Stop reacting to the news cycle. Start driving it. ⚡
Strategic communication for political and corporate leaders who demand results.
See how we work: https://t.co/kWIzUAIeTh
#CommsLytics#CampaignStrategy#ReputationManagement
Campaigns don't fail from lack of effort. They fail from lack of intelligence.
Commslytics builds the data-driven communications strategy behind Kenya's next generation of political leaders. Insight before impact.
I started @CommsLytics because I saw a gap — campaigns rich in passion but poor in factual data.
AI is closing that gap faster than anyone expected. The future of African political comms is here.
Your opponent is still doing politics the old way. AI is rewriting the rules — from social listening to narrative strategy.
The 2027 race will be won in the data layer. Are you ready?
Your opponent is still doing politics the old way. AI is rewriting the rules — from social listening to narrative strategy.
The 2027 race will be won in the data layer.
Are you ready?
Political communication isn't about being the loudest voice in the room.
It's about being the most trusted one.
That's the difference between noise and influence.
#DigitalPolitics#PoliticalComms
It was great joining Njideka Akunyili Crosby — a gifted Nigerian-born, Los Angeles-based artist — to unveil our first portrait together. This piece reflects so many chapters of Michelle and my story, and we’re thrilled that it will be on display in the Hope and Change lobby at the Obama Presidential Center starting this Juneteenth.
Meanwhile, someone in Nairobi is busy planning meetings in tents — speaking to empty chairs.
The people chose a different address. 📍Thika.
#LindaMwananchi
Today, we’re breaking down a term you may have heard in climate conversations: green premium.
So what is a green premium?
A green premium is the additional cost of choosing a cleaner, more sustainable option over a more polluting one.
For example:
• Electric vehicles compared to fuel cars
• Clean cooking solutions compared to charcoal
• Renewable energy compared to fossil fuels
In many cases, the greener option is still more expensive. That price gap is what we call the green premium.
Why does this matter?
Because it explains one of the biggest barriers to climate action. If sustainable options are not affordable, adoption slows down, especially in developing economies.
So how do we reduce the green premium?
• Invest in innovation to lower costs over time
• Scale production to make solutions more accessible
• Use public finance and subsidies to reduce upfront costs
• Create policies that support green industries
For countries like Kenya, reducing the green premium is key to scaling clean energy, clean transport, and climate smart solutions.
Climate action cannot remain a luxury. It has to be practical, accessible, and affordable.
That is how real transition happens.
#MazingiraMonday #ClimateFinance #GreenPremium #AfricaClimate #Sustainability
Behind every political message that lands, someone ran the counter-narratives first. Stress-tested the framing. Mapped the attack vectors.
The visible 10% is the tweet. The invisible 90% is the brief.
This is no longer about leaders.
It's about citizens reclaiming their voice.
Thika, we are coming.
📍Sunday, 14th June 2026
Bring your hopes. Bring your frustrations. Bring your ideas.
#LindaMwananchi
There’s a growing need to support locally led climate solutions across Africa, and opportunities like the AFR100 Direct Beneficiary Grants 2026 are helping make that possible.
The Food and Agriculture Organization (FAO), with support from the Government of Germany, has launched this call to empower local organizations actively working on forest and landscape restoration. These grants provide funding ranging from $5,000 to $50,000 for practical, on-the-ground initiatives that restore degraded land and strengthen community-led green economies.
How to apply:
Applications are submitted online via the official portal. Eligible entities including Community-Based Organizations (CBOs), youth groups, women's groups, and agricultural cooperatives, must provide a project proposal mapping out concrete restoration outcomes, community engagement, and a sustainable budget.
Timeline:
The application window is open, with a firm submission deadline of June 19, 2026.
Why it matters:
While large-scale climate commitments make headlines, the real work happens at the grassroots. Funding community nurseries, agroforestry, and local value chains ensures that environmental restoration directly drives climate resilience and sustainable livelihoods where it is needed most.
#ClimateFinance #LandscapeRestoration #AFR100 #AfricaClimate
Quick observation: if everyone uses AI for graphic design, everything starts looking the same.
And when everything looks the same — nothing stands out.
The creative eye of a skilled designer isn't a nice-to-have. It's the whole point.
Microsoft just banned its own engineers from using AI.
The tool was literally costing MORE than the humans it was supposed to replace.
They lied to you about AI adoption and now the whole narrative is blowing up:
Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it.
Engineers loved it and adoption exploded. But then the invoices arrived.
Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead.
The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much.
Uber's story is even worse...
Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April.
Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems.
Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session.
The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money.
Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote:
"For my team, the cost of compute is far beyond the costs of the employees."
This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans.
Think about what this means for the entire AI narrative.
Every CEO on every earnings call for the past two years has said the same thing:
AI will make us more efficient, reduce headcount, and cut costs.
The stock market rewarded every company that said it.
Fired workers, stock goes up. Announced AI adoption, stock goes up.
But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill.
Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools.
Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible.
Both companies are spending hundreds of billions on AI infrastructure this year alone.
And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control.
The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP.
This is the gap nobody on Wall Street is pricing in.
$725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work.
What do you think?