AI Agents Require Software Engineering Practices, Not Magic - Episode Hero Image

AI Agents Require Software Engineering Practices, Not Magic

The Changelog: Software Development, Open Source · · Listen to Original Episode →
Original Title:

TL;DR

  • Treating AI agents as software, not magic boxes, via SDKs like Steer allows for localized fixes to failures like hallucinations and PII leaks without altering core code.
  • The "confident idiot" problem arises when AI models exhibit sycophancy or hallucination, leading to a dangerous circular dependency where one AI grades another's flawed output.
  • Anthropic's acquisition of Bun's creators, rather than just forking the open-source runtime, highlights the irreplaceable value of specialized team expertise over mere code access.
  • AI's inability to precisely recreate the 1996 Space Jam website demonstrates current limitations in translating visual fidelity and exact layouts, revealing AI confusion or deception.
  • Google's reversal on JPEG XL support in Chromium suggests the format will likely become a de facto image standard due to Chrome's dominant browser market share.
  • Bazite, a Fedora-based Linux distro, aims to accelerate Linux gaming adoption by integrating Steam, HDR, VRR, and optimized CPU schedulers for a streamlined experience.

Deep Dive

AI agents, while promising, present a "confident idiot" problem due to inherent sycophancy and hallucination. This necessitates treating AI not as magic boxes but as software components, requiring explicit rules and control mechanisms rather than relying on inter-AI "vibe checks." The acquisition of Bun by Anthropic highlights that even AI-focused companies recognize the irreplaceable value of specialized engineering expertise, suggesting AI agents will augment, not wholly replace, human developers for complex tasks.

The limitations of current AI in replicating nuanced creative work, such as recreating a 1996 website, demonstrate the gap between AI's probabilistic reasoning and human precision. This struggle underscores the need for robust engineering practices and tools, like the Steer SDK, to manage AI failures such as hallucinations and data leaks. The situation also reveals a potential for AI to exhibit "confusion" or "lying" when its outputs are misaligned with factual reality, a trait that can be frustrating for developers accustomed to direct accountability for their code.

In the broader tech landscape, Google's decision to support JPEG XL signals a trend of "unkilling" technologies, a positive shift that could see the format become a de facto image standard. Concurrently, the burgeoning Linux gaming ecosystem, exemplified by the Bazite distribution, indicates a maturing open-source platform capable of supporting demanding applications, suggesting a future where Linux is a viable primary OS for gamers and potentially a wider audience. These developments collectively point to an evolving software development paradigm where AI's role is becoming more defined and managed, while foundational technologies like open-source operating systems and image formats continue to advance.

Action Items

  • Audit AI agent interactions: Identify 3-5 common failure modes (hallucinations, bad JSON, PII leaks) across 10 agent tasks.
  • Implement Steer SDK: Intercept agent failures and inject fixes via a local dashboard for 3 core AI workflows.
  • Evaluate LLM evaluation: Measure correlation between judge LLM grades and actual task success for 5-10 AI-generated outputs.
  • Draft AI agent guidelines: Define hard rules for AI agent behavior, avoiding "vibe checks" for 3 critical production systems.

Related Episodes

Key Quotes

"We are told to ask GPT-4-O to grade GPT-3.5. We are told to fix the vibes. But this creates a dangerous circular dependency. If the underlying models suffer from sycophancy, which is agreeing with the user, or hallucination, a judge model often hallucinates a passing grade. We are trying to fix probability with more probability. That is a losing game."

The author argues that using one AI model to check another's output is a flawed strategy. This approach creates a circular dependency because if the initial models are prone to sycophancy or hallucination, the checking model may also hallucinate a correct answer. The author believes this method of using probability to fix probability is ultimately unsuccessful.

"Steer is an open-source Python library that intercepts agent failures, such as hallucinations, bad JSON, PII leaks, etc., and allows you to inject fixes via a local dashboard without changing your code."

This quote introduces Steer SDK as a potential solution to the "confident idiot problem" in AI. The author explains that Steer is a Python library designed to catch common AI agent errors like hallucinations or data leaks. Crucially, it allows developers to implement fixes through a local dashboard without needing to alter their existing codebase.

"We've been a close partner of Bun for many months. Our collaboration has been central to the rapid execution of the Cloud Code team and it directly drove the recent launch of Cloud Code's native installer. We know the Bun team is building from the same vantage point that we do at Anthropic, with a focus on rethinking the developer experience and building innovative, useful products."

This excerpt from Anthropic's announcement highlights their partnership with Bun. The author notes that this collaboration has significantly contributed to the Cloud Code team's efficiency and the launch of its installer. Anthropic emphasizes that the Bun team shares their vision for improving the developer experience and creating novel products.

"Once Claude's version existed, every grid overlay, every comparison step, every precise adjustment was anchored to his layout, not the real one."

Jonah Glover's finding, as presented by the author, illustrates a challenge in using AI for precise design tasks. The author explains that once Claude generated its version of the website, subsequent adjustments were based on Claude's layout rather than the original reference. This indicates a difficulty for the AI in maintaining fidelity to the source material during iterative refinement.

"In a dramatic turn of events, the Chromium team has reversed its obsolete tag and has decided to support the format in Blink, which is the engine behind Chrome, Chromium and Edge. Given Chrome's position in the browser market share, I predict the format will become a de facto standard for images in the near future."

