Vistarix Corporation retweeted
โฐ Before you could set five alarms on your phone and still hit snooze, getting up on time took a little more ingenuity.
More than 2,000 years ago, people were already finding ways to wake themselves up. Ancient water clocks helped mark time, mechanical alarms eventually became personal possessions, and in Britain and Ireland, some people even made a living knocking on windows to wake their neighbors. ๐
These professional morning callers were known as "knocker-uppers." Armed with tools ranging from long poles to pea shooters, they helped workers get to their jobs on time, long before alarm clocks became commonplace.
From elaborate clockwork to a hand reaching for snooze, we've come a long way in our quest to wake up on time. And yet, the struggle remains. ๐ด
How many alarms does it take to get you out of bed?
๐ Read the full story at the link: bit.ly/4yjOVgl
Vistarix Corporation retweeted
My full presentation of the Fall 2026 Flexport Tech Release from last week.
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Strategic perspectives for leaders building modern Go-to-Market organizations.
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Vistarix Corporation retweeted
The GTMAtlas Executive Brief Edition 23: '๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ ๐ถ๐ป ๐ ๐ผ๐๐ถ๐ผ๐ป: ๐๐ฒ๐๐ถ๐ด๐ป๐ถ๐ป๐ด ๐๐ฎ๐บ๐ฝ๐ฎ๐ถ๐ด๐ป๐ ๐ง๐ต๐ฎ๐ ๐ข๐ฟ๐ฐ๐ต๐ฒ๐๐๐ฟ๐ฎ๐๐ฒ ๐ง๐ต๐ฒ๐บ๐๐ฒ๐น๐๐ฒ๐' is out now.
lnkd.in/gpFdBgTn
Please read, like, comment, & share the article. #GTM #atlas
Vistarix Corporation retweeted
The GTMAtlas Executive Brief Edition 23: '๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ ๐ถ๐ป ๐ ๐ผ๐๐ถ๐ผ๐ป: ๐๐ฒ๐๐ถ๐ด๐ป๐ถ๐ป๐ด ๐๐ฎ๐บ๐ฝ๐ฎ๐ถ๐ด๐ป๐ ๐ง๐ต๐ฎ๐ ๐ข๐ฟ๐ฐ๐ต๐ฒ๐๐๐ฟ๐ฎ๐๐ฒ ๐ง๐ต๐ฒ๐บ๐๐ฒ๐น๐๐ฒ๐' is out now.
lnkd.in/gpFdBgTn
Please read, like, comment, & share the article. #GTM #atlas
Vistarix Corporation retweeted
๐๐
๐ฒ๐ฐ๐๐๐ถ๐๐ฒ ๐๐ฟ๐ถ๐ฒ๐ณ ๐๐ฑ๐ถ๐๐ถ๐ผ๐ป ๐ฎ๐ญ: ๐๐น๐ถ๐ด๐ป๐ถ๐ป๐ด ๐ฌ๐ผ๐๐ฟ ๐๐ง๐ ๐ง๐ฒ๐ฎ๐บ๐ ๐๐ผ ๐ ๐ผ๐๐ฒ ๐ฎ๐ ๐ข๐ป๐ฒ ๐ฅ๐ฒ๐๐ฒ๐ป๐๐ฒ ๐ฆ๐๐๐๐ฒ๐บ ๐ถ๐ ๐ผ๐๐ ๐ป๐ผ๐.
linkedin.com/pulse/aligning-โฆ
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Vistarix Corporation retweeted
So cool to see @Gemini_Notebook land at #9 in the new @a16z rankings of most popular consumer AI web apps. The team has been cranking! (And note that @Google is the only company with two AI products in top ten โ and four in the top twenty.)
In this weekโs ๐๐ง๐ ๐๐๐น๐ฎ๐ ๐๐
๐ฒ๐ฐ๐๐๐ถ๐๐ฒ ๐๐ฟ๐ถ๐ฒ๐ณ, we explore how to turn Marketing Qualified Campaigns (MQCs) into a repeatable, compounding market motion.
