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Chronicles

The story behind the story

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VA used a DOGE AI tool by Gumroad founder Sahil Lavingia that hallucinated contract sizes to cancel 24+ deals; Lavingia says “mistakes were made”

We obtained records showing how a Department of Government Efficiency staffer with no medical experience used artificial intelligence to identify which VA contracts to kill.

ProPublica

Context & Ripple Effects

The report follows Sahil Lavingia’s brief, publicly discussed role as a DOGE software engineer at the VA, including his account that he was removed after a Fast Company interview; it now supplies a concrete operational consequence of that work in the earlier account of his VA assignment.

It also sits alongside DOGE’s broader push to use generative AI in federal administrative work, including a reported effort to build GSAi for contract and procurement analysis for procurement analysis at the GSA. The VA case makes the quality-control problem tangible: an AI output became part of a decision process affecting live agreements.

First-order effects

  • More than 24 VA deals were canceled after the tool’s analysis, while hallucinated contract-size information distorted the basis for at least some of those decisions.
  • The VA and the affected vendors face immediate reconciliation of which cancellations relied on erroneous AI-derived figures and whether the underlying reviews support those decisions.

Second-order effects

  • Procurement teams using AI to triage contracts will face pressure to separate model-generated summaries from verified contract records before acting on recommendations.
  • DOGE’s wider government-AI agenda may encounter greater scrutiny over review workflows, domain expertise, and accountability when tools are used to recommend cuts rather than merely summarize data.

Third-order effects

  • If agencies continue deploying generative AI in procurement and program administration, human verification of high-consequence outputs is likely to become a core requirement of state AI procurement rather than an optional safeguard.
  • The episode points to a structural tension in public-sector automation: tools designed to accelerate spending cuts can transfer error costs to agencies, contractors, and service delivery unless decision authority remains auditable.

The trend: Government adoption of generative AI is moving from productivity experiments into consequential administrative decisions, making governance and verification as important as deployment speed.

Discussion

  • @charlesornstein Charles Ornstein on bluesky
    Experts who reviewed the code a DOGE employee used to identify VA contracts to cut found numerous and troubling flaws, providing a disturbing glimpse into how the Trump administration is allowing artificial intelligence to guide critical cuts in services.
  • @smcgrath.phd Scott McGrath on bluesky
    DOGE's reckless deployment of half-baked AI tools is going to make things worse.  —  Examples DOGE's haphazard AI use risks becoming the definitive, negative narrative on AI, thereby undermining efforts for ethical and safe AI deployment and overshadowing any potential benefits a…
  • @dzaia40 Dave Czaja on bluesky
    “I think that mistakes were made.  I'm sure mistakes were made.  Mistakes are always made.  I would never recommend someone run my code and do what it says.  —  www.propublica.org/article/trum...
  • @bxroberts.org Brandon Roberts on bluesky
    6/ You can see his code for yourself.  —  We broke down the prompts Lavingia used in detail here:  —  www.propublica.org/article/insi...
  • @kwcollins Kevin Collins on bluesky
    The same day the Hard Fork posts a very friendly interview with a former DOGE employee, @propublica.org actually investigates his specific work ... and finds that it was poorly done (none of which came up in the Hard Fork pod) www.propublica.org/article/insi...
  • @markriedl Mark Riedl on bluesky
    Oh.  My.  Fucking.  God.  —  This is part of the prompt used to identify Veterans Affairs contracts that should be canceled, or, using the very-much non-technical term “munched”.  —  www.propublica.org/article/insi...  [image]
  • @jongreen Jon Green on bluesky
    Everyone loves Milkshake DOGE, the disaffected DOGE developer who just wanted to write some useful code for the government to save money on wasteful contracts  —  [two weeks later]  —  We regret to inform you that the developer's prompt engineering is for shit www.propublica.org/…
  • @jkuenzie Jack Kuenzie on bluesky
    ProPublica's in-depth look at how DOGE bungled AI-driven analysis of VA spending.  Starts with Trump's ridiculous one-month deadline to review and flag all contracts.  —  www.propublica.org/article/insi...
  • @willoremus.com Will Oremus on bluesky
    good example of how AI hype can have damaging real-world consequences [embedded post]
  • @justinhendrix Justin Hendrix on bluesky
    “ProPublica obtained the code and the contracts it flagged from a source and shared them with a half dozen AI and procurement experts.  All said the script was flawed.  Many criticized the concept of using AI to guide budgetary cuts at the VA, with one calling it ‘deeply problema…
  • @karlbode.com Karl Bode on bluesky
    again, if you squint real hard and turn your head just right, you may be able to detect a theme [embedded post]
  • @nrvscrcts David William on bluesky
    “The experts found numerous and troubling flaws: the code relied on older, general-purpose models not suited for the task; the model hallucinated contract amounts...; and the AI did not analyze the entire text of contracts.”
  • @themorrancave Chris Morran on bluesky
    New: A DOGE staffer developed an AI tool to review Veterans Affairs contracts.  —  But there was a slight hitch.  —  It hallucinated the size of those deals.  —  For example, it concluded that more than a thousand contracts were each worth $34M, when in fact some were for as litt…
  • @astro_jcm@mastodon.online @astro_jcm@mastodon.online on mastodon
    “I think that mistakes were made,” said Lavingia, who worked at DOGE for nearly two months.  “I'm sure mistakes were made.  Mistakes are always made.  I would never recommend someone run my code and do what it says.  It's like that ‘Office’ episode where Steve Carell drives into …
  • r/technology r on reddit
    DOGE Developed Error-Prone AI Tool to “Munch” Veterans Affairs Contracts
  • r/fednews r on reddit
    DOGE Developed Error-Prone AI Tool to “Munch” Veterans Affairs Contracts