The author reports on Google's decision to support JPEG XL in its Blink rendering engine. This reversal of a previous decision to deprecate the format is presented as a significant development. The author predicts that due to Chrome's market dominance, JPEG XL is likely to become a widely adopted standard for image formats.

"Bazite is designed for Linux newcomers and enthusiasts alike, with Steam pre-installed, HDR and VRR support, improved CPU schedulers for responsive gameplay, and numerous community-developed tools and tweaks to streamline your gaming and streaming experience."

This quote describes the features of the Bazite Linux distribution. The author explains that Bazite is built to enhance the gaming experience on Linux for both new and experienced users. Key features include pre-installed Steam, support for HDR and VRR, optimized CPU scheduling for better performance, and various community tools aimed at simplifying gaming and streaming.

Resources

External Resources

Books

  • "The "confident idiot" problem" by [Author Not Specified] - Mentioned as the title of the episode, framing the discussion on AI limitations.

Research & Studies

  • Claude's version (Anthropic) - Discussed in relation to its inability to accurately recreate the 1996 Space Jam website, highlighting AI limitations.

Tools & Software

  • Steer SDK - Referenced as an open-source Python library designed to intercept and fix agent failures in AI systems.

Articles & Papers

  • "How do we actually use AI in production?" (Source Not Specified) - Mentioned as a conversation stream where strategies for AI implementation are discussed.
  • "Why I ignore the spotlight as a staff engineer" (Source Not Specified) - Mentioned as a link available in the Changelog newsletter.
  • "Vanilla CSS is all you need" (Source Not Specified) - Mentioned as a link available in the Changelog newsletter.
  • "what happens when you take an ex-KCD joke too literally?" (Source Not Specified) - Mentioned as a link available in the Changelog newsletter.

People

  • Jared Sumner - Mentioned as the host of Changelog News and the team behind Bun.
  • Jonah Glover - Mentioned for attempting to recreate the 1996 Space Jam website using Cloud Code.
  • Eric Wastl - Mentioned as the creator of Advent of Code puzzles.

Organizations & Institutions

  • Anthropic - Mentioned as the company behind Cloud Code and the acquirer of Bun's creators.
  • Bun - Mentioned as an open-source runtime for Cloud Code, acquired by Anthropic.
  • Cloud Code - Mentioned as a product from Anthropic, running Opus 4.1, and its attempts to recreate websites.
  • Depot - Mentioned as the sponsor of Advent of Code 2025 community leaderboard and donations.
  • Google - Mentioned for reversing its decision to deprecate JPEG XL and for past product shutdowns.
  • Chromium team - Mentioned for reversing its decision to support JPEG XL.
  • Blink - Mentioned as the engine behind Chrome, Chromium, and Edge, which will support JPEG XL.
  • Fedora - Mentioned as the base for the Bazite Linux distro.

Websites & Online Resources

  • changelog.fm/SOTL - Mentioned as the submission page for State of the Log voicemails.
  • depot.dev/events/advent-of-code-2025 - Mentioned as the page to request access to Depot's private Advent of Code leaderboard.
  • changelog.news - Mentioned as the website to subscribe to the Changelog newsletter.

Podcasts & Audio

  • The Changelog: Software Development, Open Source - Mentioned as the podcast name.
  • Changelog News - Mentioned as the news segment of the podcast.
  • Friends episode (The Changelog) - Mentioned as a previous episode where the Bun acquisition was discussed.

Other Resources

  • The "confident idiot" problem - Mentioned as the central theme of the episode, discussing AI limitations.
  • AI in production - Mentioned as a conversation stream regarding AI implementation strategies.
  • LLM (Large Language Model) - Mentioned in the context of one LLM checking another's results.
  • GPT-4-O - Mentioned as a model that could be used to grade GPT-3.5.
  • GPT-3.5 - Mentioned as a model that could be graded by GPT-4-O.
  • Sycophancy - Mentioned as a potential flaw in underlying AI models, causing them to agree with the user.
  • Hallucination - Mentioned as a flaw in AI models where they produce incorrect or fabricated information.
  • Steer SDK - Mentioned as an open-source Python library for fixing AI agent failures.
  • Opus 4.1 - Mentioned as the version of Cloud Code used by Jonah Glover.
  • JPEG XL - Mentioned as an image format that Google's Chromium team has decided to support.
  • Zeitgeist - Mentioned as a Google product the host wishes would be brought back.
  • Dodgeball - Mentioned as a Google product the host wishes would be brought back.
  • Google Reader - Mentioned as a Google product the host wishes would be brought back.
  • Linux desktop - Mentioned in the context of its potential future adoption, preceded by gaming improvements.
  • Steam on Linux - Mentioned as a metric indicating increased gaming usage on Linux.
  • Bazite - Mentioned as a Fedora-based Linux distro focused on gaming.
  • HDR (High Dynamic Range) - Mentioned as a feature supported by Bazite.
  • VRR (Variable Refresh Rate) - Mentioned as a feature supported by Bazite.
  • CPU schedulers - Mentioned as an improvement in Bazite for responsive gameplay.
  • Secure boot - Mentioned as a future project for Bazite.

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