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My Thoughts on AI: Week of June 12

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I am not trying to crown one AI tool as the winner forever. These tools change too fast for that. What matters to me is more practical: when I sit down to do real work, which one helps me keep going, make fewer messy mistakes, and understand what happened when the session is over? Codex and Claude Code both do serious coding work. They can read files, make changes, run commands, and help move a project forward. But they feel different. Codex feels more like the tool I use when I need to finish implementation. Claude feels stronger when the work needs taste, presentation, and design sense. This is also just where I am right now. My opinion is based on GPT-5.5 in Codex and Opus 4.8 in Claude Code. Fable 5 also came out this week, on June 9, 2026, so even while I am writing this, the ground is already moving. Codex Feels Better When the Job Has a Clear Finish Line Codex works best for me when the task is concrete. Read the repo. Follow the project rules. Make the change. Run the ch...
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My Experience Writing Zone 2 Trainer for Android

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Zone 2 Trainer started as a simple idea: I wanted a lightweight way to stay honest about easy aerobic work without committing to another subscription or buying another dedicated device. The app became both a fitness tool and a test case for how far modern AI coding assistants can carry a non-mobile developer. For the last couple of months, I have been developing an Android application to enhance my endurance and recovery. Most applications on the market require an active subscription and a special device. With the current developments in AI-assisted software development, I was able to step out of my comfort zone and build an application from scratch using Android Studio, Antigravity, and Codex. That matters to me because I am not a developer by trade. I am closer to a tinkerer who is comfortable with scripts, databases, and infrastructure than someone who spends every day building polished mobile apps. Zone 2 Trainer became a useful test of how far AI coding tools can take someone l...
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My Thoughts on AI: Week of May 25

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The AI product climate this week was weirdly clarifying. I am still not ready to move my development workflow back to Gemini after the rate-limit frustration, but I also have to admit that Google shipped a few things that made me pay attention again. At the same time, OpenAI reminded me that even the best developer tooling can feel unnecessarily confusing when the billing model sprawls across too many surfaces. Then OpenRouter raised a serious round of funding and made the case for a future where developers do not have to bet everything on one model vendor. That is the pattern I keep coming back to: the tools are getting better, but the surrounding product experience still matters just as much as the model. Gemini Is Back in My General-Purpose Rotation I have complained plenty about Gemini rate limits. The stricter enforcement hit the wrong nerve for me because it made the product feel unpredictable at exactly the moment I wanted to rely on it more. Once a tool makes me ration m...
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Accelerating PostgreSQL with ReadySet Caching

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Disclaimer: The opinions expressed in this article are my own and do not necessarily reflect the views of my employer. This tutorial demonstrates how to use ReadySet as a caching layer for PostgreSQL databases. ReadySet is a wire-compatible caching solution that sits between your application and database, providing sub-millisecond query performance without requiring code changes. Why Cache PostgreSQL? PostgreSQL is the world's most advanced open-source relational database, widely used for transactional workloads. Whether you're running PostgreSQL on-premises, in the cloud, or using a managed service, every query incurs: Network round-trip latency – Depending on region and network conditions (e.g., 14ms from a client in New Jersey to a cluster in AWS us-east-1) Query processing overhead – Parsing, planning, and execution on the database server Result serialization – Packaging and transmitting results back to your application For read-heavy workloads with repetitiv...
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Exploring Real-Time Data Ingestion into Snowflake Using CockroachDB, Redpanda, and Kafka Connect

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This article serves as a follow-up to previous discussions on data ingestion into Snowflake, specifically focusing on the complexities and efforts involved in integrating Change Data Capture (CDC) data with Snowflake in real time. Previous Articles on Snowflake Tour of Snowflake ingestion using CockroachDB and Redpanda Connect Integrating Snowflake with Trino Previous Articles on CockroachDB CDC Emitting Protocol Buffers with CockroachDB CDC Queries Using CockroachDB CDC with Apache Pulsar Using CockroachDB CDC with Azure Event Hubs SaaS Galore: Integrating CockroachDB with Confluent Kafka, FiveTran and Snowflake Using CockroachDB CDC with Confluent Cloud Kafka and Schema Registry CockroachDB CDC using Minio as cloud storage sink CockroachDB CDC using Hadoop Ozone S3 Gateway as cloud storage sink Motivation This article builds upon the previous discussion in Tour of Snowflake ingestion using CockroachDB and Redpanda Connect , where we investigated the process of stre...
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Tour of Snowflake ingestion using CockroachDB and Redpanda Connect

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This is an exploratory article delving into various ways to ingest real-time data into Snowflake. The premise of the article is to examine the level of difficulty and effort required to ingest change data capture (CDC) data into Snowflake. Previous Articles on Snowflake Integrating Snowflake with Trino Previous Articles on CockroachDB CDC Using CockroachDB CDC with Apache Pulsar Using CockroachDB CDC with Azure Event Hubs SaaS Galore: Integrating CockroachDB with Confluent Kafka, FiveTran and Snowflake Using CockroachDB CDC with Confluent Cloud Kafka and Schema Registry CockroachDB CDC using Minio as cloud storage sink CockroachDB CDC using Hadoop Ozone S3 Gateway as cloud storage sink Motivation I work with financial services clients, and it's common to encounter a need for streaming changes in the operational datastore into a data warehouse or a data lake. A former colleague recently reached out for advice on the fastest and most efficient way to load trade data ...
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