The AI Productivity Trap

We're drowning in AI tools that promise to make us faster, but the real challenge is knowing when to slow down.

Your AI Coding Assistant Is Secretly Slowing You Down

The promise of 10x speed is creating a productivity paradox, and nobody is talking about the cost of mindless approval.

An AI coding assistant turned a two-week project into a two-month nightmare for one developer. The reason? Mindlessly approving the AI's suggestions. It’s a cautionary tale about the promise of speed versus the reality of software development, where unchecked velocity can lead you straight off a cliff.

This isn't an indictment of the tools, but of our approach to them. AI assistants are brilliant goldfish; they lack the deep, implicit context of a sprawling codebase or the nuance of a team's coding style. The data backs this up, with developers only accepting around 44% of AI suggestions. The real bottleneck isn't code generation, it's the critical, human-led work of review, integration, and validation that follows.

The takeaway is to treat AI suggestions as a starting point, not gospel. The strategy isn't buying a better tool, it's building a better process around it—one that prioritises mindful approval and rigorous review. AI should augment your intelligence, not replace your judgement.

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Your New AI Teammates

While some assistants introduce friction, a new wave of tools aims to become a more complete partner in the development lifecycle.

Kilo Code: The open-source AI agent for JetBrains

Kilo Code's move into JetBrains isn't just about another IDE. It's about shifting the AI assistant from a simple code-completer into a multi-skilled agent for architecture, debugging, and orchestrating complex tasks.

DevTools MCP: Autonomous AI agents for debugging

This framework for creating multi-agent AI systems hints at the future of development. It’s about building autonomous debugging squads that diagnose and fix issues without constant human hand-holding.

VibeSDK: A platform to build AI coding platforms

Cloudflare's VibeSDK lets you build your own AI coding platform with a single click. This is the ultimate meta-move: don't just use AI assistants, build the factory that makes them.

AI Is Eating Your Workflow

The next generation of AI isn't just in your IDE; it's showing up in your meetings, analytics, and even your text messages.

Poke.com: Your AI assistant, now in your texts

Poke embeds an AI assistant directly into iMessage and SMS, managing emails and meetings from your chats. This is about 'invisible AI' that works where you are, rather than making you switch contexts.

Orito: The AI meeting agent with 'sound awareness'

This AI meeting agent claims to detect tone and translates 66 languages. It's a leap from just transcribing what was said to understanding *how* it was said, a crucial step for global teams.

Murmur Lab: The AI Product Manager in your workspace

Murmur Lab is an AI product manager that scours social channels for customer insights. The interesting bit is AI moving upstream from code creation to influencing product strategy and discovery.

Quick hits

Creatium: Make interactive learning that doesn't suck
An AI-powered toolkit to build interactive training courses that people might actually finish, using gamification and role-playing scenarios.

Kora: Your personal AI philosopher
Get philosophical advice from history's greatest minds like Socrates and Marcus Aurelius through an AI-powered voice chat app.

AI Search Crawler Check: Is your site invisible to AI?
Before you blame your SEO, check if you're accidentally blocking ChatGPT or Claude with this simple robots.txt analysis tool.

My takeaway

The real skill in the age of AI isn't using the tools, but knowing when not to.

We're obsessed with the velocity AI promises, measuring output in lines of code or features shipped. But the paradox is that moving faster without direction just gets you to the wrong place sooner. The most valuable developers will be the ones who can apply critical thinking and strategic slowness to AI-generated chaos.

This forces us to redefine productivity from raw output to meaningful progress. We need to build systems for mindful approval and reward deep work, not just fast work. The ultimate competitive advantage won't be who has the best AI, but who has the best judgement.

What's one part of your workflow you're intentionally keeping human-only?

Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().