About Me
I’m Kagan and this is my resume.
I’m an AI engineer with seven years of software engineering experience. Over the last two years, I’ve moved from shipping AI features to building production agents and the evals that keep them reliable. I start with the problem and the people I’m solving it for, then decide whether it is worth building.
At Pendo, I build AI agents used by product teams at some of the world’s largest enterprises. They trust these agents with their data and use their answers to make product decisions.
I move quickly, put 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 Leo, Pendo’s agent: built and shipped the supervisor orchestrating quantitative, qualitative, knowledge and data-synthesis subagents, plus 8 production agentic workflows and MCP tools in Go. 194 merged PRs in first 9 months.
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Built Pendo’s agent evaluation platform from scratch: LLM-as-a-Judge with failure taxonomies and levelled test sets, multi-run flake resistance, LangSmith trace integration, and a multi-backend comparison harness (API, MCP, Claude SDK, LangGraph, Slack/Teams) with a web UI used by engineers and PMs. Adopted into company infrastructure.
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Led Leo’s migration from OpenAI to Gemini across the supervisor and all subagents: staged rollouts behind flags, streaming thinking output, full decommission of legacy paths. Shipped region-aware model routing and localization for Pendo’s Japan launch.
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Own agent reliability in production: hypothesis-driven debugging via traces, guardrails against fabricated data, tool-contract and context-window fixes.
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Accelerate AI adoption through hands-on delivery, internal AI training and team onboarding across multiple teams. Named Pendo's AI MVP for Q1 2026.
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Bridge engineering, product and leadership: set up the meetings that keep product and engineering aligned, join customer calls to feed user context back into agent decisions, and back leadership decisions with eval reports and technical recommendations.
The only project management platform built specifically for client work.
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Worked on AI features from ideation to production, shipped AI-generated project setups that doubled onboarding completion rates.
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Built AI Forecasting using TinyTimeMixer and Prophet, self-hosted on AWS.
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Built production features with Vue.js, Tailwind CSS and Go. Used LaunchDarkly feature flags for safe, incremental rollouts.
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Ran data-driven experiments to optimize KPIs and drive user growth using Pendo, HubSpot and Hotjar.
London-based fintech startup. ePOS app that turns tablets and smartphones into powerful cash registers.
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Small team, high autonomy. Worked directly with CEO and CTO to define the product. Learned to be outcome-focused and ship fast.
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Built Go microservices with gRPC. Dockerized and deployed on Google Kubernetes Engine.
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Integrated with partner bank API to automate merchant onboarding, reduced time from contract to first transaction to just hours.
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Shipped a React + TypeScript mobile app using Ionic and Capacitor. Built custom Capacitor plugins for native SDK access.
Software consultancy in Izmir, Turkey. Strong culture of learning and exploring new technologies.
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Shipped multiple projects as an intern: product catalog app, activity monitoring software and data pipelines. Learned by building, not just reading.
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Built microservices with Java + Micronaut, PostgreSQL, GraphQL. Containerized with Docker and Docker Swarm.
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Built web scrapers with Scrapy-Splash to extract gigabytes of data daily. Prepared data for ML training using Python.
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Data visualization and analysis with Pandas, Elasticsearch, Kibana. Automated deployments with Bash.
Notable
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.
Open Source
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
Agent Orchestration Multi-Agent Systems Agentic Workflows Evals / Agent Evaluation LLM-as-a-Judge Failure Taxonomies Context Engineering Prompt Engineering Tool Calling RAG MCP Coding Agents Python TypeScript JavaScript Go Vue.js React Node.js FastAPI LangChain LangGraph LangSmith Gemini / Vertex AI OpenAI Anthropic / Claude APIs PostgreSQL Redis Docker Kubernetes GitHub Actions GCP AWS Cloudflare Claude Code Codex Observability LaunchDarkly Pendo