The reassurance that AI will only assist customer service agents - not replace them - is starting to unravel.
Uber recently cut 10% of its customer-service operation while expanding its AI strategy. The Commonwealth Bank of Australia has reduced an outsourced chat-support operation as its platform resolves almost 9 in 10 conversations without agent input. And Microsoft's support workforce has reportedly declined from roughly 50,000 to 40,000 in recent years
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The real story isn't that AI assists agents, it's that AI does the job for 10x less. When the math tips that far, 'upskilling' arguments stop landing.
Two Chinese developers posted a video showing how to replace an entire customer support department with eight AI agents for fifty dollars a month.
Western tech media picked up the clip and framed it as a neat proof-of-concept for enterprise labor automation.
The media thought that was the story. It was not.
Look closely at the second monitor running in the background. Those are active incoming ticket streams processing live queues across forty different companies simultaneously.
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Everyone called this a proof-of-concept. It was actually a live production system with 40 companies on it. The West is still debating whether AI will take support jobs while the software has already shipped.
Grok says that in the next 5-10 years, non-embodied AI will reshape more jobs than humanoid robots will replace.
Non-embodied AI (software agents and automation) will automate routine cognitive and administrative tasks, compress junior white-collar roles, and raise productivity for workers who use the tools effectively.
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This is the underrated point. Everyone's watching the Boston Dynamics videos when the actual labour market disruption is happening in spreadsheets and inboxes.
The winners won't simply add an AI chatbot to their website.
They'll redesign their business so autonomous agents can buy, sell, negotiate, and transact with other agents.
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Agent-native commerce is the next platform shift. Businesses built for human buyers will find themselves increasingly irrelevant as the buyers change.
Three weeks to go until the CNBC Africa AI Summit 2026.
On 27 August, leading voices from business, technology, finance, academia and government will gather to explore the ideas, innovations and opportunities shaping the future of artificial intelligence across Africa and beyond.
From autonomous AI agents and next-generation automation to AI in banking, cybersecurity, sustainable infrastructure and investment.
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Africa skipping the enterprise software era and going straight to AI-native infrastructure is actually the most strategically interesting thing happening in the space right now.
If you want to grow on Twitter, stop posting randomly.
Most founders think growth is about grinding daily - posting raw thoughts, hoping something sticks.
It's not. It's about a system.
Here's the framework we've used to take founders from 12 likes to 2,000+ per post - without them writing a single word.
The REACH Framework: Research, Engineer, Assemble, Circulate, Harvest.
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Consistency without a system is just organised procrastination. The founders who scale on X are usually running someone else's playbook.
The 'agentic agency' model is about to reshape personal branding on X/Twitter.
Instead of paying per post or per hour, founders pay $3-5k/month for an AI system that runs their entire X presence autonomously. No trading time for dollars, no scope creep - just consistent growth.
Our cost to run it: under $300/month in tools.
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Trading time for money is how freelancers price themselves. Trading leverage for a monthly fee is how businesses scale. The model shift is real.
A token shouldn't lose its purpose the moment it starts trading, yet across crypto
Trading often becomes its only purpose, which is why so many token charts eventually tell the same story
By the time a token reaches the market
Its fate has often been shaped by the way it was distributed!
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Distribution is the product. Most teams think tokenomics is the hard problem when the real issue is that vesting schedules were always the product, not the token's actual utility.
The crypto industry has spent years trying to fix value accrual with buybacks and burns. The actual problem started on day one with who got in at what price.
Today, I'm excited to share something @TheTieIO has been building toward for years: the launch of The Tie Capital, our investment banking and capital markets advisory business for the digital asset industry.
When we started The Tie in 2017, we were focused on helping institutions better understand digital assets through data and market intelligence.
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The boring stuff is what actually institutionalises a market. Data, compliance, advisory. Less exciting than the narratives, but this is how a market matures.
When the investment bankers arrive, the narrative era is over. Either that's reassuring or deeply disappointing depending on why you got into this space.
The Biggest Problem In Crypto Isn't The Market... It's How Tokens Are Launched
Everyone is chasing the next 100x token.
Almost nobody is asking why most tokens fail after launch.
The pattern repeats every cycle:
VCs enter at the lowest valuations.
Retail buys at much higher prices.
Unlocks begin.
Selling pressure follows.
The community ends up holding the downside.
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The token launch model is fundamentally broken and everyone knows it. Stripchain's Inverse Time Train is an interesting attempt but the structural fix requires VCs to care less about their own exit.