cd /news/ai-agents/the-ai-wait-equation · home topics ai-agents article
[ARTICLE · art-131677] src=xendo.bearblog.dev ↗ pub= topic=ai-agents verified=true sentiment=↓ negative

The AI Wait Equation

A Big Tech engineer argues that developers who rush to build agentic tooling around current-generation AI models are wasting effort, citing friends who spent all of 2026 delivering agentic tooling "with a half-life of hydrogen-7 while delivering nothing for customers." The author invokes the Wait Equation from space travel to claim pragmatic engineers who use AI only to the extent it supports product work will pull ahead of early adopters. The piece concludes that readers should worry about being in front rather than being left behind.

read2 min views1 publishedSep 16, 2026
The AI Wait Equation
Image: Xendo (auto-discovered)

In space travel, there exists the concept of the Wait Equation [0]. It basically means that if you consider radical propulsion innovations and the resulting speed improvements, it may be better to wait before starting your journey. Excited travelers—early adopters—will lose time flying, while their pragmatic friends will wait on Earth and still arrive at the destination faster.

A similar thought experiment is relevant when it comes to adopting AI. Developers who heavily invest in AI too early spend their time working on tools and harnesses. They build complex agent orchestration frameworks whose sole purpose is to work around weaknesses of the current generation of models (I will have another post on how structuring teams of agents after human teams is dumb). They need to tune and tweak their workflows each time a new model is released. They nervously say that "coding is solved," while at the same time producing enormous and buggy codebases that outrun the models' reasoning capabilities [1]. Other, more pragmatic engineers may still use AI, but only to the extent that allows them to work on their products and features without the agentic mental masturbation. They still read their code, write it in small chunks, and steer the models to build proper, human-compatible abstractions. They learn, they build products, and they focus on customers. They are not rewriting stuff in Rust just because it's possible. They still benefit from all improvements in LLMs and coding harnesses, but at the same time, the products they build and the experience they gain are what pull them ahead. Unless your work is to build agentic tooling, you shouldn't.

Working in Big Tech, I believe this thought experiment accurately describes what's happening. Several friends of mine spent all of 2026 working hard on delivering agentic tooling with a half-life of hydrogen-7 while delivering nothing for customers.

I wrote before that you shouldn't be worried about being left behind. Now I've changed my mind. You should be worried about being in front. As William Wallace would say: Hold!

[0] https://en.wikipedia.org/wiki/The_Wait_Equation

[1] https://x.com/Steve_Yegge/status/2094947586373505122?s=20
── more in #ai-agents 4 stories · sorted by recency
── more on @william wallace 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
Live at https://your-agent.zahid.host
Get free account → Pricing
from €0/mo · no card required
LIVE [news/the-ai-wait-equation] indexed:0 read:2min 2026-09-16 ·