Tom’s Hardware reports Uber leaders are questioning whether rising AI token spend is translating into shipped features and measurable productivity.
As agentic tools multiply calls behind the scenes, usage-based billing can surge faster than impact. Execs are starting to demand ROI signals instead of “use more AI” KPIs.
Treat tokens like cloud spend: instrument cost per workflow, set per-team budgets, and tie “AI usage” to outcome metrics (deploys, tickets, revenue touches) so loops don’t run unchecked.
Uber’s COO says the link between more token usage and more useful product isn’t clear yet.
langfuse/langfuse
Open-source LLM engineering platform for observability, traces, metrics, evals, prompt management, datasets, and playground workflows.
promptfoo/promptfoo
A CLI and CI workflow for testing prompts, agents, and RAG systems across models, with evals and red-team style checks.
stanfordnlp/dspy
A framework for programming and optimizing language-model pipelines rather than hand-tuning one prompt at a time.
Microsoft EVP Jay Parikh told staff that tokenmaxxing is not the goal, giving divisions AI token budget targets as of July 2026 and making OpenAI's cheaper GPT-5.6 the default model for internal use.
Guardian Australia saw an internal memo: Atlassian gave R&D staff monthly AI “wallets” of $500 to $2,000 spanning four tools including Claude Code. Alerts fire near the cap, usage pauses at zero, and no top-up has been refused yet.
AP reports the tokenmaxxing fad is buckling as costs climb without matching productivity. Moody's AI analytics head Vincent Gusdorf, author of a new report, says bills piled in and teams realized the tools need disciplined use.