When @SportingLagos got relegated in 2024, David Odunlami [@odunlami_ ] made a mistake he's now open about. He let how he felt shape the club's communication. They went quiet. Pulled back on game-day energy. Stopped doing the things that had made attending feel worth it. The reasoning made sense in the moment; they'd just been relegated, what was there to celebrate? But here's what that thinking gets wrong. Community isn't a reward for good results. It's not something fans give you when you're winning and take back when you're not. It's something you either keep investing in or you don't. And when you stop, people notice. Then attendance drops, engagement thins, and fans disappear quietly. The job of communications isn't to reflect the club's mood. It's to hold the community together when the product is struggling. That's exactly when it matters most. David figured this out a season later. They took a different approach, and by the end of the just-concluded season, fans were buying bus tickets for strangers to make sure the stadium is full. The World Cup starts today. Before the national teams take over everything, read the full story of how Sporting Lagos rebuilt that community.

We got an urgent order for 10 cards today and the customers were minutes away from travelling. Logistics partners were delaying so I got on a bike and delivered them myself. That’s how everyone at Timon thinks about customer satisfaction. We’ll never leave you hanging

When @SportingLagos got relegated in 2024, David Odunlami [@odunlami_ ] made a mistake he's now open about. He let how he felt shape the club's communication. They went quiet. Pulled back on game-day energy. Stopped doing the things that had made attending feel worth it. The reasoning made sense in the moment; they'd just been relegated, what was there to celebrate? But here's what that thinking gets wrong. Community isn't a reward for good results. It's not something fans give you when you're winning and take back when you're not. It's something you either keep investing in or you don't. And when you stop, people notice. Then attendance drops, engagement thins, and fans disappear quietly. The job of communications isn't to reflect the club's mood. It's to hold the community together when the product is struggling. That's exactly when it matters most. David figured this out a season later. They took a different approach, and by the end of the just-concluded season, fans were buying bus tickets for strangers to make sure the stadium is full. The World Cup starts today. Before the national teams take over everything, read the full story of how Sporting Lagos rebuilt that community.

JUST IN: Redditor claims he can now “use ChatGPT” in his head & accurately predict what it would say.

It's Today!🔥 The countdowns are over, the room is ready, our speakers are ready and we have one question for you — Are you ready to Reech us? We trust you are. See you by 4PM! #reechme #reechmeAMA #reechafrica #reech #appmarketing #growthandperformance

2️⃣ days to go. Lionel Messi is the only player to win two #FIFAWorldCup adidas Golden Ball awards 🏆🏆

'The issue of unlimited data on mobile networks: it doesn't exist anywhere in the world except if you're paying a fortune. There's a limit because you can never build enough capacity for everyone to be on an unlimited bundle, and you think you'll provide a quality of service that is decent,' says Chief Executive Officer (CEO) of MTN Nigeria, Karl Toriola.

I built a content machine. It turned me into a one-person media company, has driven tens of millions in pipeline for @tenex_labs, and is allergic to AI-slop. It has also turned all of my employees into content creators. I may opensource the whole thing, but for now, I'm going to share how I built it & how it works. Feel free to copy & paste the steps to Claude/Codex if you want to build your own content machine. Step 1: Map out the process In order to make any of your work AI-native, you need to understand the way in which it's been done historically. This is why business context & domain expertise REALLY matters, even in a post-AI world. Content has been my bread & butter for the last decade, so I started by pulling out an 8.5x11 sheet of printer paper and drawing the traditional process. 1) Look for inspiration 2) Pick a 10x content idea 3) Research the idea 4) Brain dump all of my thoughts about the idea 5) Decide the post format I want to create 6) Create a draft of the post 7) Edit the post 8) Create derivative versions of the post 9) Go live 10) Track performance Step 2: Where am I needed vs. not needed? I am needed for the first & final mile: First mile: picking the idea/direction & providing all of the necessary context Final mile: going through the final draft with a fine tooth comb & giving final sign-off. AI can handle the rest: Looking for inspiration, researching the idea, pulling my thoughts out, writing the post, doing a first edit, creating derivative content, and tracking performance. Step 3: Build the Content Machine The machine is one pipeline, run end-to-end or step-by-step. It is a directory of skills that mimic the steps in the content process that I've delegated. 1) The Oracle [AI] Mines my Slack, Notion, call transcripts and Gmail for spikes, moments I naturally said something worth expanding, while the Internet Reader curates an external feed of X accounts & websites I've selected. Qualifying ideas (≥6/10) are written to The Vault (a notion database of content ideas). 2) Select the idea from The Vault [Human] 3) The Researcher [AI] Before any interview, build a sourced research-report.md: TL;DR, key facts with links, current developments, what's already been said, contrarian angles, and open questions for the interview. Claims are adversarially checked; fact is separated from opinion. 4) Interview Panel [AI Human] Six world-class interviewers (Joe Rogan, Howard Stern, Michael Barbaro, etc) ask 12–15 questions, one at a time, each pushing a different dimension...and never satisfied with vague answers. Won't advance without 2–3 specific stories, real numbers, and emotional specificity. 5) Production [AI] The interview becomes a raw .md file: transcript, key stories, core insights, quotable moments, emotional anchor, surprising reveals, and the "so what." This raw file is sacred: my exact words, never paraphrased away. 6) Refinement [AI Human] I tell the machine what content type I want to create. It reads my custom style guide past feedback lessons content-type spec, then drafts in my voice...pulling real stories and quotes from the raw file. The #1 rule: write like you're texting a friend. Supports long posts, LinkedIn, X threads, and more. 7) Writer's Council [AI] Six expert reviewers (Shaan Puri, Morgan Housel, David Perell, etc) score the draft through their own lens, splitting fixes into editorial (the machine can rewrite) and information gaps (only the creator can answer...these route back to the interview panel). 8) Revision Loop [AI] Iterate until council scores 9/10. 9) Repurposing Engine [AI] One anchor → 10 natively-formatted derivatives, each re-hooked for its platform and each held to the same full Council → revision bar of 9/10. This is how two people produce like a hundred. 10) Final revision [Human] 11) Learning Loop [AI] After approval, the machine compares first draft vs. final, extracts confirmed lessons, and saves them to that creator's content-lessons.md. Every future first draft starts smarter. Lessons override the style guide when they conflict. Feel free to steal the machine & ask me any questions about how it works!