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    <description>José Neves on data pipelines, PostgreSQL and bringing AI into engineering work.</description>
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    <lastBuildDate>Tue, 03 Nov 2026 00:00:00 GMT</lastBuildDate>
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      <title>Database Locks: Why You Shouldn&apos;t Let Your AI Loose</title>
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      <pubDate>Tue, 03 Nov 2026 00:00:00 GMT</pubDate>
      <description>LLM-written code tends to default to database locks to deal with concurrency. A small Go and PostgreSQL benchmark shows what that costs: last write wins served 1.5 to 3 times more users than the locking patterns.</description>
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      <title>Meet Toki, our AI Assistant</title>
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      <pubDate>Sun, 10 May 2026 00:00:00 GMT</pubDate>
      <description>An internal AI assistant — named after the Japanese 時 / とき (time, moment, era, opportunity) — autonomously resolved 32.5% of intervened engineering support requests over four weeks. A look at how it&apos;s plugged in, its quirks, and where it&apos;s actually helping versus where humans still own the work.</description>
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      <title>Another Try at LLM Workflow Automation</title>
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      <pubDate>Sat, 18 Apr 2026 00:00:00 GMT</pubDate>
      <description>After repeated attempts at LLM workflow automation, a first real success comes not from smarter models but from scaffolding — small, scoped tools around the LLM that iterate, validate, and fit into existing workflows without a chatbox in sight.</description>
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      <title>Tried to Automate Engineering Support, and I Succeeded, Well... Kind&apos;a</title>
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      <pubDate>Fri, 20 Mar 2026 00:00:00 GMT</pubDate>
      <description>~15% of engineering time goes toward support work. After attempting a self-evolving knowledge graph and failing, a more practical AI-assisted approach emerged — one that lets a single engineer handle triage 10 to 30 times faster.</description>
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      <title>Why We&apos;re Splitting Our ETL Pipeline Into Three Independent Layers</title>
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      <pubDate>Fri, 06 Mar 2026 00:00:00 GMT</pubDate>
      <description>Most ETL pipelines combine ingestion, change detection, and transformation into a single process. Learn why we&apos;re pulling them apart into three independent stages — and the early signs that suggest it might be the right call.</description>
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      <title>Becoming Protocols</title>
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      <pubDate>Mon, 23 Feb 2026 00:00:00 GMT</pubDate>
      <description>A reflection on how AI tools are reshaping how we communicate and create content online. Using AI to express ourselves is powerful — when used with intent — but we risk dissolving into the systems we use if we&apos;re not careful to remain present in what we produce.</description>
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      <title>From AI-Orchestrated to AI-Practical: What Two Weeks of Obsession Actually Taught Me</title>
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      <pubDate>Wed, 18 Feb 2026 00:00:00 GMT</pubDate>
      <description>A follow-up reflection on dismantling an AI orchestration system and rebuilding a practical, overhead-free workflow. This article explores the gap between what&apos;s theoretically possible with AI agents and what&apos;s practically useful today.</description>
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      <title>From AI-Assisted to AI-Orchestrated: A Software Engineer&apos;s Reluctant Evolution</title>
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      <pubDate>Sat, 14 Feb 2026 00:00:00 GMT</pubDate>
      <description>A personal reflection on the transition from using AI as a coding assistant to fully embracing AI-orchestrated development workflows. This article explores the mindset shift required to move beyond traditional software engineering practices and adapt to a new paradigm where AI agents handle increasingly complex tasks.</description>
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      <title>A journey into PostgreSQL logical replication - the next chapter</title>
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      <pubDate>Tue, 15 Oct 2024 00:00:00 GMT</pubDate>
      <description>Toggl Engineering shares how they expanded their PostgreSQL logical replication CDC pipeline to support event-driven architecture and OLAP features. The team discusses challenges overcome and practical optimization techniques for handling near real-time data transformations across multiple transactional databases.</description>
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      <title>A journey into PostgreSQL logical replication</title>
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      <pubDate>Fri, 19 Jan 2024 00:00:00 GMT</pubDate>
      <description>Toggl Track faced challenges serving analytical reporting needs alongside their transactional database. The engineering team implemented a PostgreSQL logical replication pipeline to stream data changes in near real-time, but discovered critical misconceptions about LSN offset tracking that caused data inconsistencies in production.</description>
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