๐ Read this weekโs Executive Brief: linkedin.com/pulse/architectโฆ
#GTM #GTMOrchestration #GTMAtlas
Vistarix Corporation retweeted
โBecome a master of overcoming hard moments. That is the sign of a champion.โ
~ Roger Federer
We often talk about defining the Ideal Customer Profile. But the harder question is whether Marketing, Sales, Product, Customer Success, and RevOps are truly aligned around the same customer.
Youโve defined your ICP. But are you aligned around it?
gtmatlas.com/blog/the-icp-alโฆ
#GTM
Make every campaign count. Qualify the campaign before expecting it to qualify the lead.
๐ Read the full breakdown in The GTMAtlas Executive Brief, Edition 22: Qualifying Your Campaigns Before They Qualify the Lead:
linkedin.com/pulse/qualifyinโฆ
#GTM #GTMOrchestration #GTMAtlas
In the latest #GTMAtlas Executive Brief, we explore how GTM Strategy & Market Architecture helps leaders make better strategic decisions, align execution, and create lasting value for the business and its customers.
Explore the latest edition: linkedin.com/pulse/executiveโฆ
#GTM
Puddle Jumpers: Simple and Proven Ways to Raise Confident goodreads.com/book/show/2429โฆ via @goodreads
Keeping your GTM journey in motion gtmatlas.com/blog/keeping-yoโฆ
How to Predict Demand for Your New Product gtmatlas.com/blog/how-to-preโฆ
Vistarix Corporation retweeted
Whatโs happened is that we went from AI chat tools that were relatively cheap and had small context windows, to AI agents that have giant context windows, the ability to keep track of longer running work, and models that cost an order of magnitude more on inference because theyโre that much better.
This has compounded far faster than most realized (unless you were paying close attention at the middle or end of last year, which many here were), and the dollars flowing in now are much more real.
What follows is a continued march of AI capability that will continue to be used by anyone with a frontier use-case (like coding, sciences, finance, consulting) and then a peeling off of tasks to lower cost models that are capable enough for the job. Whereas we thought the cost of AI might converge on a single low price per token before, itโs clear the stratification is only widening based on the task you need performed.
This will be yet another component that has to be figured out for broad AI diffusion. Enterprises will need to put in programs, new finance teams, and technology solutions to manage this all. The labs and platforms that can ensure customers can price optimize for the task at hand will be in the best position.
๐ฆMicrosoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months. American AI software prices have jumped 20% to 37%, and GitHub (owned by Microsoft) is dropping flat-rate plans for usage-based billing across its products.
My Take
The AI subsidy era is ending in real time. The same company that put $13 billion into OpenAI and built the Azure infrastructure powering most of Anthropic's compute just looked at the bill from a competitor's coding tool and decided it was not worth paying. That is not a productivity failure on Anthropic's end. Token-based pricing is forcing every enterprise customer to confront the actual cost of running these models at scale, and the number turns out to be far higher than the flat-rate experiments suggested.
This ties directly to my Gemini Flash post yesterday. Anthropic, OpenAI, and Google all raised effective prices in the last six months. Enterprises that built workflows assuming AI costs would keep falling are now watching annual budgets evaporate in months. Two outcomes look likely from here. Either enterprises scale back AI usage to fit budgets, which slows the revenue ramp the labs need to justify their valuations ahead of IPOs, or the labs cut prices and absorb the losses, which makes the unit economics worse at exactly the wrong moment. Both paths land in the same place, the numbers stop working, and somebody has to take the writedown.
Hedgie๐ค
How to Predict Demand for Your New Product gtmatlas.com/blog/how-to-preโฆ
#DemandGeneration #GTMJourney #GTMAtlas
Vistarix Corporation retweeted
Replying to @BatsouElef
goodhandscap.com/ we help drive value for B2B businesses and will make equity investments as well



















