with practical patterns for managing context windows, subagents, skills and agentic workflows (bash loops) for AI-first development.
Viral Post
2M+ views across LinkedIn & Reddit
“Fewer Juniors Today = Fewer Seniors Tomorrow”: Sparked widespread industry discussion on the long-term talent pipeline risks of AI hype in software engineering.
Projects
A two-phase gate locks design verdicts (right place, right abstraction, right thing to build) before line-level review begins. Separate evaluation bars per phase, a finding-depth ladder and a grader pass keep the output high-signal.
Portable skills + hooks that give coding agents wall-clock time awareness (chronos), productive disagreement (pushback), first-class git/PR workflows (shipit) and structured thinking (socratic). Multi-harness: Claude Code, Codex and others. More at github.com/kadenn.
Education
Ege University
BSc Computer Science
2017 - 2021 (GPA 3.11/4.0)
Top research university in Turkey.
Started working as a developer in my second year while balancing coursework. Active in Ege Entrepreneurship Society, organizing company visits and campus events. Learned early that building is the best way to learn.
Software Skills
AI Agents Multi-Agent Orchestration Agentic Workflows Evals / Agent Evaluation LLM-as-a-Judge Context Engineering Tool Calling RAG MCP Coding Agents Python TypeScript Java Go Vue.js React FastAPI LangGraph LangSmith Gemini / Vertex AI OpenAI / Anthropic APIs PostgreSQL Docker Kubernetes GCP AWS Cloudflare Observability Claude Code Codex