AI Collectives Lagos

The world’s largest AI community. Uniting 200k+ pioneers across 100+ global forums. Building the human layer for the AI era.

[AI Collectives Lagos @aiclagos]

We will discuss how we can build and adopt AI systems responsibly.

August 28th, 2026
Register here: https://t.co/5oyd2EEY01

[AI Collectives Lagos @aiclagos]

@solopribuilds The observabilty to the workings of that app that works would be key to knowing how to proceed.

[Div Garg @divgarg]

We made an MCP for your phone.

Your laptop is just half of your life, and the other half is in your phone. Now your agent gets the mobile screen too. No connectors, no complex setup, it has access to everything that lives on your phone, all the logged-in apps, your notes, your calls, you name it.

It sees the screen, taps it, types on it, from Claude Code, Codex, or any MCP client.

Live now at https://t.co/LCzta2HAFd
$20 in credits, $20 more for the first 100 who connect a phone and run a task.

Comment "discord" if you want the invite to the builder Discord, I'll DM it to you.

[AI Collectives Lagos @aiclagos]

We will discuss how we can build and adopt AI systems responsibly.

August 28th, 2026
Register here: https://t.co/5oyd2EEY01

[AI Collectives Lagos @aiclagos]

The AI Collective Lagos Chapter First Event

We’re excited to host our very first chapter event on August 28th, a special conversation around AI Governance and the future of responsible AI.

https://t.co/5oyd2EEY01

[AI Collectives Lagos @aiclagos]

Join us as we bring together global perspectives from:

Michela De Mattia — AI Governance Leader, Canada
Alice Namuli — Legal Partner, KATS, Uganda

Harmony Abayomi - CEO, Valor AI

[AI Collectives Lagos @aiclagos]

The AI Collective is a global non-profit — 250,000+ AI builders, 200+ chapters worldwide.

Lagos just became one of them.

We're not a conference. We're not a course.
We're the people building the future of AI.

Welcome to @aiclagos. 🇳🇬

[AI Collectives Lagos @aiclagos]

Lagos, we're here.

@AICollective just landed — building the
most serious AI community on the continent.

Founders. Researchers. Builders. Operators.

If you work on AI — this is your home.

Follow. We're just getting started. 🔥

#AILagos #AICollective

[AI Collectives Lagos @aiclagos]

@AICollectiveCo 🚀

[The AI Collective @AICollectiveCo]

Every enterprise AI deal has a hidden gate. Before a buyer signs or an investor writes a check, they're running the same quiet screen: can I trust this thing where it matters.
Join us for another Lunch & Hack session! 🚀
Check the comments for the event link

[Boston Dynamics @BostonDynamics]

Did you see Atlas step into the spotlight at the FIFA World Cup 2026™? Atlas arrived pitchside at NYNJ Stadium in front of 80,000 people gathered to see Brazil vs Norway. After performing some of the sport’s most memorable player celebrations, Atlas helped kick-off the second half by delivering the match ball!

[Africa Deep Tech Community @africadeeptech]

The Africa Deep Tech Challenge 2026 is officially live.

This year’s theme is "The Laptop LLM" — an engineering-first challenge for African builders creating practical on-device AI that runs on commodity laptops, with no cloud dependency.

Why participate?
- $20,000 prize pool
- Mentorship + technical reviews
- Continental visibility
- Pilot + commercialization opportunities
- Community support

Applications are now open. Share this with someone.
Register here: https://t.co/BEQ7wVfGV8
Gate 1 deadline: 24 July 2026

Our Partners: @MITKuoSharper @3MTTNigeria @anafricanfuture @gdglagos @acceler_8africa @isnhubs @udutech @ARVRAfrica @ojiudezue

#TheLaptopLLM
#ADTC2026
#AfricaDeepTech
#AIForAfrica
#AfricanInnovation

[Chappy Asel @chappyasel]

AI is here but is it serving humanity?

After two years building an AI community, I saw that the future isn't waiting anymore. So neither are we.

Introducing: The AI Collective. (@_ai_collective)

We are the world’s largest grassroots movement, now a non-profit, dedicated to collaboratively steering AI towards trust, openness, and human flourishing.

We're mobilizing builders, researchers, and visionaries because our old systems can't keep up.

We’re building the future through a global chapter network and Singularity Fest, The AI Collective Institute for responsible AI governance, and a program connecting founders with values-aligned capital.

Formerly The GenAI Collective, we're already:
🌎 70,000+ members (Founders, investors, and researchers from OpenAI, Meta, Anthropic, Google & more)
🌍 25+ global chapters & 200+ impactful events
🌏 100+ mission-driven volunteer organizers

To join the movement & help shape a future we can all believe in, REPOST & comment! 🤝

Let's build something future generations will thank us for.

[The AI Collective @AICollectiveCo]

On today's Byte: the real reason your AI agents keep getting it wrong.

Hint: it isn't the model. The answer was just sitting in a system the agent couldn't reach. Connect your context and everything changes.

Full read 👇
https://t.co/25az34mJEP

[The AI Collective @AICollectiveCo]

On today's Byte: Will New York's RAISE Act build trust in AI?

