Le texte que vous vous allez découvrir est le fruit de mon travail de veille, de recherche et de vulgarisation quasi-quotidien depuis plus d'un an.
Je le partage dans l'espoir de proposer un modèle unifié, politiquement exploitable pour :
Comprendre la bulle de l'IA et le système financier, leurs mécanismes de fonctionnement et d'effondrement, et leurs conséquences
Nous organiser et mener des changements systémiques afin que cela n'arrive plus
Il commence par une synthèse du contexte : évènements des derniers mois, acteurs, exemples… Ensuite, il dézoome progressivement en répondant à des questions successives sur les notions d'éclatement et d'infrastructure, puis sur le déroulé de l'éclatement de la bulle pour arriver à la rupture du système financier et à ses conséquences possibles sur nos vies.
La dernière partie propose des outils pour commencer à nous positionner individuellement et nous organiser collectivement afin de changer les choses.
Toutes les notions importantes sont (normalement) expliquées et contextualisées au fur et à mesure.
N'hésitez pas à utiliser le sommaire pour vous repérer, bonne lecture !
Note : si vous avez découvert et apprécié ce texte dans sa forme première sur Mastodon, sachez que vous avez ici affaire à une version retravaillée en profondeur, avec notamment une nouvelle section sur la notion de redondance dans le système financier et le rôle de l'inflation comme carburant de la crise.
The $20 AI subscription you use every day is a mathematical impossibility. While you enjoy flat-rate access to advanced tools like Claude Code, the raw compute costs for a power user can actually skyrocket to $15,000 a year. We are officially living inside the "AI Uber Moment", a temporary illusion completely subsidized by venture capitalists who are bleeding billions just to get you hooked. But as tech giants resort to hidden financial loops and "stealth-nerfing" your favorite chatbots to survive, the money is officially running out.
Chapters:
- 00:00 - The Trillion Dollar House of Cards
- 00:36 - Chapter 1: The $20 Illusion
- 02:38 - Chapter 2: The Ghost Of Uber
- 05:03 - Chapter 3: The Claude Code Math
- 05:56 - Chapter 4: The Search Penalty
- 08:08 - Chapter 5: The Round Trip Scam
- 09:35 - Chapter 6: The Hardware Debt Trap
- 11:58 - Chapter 7: The Stealth Nerf
- 13:21 - Chapter 8: The 2026 Mass Extinction
- 15:02 - Chapter 9: The Great AI Rug Pull
Narrated by: Josh Risser
"Tokenmaxxing" is the latest corporate trend taking over the tech world, but is it actually measuring developer productivity—or is it just burning a monumental hole in company finances?
In this episode of Internet of Bugs, Carl breaks down the origins of tokenmaxxing, from Jensen Huang’s podcast comments to prestigious VC letters pushing AI-driven developer metrics. We explore the terrible history of trying to measure programmer productivity (like counting lines of code), how Goodhart's law ruins these systems, and why massive tech companies might actually be incentivizing this slop just to train their own internal AI models.
Furthermore, we look at the financial reality of the AI bubble, upcoming tech IPOs, and why shipping dead code or hiding bugs behind feature flags can cause catastrophic real-world losses (like the 2012 Knight Capital Group meltdown).
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- 00:00 What is "Tokenmaxxing"?
- 00:55 Where the Trend Started (Nvidia & VCs)
- 02:03 The Nightmare of Corporate Token Leaderboards
- 02:24 How Do We Actually Measure Good Code?
- 03:52 Lines of Code, Story Points, and Failed Metrics
- 05:01 Goodhart's Law & Gaming the System
- 05:39 Why Big Tech Wants You Burning Tokens
- 06:49 The Superstitions of Software Engineering (LeetCode & Agile)
- 07:55 The Danger of Dead Code & The $440M Bug
- 09:17 The Real Solution
- 10:47 The AI Bubble's "Groundhog Day" IPO Forecast
#Tokenmaxxing #SoftwareEngineering #AIBubble #DeveloperProductivity #TechTrends #Programming #TechIndustry #InternetOfBugs
// Sources
// Origins
https://the-decoder.com/nvidia-ceo-je...
https://www.nytimes.com/2026/03/20/te...
https://a16z.com/there-are-only-two-p...
https://finance.yahoo.com/news/a16z-u...
https://www.notboring.co/p/a16z-the-p...
https://en.wikipedia.org/wiki/Andrees...
// What companies are doing
/ metas_internal_leaderboard_ranks_employees...
https://fortune.com/2026/04/09/meta-k...
https://www.bbc.com/news/articles/cvg...
https://www.firstround.com/ai/shopify
https://gaiinsights.com/blog/the-ceo-...
https://help.shopify.com/en/manual/sh...
https://www.forrester.com/blogs/what-...
https://www.businessinsider.com/amazo...
https://aws.amazon.com/blogs/machine-...
https://aws.amazon.com/blogs/machine-...
// Programming History Mentioned
https://maseconomics.com/goodharts-la...
https://dl.acm.org/doi/10.1145/362929...
https://junit.org/
https://www.henricodolfing.ch/en/case...
https://blog.statsig.com/how-to-lose-...
// AI limitations
https://epoch.ai/blog/will-we-run-out...
// Tokenmaxxing backlash
https://www.tomshardware.com/tech-ind...
https://news.ycombinator.com/item?id=...
https://www.businessinsider.com/uber-...
// Financial irregularities (just the most recent tip of the massive iceberg)
https://www.wheresyoured.at/anthropic...
https://www.thestreet.com/latest-news...
https://www.datacenterdynamics.com/en...
https://techcrunch.com/2026/05/20/ant...