Goal
To make complex technical topics simple and actionable, and to leave the audience with a way of looking at the problem and concrete examples they can put to use in their own projects right away.
I consider sharing what I learn part of engineering. Under the name Developer Meeting, I gave talks to software developers on the tools that hold up in real projects, architectural decisions and ways of working.
To make complex technical topics simple and actionable, and to leave the audience with a way of looking at the problem and concrete examples they can put to use in their own projects right away.
I prepared every talk myself, from choosing the topic to structuring the content and delivering it; I walked through each topic with examples and kept it open to Q&A and discussion.
How speech-to-text libraries work, how well they support Turkish, and how to integrate them into an application.
Building iOS and Android apps from a single codebase: architecture, development workflow and what to watch out for in mobile projects.
Taking a software project from scope to delivery: planning, prioritization, division of work and communication within the team.
Packaging applications in containers: images, layers, Docker Compose and closing the gap between development and production.
Sketching the idea before writing any code: using quick sketches and prototypes to pin down requirements and get the whole team looking at the same picture.
Testing APIs so you can change them with confidence: request collections, automated tests and contract conformance.
Normal forms in database design: preventing redundancy and inconsistency, and knowing when to denormalize deliberately.
Data visualization with Apache ECharts: chart types, interactivity and dashboard performance with dense data.
A talk that explains software development through everyday examples and reminds us that code has a life cycle too.
A shared template so that new projects start from the same solid foundation: layered architecture, authentication, authorization and standard tooling.
Continue, the open-source AI coding assistant: connecting different models to the editor and developing with the codebase as context.
The shared template’s continuous integration and deployment pipeline: build, test, image creation and automated release.
How a growing monolith becomes unwieldy, the signs that it needs to be broken apart, and how the migration can be done step by step.
The core principles of good software: how approaches like SOLID, DRY and KISS turn into readable, maintainable code across a team.