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AI code generation complicates technical due diligence for software products

By PulseAugur Editorial · [1 sources] ·

A seasoned software engineer with decades of experience and a successful startup exit highlights the evolving challenges of technical due diligence for AI-built products. While core questions about maintainability, security, and ownership remain constant, the rapid pace of AI-driven code generation now outpaces traditional documentation, testing, and record-keeping, creating new gaps for buyers to uncover. This shift necessitates a deeper, more nuanced approach to evaluating AI-generated software. AI

IMPACT AI-generated code is creating new challenges for software due diligence, requiring updated evaluation methods for maintainability, security, and ownership.

RANK_REASON The item is an opinion piece from an individual with relevant experience discussing the implications of AI on software development practices.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI code generation complicates technical due diligence for software products

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3 / 100
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The item is an opinion piece from an individual with relevant experience discussing the implications of AI on software development practices.
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · Kevinhorek ·

    Technical due diligence on an AI-built product. My background: 30 years, 50+ shipped platforms, and a startup I sold to EBSCO. The questions don't change: can t

    Technical due diligence on an AI-built product. My background: 30 years, 50+ shipped platforms, and a startup I sold to EBSCO. The questions don't change: can the buyer's team maintain it, how secure is it, and does the company own it. What changes is where the gaps hide, because…

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