AI Efficiency

6 summarised stories about AI Efficiency, each linking back to the original source. Browse all topics →

Key players

OpenAI Doist Gonçalo Silva GPT-5.4 GPT-5.4 mini GPT-5.4 nano

Thursday, 6 August 2026

Why Todoist says less AI can deliver more

The New Stack 3 weeks ago 13

Todoist's parent company Doist adopted a philosophy of building AI features only when purposeful, rather than shipping every AI-enabled capability, with CTO Gonçalo Silva explaining that the company prototyped at least 18 AI ideas before settling on just a few to launch. The company plans to release Automations in August or early September, a feature that uses AI to interpret user requests into workflows but then executes them with traditional code rather than repeatedly invoking language models. By separating AI generation from reliable execution, Doist reduces costs, improves consistency, and maintains the ability to swap model providers without breaking user-facing behavior.

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Cost Optimization AI Efficiency

What are code reviews even for?

Engineering Enablement 3 weeks ago 13 ● 2 sources

AI coding tools at Meta and across the industry are generating code 106% faster than human reviewers can evaluate it, with review backlogs swelling into thousands of pending diffs. The core problem isn't defect detection—which accounts for only 14% of review comments—but knowledge transfer and shared understanding, which automated review threatens to erode into cognitive and intent debt. Organizations should use AI to automate only low-risk routine changes while protecting human review for high-judgment decisions that build team expertise and ownership.

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Developer Tools AI Coding Agents AI Efficiency Code Generation

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