It pushes big AI developers to prove their systems are safer, but gives the public little say, no right to an explanation and no way to appeal when AI affects them. Safer isn't the same as trusted.

Full read 👇 https://t.co/9bQBTfZSDw

[The AI Collective @AICollectiveCo]

Have you ever watched a team of AI agents collaborate, delegate work, and communicate with each other in real time?
You’re about to. 👀
This isn't a demo of a single AI assistant. It's an entire team of agents working together to get the job done.

Want to learn more about this and other fascinating AI topics?
Join us for the Lunch & Hack series by The AI Collective and RoryPlans, where we bring together builders, founders, and AI leaders to learn, discuss, and build together.
Check the link for our upcoming agenda, event calendar, and recordings of past sessions: https://t.co/SMSY0fyeql

[Anthropic @AnthropicAI]

Claude Fable 5 will be available again globally tomorrow.

After a series of productive conversations with the US government, we're redeploying the model with a new set of classifiers to target and block more cybersecurity tasks. In the near term, some routine tasks like coding and debugging will fall back to Opus 4.8. We’ll continue to refine these classifiers over the coming weeks to reduce false positives and better distinguish genuine misuse from legitimate requests.

We’ve also begun drafting a consensus framework—with Amazon, Microsoft, Google, and other Glasswing partners—for assessing the severity of AI jailbreaks and how AI developers should respond to them. We invite other industry partners and model providers to join us in this effort.

Finally, we’re scaling up our collaboration with the US government on model testing and safeguards. This will include pre-release access to models and safeguards for evaluation, information sharing on jailbreaks and misuse, and dedicated resources for joint research.

Thank you to our users for your patience, and to our partners across the government, industry, and the research community who worked alongside us to make Fable 5 available again.

Read our full blog: https://t.co/VHyum831ri

[Andrew Ng @AndrewYNg]

“Loop engineering” is a hot buzzphrase after mentions of it by Boris Cherny (Claude Code’s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, I’d like to share my 3 key loops, shown in the image below, for building 0-to-1 products. These loops guide not just how I build software, but also how I decide what software to build.

Agentic coding loop: Given a product specification and optionally a set of evals (that is, a dataset against which to measure performance), we can have an AI agent write code, test its work, and keep iterating until the code is bug-free and meets its specification. This idea of closing the loop took off around the end of last year, and it has been a game changer in enabling coding agents to work longer productively without human intervention. For example, over the weekend, I was building an app for my daughter to practice typing, and my coding agent could easily work for around an hour, using a web browser to check what it had built multiple times before getting back to me, without needing my intervention.

The engineering loop executes quickly. Every few minutes, the coding agent might build and test a new version of the software. I hear frequently from developers who are finding new ways to engineer more effective engineering loops. This is an active area of invention!

Developer feedback loop: In this loop, a developer examines the current product and steers the coding agent to improve it. Last year, a lot of developers (including me) were acting as the QA (quality assurance) function for our coding agents, manually finding bugs and then asking the agent to fix them. But with coding agents much more able to test their own code, the amount of time we need to spend on this function has decreased significantly. This allows us to make higher-level product decisions, such as what key features to offer, where the UI needs improvement, and so on.

The developer-feedback loop operates over time intervals between tens of minutes and hours — that's how frequently a developer might review a product and give feedback. In the case of the typing app, I changed my mind a few times about the visual design, what cat costumes she can unlock as she learns (she loves cats), and the user flow for a grown-up to log in and steer the child's learning experience.

When a developer has a clear vision for what to build, it is still a lot of work to translate that vision into a specification for a coding agent to implement. Further, after the developer has seen an implementation, they might update (or perhaps clarify) the spec to steer it toward what they want. If you find that the system repeatedly runs into certain problems, building a set of evals for the agent becomes useful.

AI-native teams are increasingly using AI to help shape product direction, for example, automating the gathering and analysis of usage data, summarizing written and verbal customer feedback, or carrying out competitive analysis. However, for pretty much all the products I’m involved in, I see humans as having a significant context advantage over current AI systems — we know a lot more than the AI system about the users and the context the product has to operate in — and thus humans play a critical role. Many people describe this human contribution as “taste,” but I prefer to think of it as humans having a context advantage, since that gives us a clearer path to helping AI systems get better. This also speaks to why this step can’t be automated: So long as the human knows something the AI does not, human-in-the-loop is needed to to inject that knowledge into the system.

External feedback loop: This includes a wide range of tactics like asking a few friends for feedback, launching to alpha testers, or putting the code into production with A/B testing. These tactics are usually slow, rarely taking less than hours and sometimes taking days or even weeks. This data informs the developer vision, which in turn continues to drive the detailed product spec, which in turn drives the coding agent.

With coding agents speeding up software development, more engineers are starting to play a partial product management role. For many engineers who are growing into this role, the hardest part is shaping the product vision and striking a balance between building (bridging the gap between vision and spec) and getting user feedback to evolve the vision. It is important to do both!

I will write more about how to do this in future posts, but for now, I find it encouraging that engineers are playing an expanded role (just as product managers and designers now do more engineering).

[Original text: The Batch]