2026-09-20
When Should Claude Code Crack a Joke?
Emre Erkan's sitcom-flavour plugin brings sitcom lines into Claude Code sessions. An honest look at the personal value of small side projects.
Read →4 min
Engineering
Technical depth, grounded in reality
Nearly three decades of designing, building, and shipping software: architecture decisions, infrastructure, and the trade-offs that determine whether a business idea can become a dependable operating system.
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2026(28)
2026-09-14
CIO, CTO, and IT Director: What the Title Misses
CIO, CTO, and IT Director roles make more sense when read through responsibility, decision authority, and the role technology plays in the company.
Read →13 min
2026-09-12
Why the Same AI Model Produces Different Results Across Applications
Why can the same AI model perform so differently across products? The application, context, tools, permissions, and evaluation setup all shape the result.
Read →4 min
2026-09-06
Writing with AI Means Thinking About Your Archive, Too
What Casey Newton’s LLM wiki reveals about using AI to connect new articles with an existing archive, research notes, and editorial decisions.
Read →6 min
2026-09-03
What Makes an AI System Specific to Your Business?
A company-specific AI system is more than a model trained on company data. The real difference often lives in data, rules, tools, permissions, and measurement.
Read →8 min
2026-09-02
How Should You Route Requests Across Multiple AI Models?
When an AI system uses several models, should requests be assigned by explicit rules, predictive routing, cascades, or fallback paths?
Read →9 min
2026-09-02
With AI, a Refactor I Wouldn't Bother With Took One Hour
PeşinTaksit was a neglected side project that still required four containers. With AI, I moved it to Cloudflare Workers in about an hour.
Read →4 min
2026-09-01
When Is One AI Model Enough?
When should an AI system begin with one model, and what improvement in quality, cost, speed, or risk would justify adding another?
Read →8 min
2026-08-31
Is Your Data Ready for AI? Start With the Decision It Must Support
Whether data is sufficient depends on the decision it must support, how current it needs to be, and how the outcome can be verified.
Read →6 min
2026-08-31
Is Your AI System Actually Delivering Business Results?
A good model response, a completed task, and a measurable business result are three different outcomes. Here is how to evaluate each one.
Read →7 min
2026-08-30
How Much Authority Should You Give an AI System?
When should an AI system prepare a recommendation, and when should it be allowed to execute a real transaction? A practical boundary for authority, approval, and verification.
Read →7 min
2026-08-29
When Does Enterprise AI Actually Need RAG?
When should enterprise AI use RAG, direct context, a database query, or an API? A practical way to choose the right source for each question.
Read →6 min
2026-08-28
When Do You Actually Need an AI Agent?
Customer support, lead routing, REDAR, and incident diagnosis show the practical difference between software-defined workflows and AI agents.
Read →6 min
2026-08-28
Does Enterprise AI Really Need Fine-Tuning?
When is providing a document enough, when does RAG help, and when does fine-tuning actually make sense? The decision starts with information, rules, and patterns.
Read →8 min
2026-08-27
Start With the Business Problem, Not the AI Model
Why model selection should not be the first decision in an AI project, and what must be defined about the business outcome, action boundary, and evidence first.
Read →6 min
2026-08-27
Integrating One Bank Is Easy. Keeping Forty Running Is Not.
A single bank integration may be straightforward. The real cost is normalising different access models and keeping dozens of connections working as banks change.
Read →9 min
2026-08-27
Preserving API Quality in AI-Assisted Development
A short guide to preserving resource models, HTTP behaviour, error handling, authorization, security, and contract decisions in prompts, reviews, and delivery checks when building REST APIs with AI.
Read →8 min
2026-08-25
Testing a Button, Treating an Entire Website Redesign as a Sure Thing
Why website redesigns should separate design, CMS, URL, content, form, and measurement changes, and how progressive redesign reduces migration risk.
Read →8 min
2026-08-24
Managing Technology and Transforming the Business Are Not the Same Thing
Why keeping technology running and using it to transform the business should not be treated as the same responsibility.
Read →5 min
2026-08-24
Turkey's First Real-Time Mystery Shopping Reporting Platform
A note on how I built the operational system behind PlusValue's mystery-shopping work, which began as a university final project in 2005.
Read →6 min
2026-08-24
Keeping Customers Happy Isn’t Enough. You Have to Follow Up.
A positive customer experience does not automatically turn into a review or recommendation. A small observation about follow-up, timing, and how AI changes the cost of building useful software.
Read →7 min
2026-08-22
Do You Know How Dependent Your Company Is on AI?
AI is not only accelerating work people already did. It is creating operational capacity companies could never afford to have — and that capacity needs a continuity plan before it becomes structural.
Read →11 min
2026-08-20
AI Wasn’t Always This Good. We Just Got Used to It.
AI is rapidly changing team capacity and software economics. That calls for a fair view of the past—and new expectations for today.
Read →5 min
2026-08-18
AI Made Code Cheap. Verification Is Still Expensive.
AI can produce an implementation in hours. If its author cannot explain the decisions behind it, the real engineering work has not disappeared — it has moved to the reviewer.
Read →6 min
2026-08-15
Accessing Know-How Is Not the Same as Creating It
Access to global know-how is a real advantage. But there is an important difference between applying ready-made knowledge and creating it yourself.
Read →5 min
2026-06-28
The Threshold Collapsed: What ProductLog Taught Me About Building in Public
I built ProductLog so founders can record their work as it progresses. The platform is live, and it remains a meaningful part of my work. But its premise also creates a tension: a well-kept public record makes a product’s story easier to follow and understand than scattered blog posts do. When AI can gather and process those records more quickly, that same clarity may become a useful shortcut for competitors.
Read →4 min
2026-06-27
The Era of the "Previous Vibe Coder" Begins: The Invisibility of Clean Code and the Technical Debt Bill of AI
An analysis of the false speed illusion of AI coding, DRY violations, the devaluation of invisible quality using Akerlof's Market for Lemons, and the upcoming crisis of the 'Previous Vibe Coder'.
Read →9 min
2026-06-23
Comprehension Debt: The Bill Comes Due Alone
I ship with AI coding agents daily. The hidden risk is the gap between what the system can do and what I can still explain, debug, and safely change.
Read →9 min
2025(3)
2025-11-20
The End of Coding or a New Renaissance? The Invisible Crisis of AI
AI may reduce the routine work through which junior developers learned. The more consequential question is how organisations will preserve practice, feedback, and the path to senior capability.
Read →6 min
2025-07-02
Why I Run camiler.org on a Single VPS
How I use Docker, Redis, and Cloudflare to run camiler.org on one small VPS, what problems it solves, and which risks I still own.
Read →7 min
2025-06-26
Medical Tourism Lead Management: How We Moved from Manual Routing to a Real-Time Sales System
How we replaced manual routing for roughly 100,000 yearly leads with a real-time medical tourism system built around language, country, shift, and capacity rules.
Read →7 min