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	<title>machine learning &#8211; Rafael Bernard Araujo</title>
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		<title>Tropeçando 120</title>
		<link>https://rafael.bernard-araujo.com/tropecando-120.php</link>
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		<dc:creator><![CDATA[rafael]]></dc:creator>
		<pubDate>Mon, 18 May 2026 00:02:13 +0000</pubDate>
				<category><![CDATA[Tropeçando]]></category>
		<category><![CDATA[ai]]></category>
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		<category><![CDATA[developer experience]]></category>
		<category><![CDATA[docker]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[software architecture]]></category>
		<category><![CDATA[software engineering]]></category>
		<guid isPermaLink="false">https://rafael.bernard-araujo.com/?p=2363</guid>

					<description><![CDATA[AI Management &#38; Organizational Restructuring The Foreman Problem: Managing Teams When Your Best Worker Isn't Human - Willian Correa Every major technology shift invented a new management role. Steam power → foreman. Office computing → project manager. Internet → product manager. AI is doing the same, but this time the failure mode is invisible: confident, [&#8230;]]]></description>
										<content:encoded><![CDATA[<h3>AI Management &amp; Organizational Restructuring</h3>
<p><a href="https://businessasusual.io/p/the-foreman-problem-managing-teams">The Foreman Problem: Managing Teams When Your Best Worker Isn't Human</a> - Willian Correa</p>
<blockquote>
<p>Every major technology shift invented a new management role. Steam power → foreman. Office computing → project manager. Internet → product manager. AI is doing the same, but this time the failure mode is invisible: confident, polished, wrong output. The new job is not directing effort but verifying that things that <em>look</em> like they're running actually are.</p>
</blockquote>
<p><a href="https://theengineeringmanager.substack.com/p/who-will-be-the-senior-engineers">Who Will Be the Senior Engineers of 2035?</a> - James Stanier</p>
<blockquote>
<p>The traditional junior-to-senior pipeline is breaking: entry-level tech postings down 67% since 2022, junior employment down ~20%. Firms adopting AI saw junior employment fall 7.7% vs non-adopters. 54% of engineering leaders plan to hire fewer juniors.</p>
</blockquote>
<h3>Compound Engineering &amp; Code Health</h3>
<p><a href="https://refactoring.fm/p/the-compounding-software-factory">The Compounding Software Factory</a> - Luca Rossi (Software Factory series, Part 3 of 3)</p>
<blockquote>
<p>What causes teams to degrade: poor coding hygiene (bad testing, poor code health, missing abstractions), failure to capture knowledge (no ADRs, no playbooks, no snapshots), and building the wrong things.</p>
</blockquote>
<p><a href="https://refactoring.fm/p/ai-coding-meets-code-health-with">AI Coding Meets Code Health</a> - Stuart Caborn</p>
<blockquote>
<p>Loveholidays' journey to becoming an AI-first engineering organization. Core thesis: code health is the foundation for successful AI adoption. By deliberately investing in code health metrics <em>before</em> adopting AI, they achieved 80+ deployments/month, 60% AI-written code, &lt;1% change failure rate, all while maintaining elite code health.</p>
</blockquote>
<h3>Security &amp; Infrastructure</h3>
<p><a href="https://www.wiz.io/blog/github-actions-security-ai-powered-actions-vulnerabilities">The (In)security Landscape of AI-Powered GitHub Actions</a> - Shay Berkovich</p>
<blockquote>
<p>AI-powered GitHub Actions from vendors like OpenAI, Anthropic, and Google are now running in thousands of public workflows. Research found bypasses of non-default configurations letting any external attacker trigger AI execution, a novel secret exfiltration vector for dynamically-created credential files, and widespread misconfigurations in production workflows.</p>
</blockquote>
<p><a href="https://www.allthingsdistributed.com/2026/04/the-invisible-engineering-behind-lambdas-network.html">The Invisible Engineering Behind Lambda's Network</a> - Werner Vogels</p>
<blockquote>
<p>A decade-long story of invisible infrastructure engineering by Lambda's networking team.</p>
</blockquote>
<h3>Career &amp; Token Economics</h3>
<p><a href="https://businessasual.io/p/tokenmaxxing-is-the-budget-game-played">Tokenmaxxing Is the Budget Game Played With AI Tokens</a> - Willian Correa</p>
<blockquote>
<p>Tokenmaxxing — maximising AI token consumption for visibility — is the corporate &quot;use it or lose it&quot; budget game in a new currency. Meta's internal &quot;Claudeonomics&quot; leaderboard ranked 85K employees by token consumption; top user burned 281B tokens in 30 days.</p>
</blockquote>
<h3>Tools</h3>
<p><a href="https://docs.docker.com/compose/how-tos/file-watch/">Use Compose Watch</a></p>
<p>Docker bind volumes gets a supercharge. Compose Watch does not replace bind mounts but exists as a companion specifically suited to developing in containers.</p>
<blockquote>
<p>More importantly, watch allows for greater granularity than is practical with a bind mount. Watch rules let you ignore specific files or entire directories within the watched tree.<br />
For example, in a Node.js project, it's not recommended to sync the node_modules/ directory. Even though JavaScript is interpreted, npm packages can contain native code that is not portable across platforms.</p>
</blockquote>
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