Most AI projects talk about datasets. Our community actually built one.
Thanks to our alpha testers:
✅ 250K+ tasks completed
✅ 670K+ EFFECT distributed
✅ Effect AI Scripted Speech 1.0 now live on Mozilla’s Data Collective 👇
https://t.co/l2kJ43OoXM
Learn more in our latest community call (replay):
https://t.co/16SNnNy4aF
Effect’s next chapter is not just about more tasks.
It is about giving workers, builders, stakers, and community members a clearer place in the network.
Effect Passport is part of that direction.
Identity. Stake. Access. Participation.
A front door for what comes next.
Monday, we start with Effect Passport.
Before we get there, think about this:
Your work in Effect should be easier to see.
Your stake should have a clearer purpose.
Your skills should matter.
Your participation should carry forward.
Your place in the network should feel more connected.
That’s the direction we want to explore with the community next week.
A few days ago, we shared a little preview of what we’ll be talking about next week.
• Effect Passport
• DAO discussions
• App ideas
• Staking
• Human feedback inside real workflows
All of these are connected in some way, but the bigger question is what they should become together.
How should workers, builders, stakers, apps, and AI agents actually interact inside Effect?
That’s the conversation we want to start opening up!
Monday, we begin.
Next week, we’re going to start sharing more about where Effect is heading.
More access.
More community input.
More ways for workers, builders, and stakers to shape the network.
Effect Passport.
DAO discussions.
App ideas.
Human feedback inside real workflows.
Creative tools like Canva.
These pieces are starting to connect. We want our community in the conversation while the ideas are still being shaped, not only after they’re finished.
First post drops Monday.
The next generation of AI apps will not be fully autonomous black boxes.
They’ll be workflows made of agents, human workers, validation layers, routing logic, and transparent settlement.
Effect AI is building the human layer for that system, connecting human intelligence to AI workflows when judgment, feedback, and verification are needed.
This is the point.
AI agents need more than model intelligence. They need reliability, validation, and clear human handoffs.
Effect AI is building the human-in-the-loop task layer that helps make agentic workflows work in production.
First large-scale study of AI agents in production just dropped: 306 practitioners, 20 case studies, 26 domains.
(Pan et al, Berkeley + collaborators, arXiv:2512.04123)
The findings that should reframe every "agentic AI" pitch you sit through this quarter:
• 68% of production agents execute ≤10 steps before human intervention
• 70% use prompting off-the-shelf models, NOT fine-tuning
• 74% rely primarily on human evaluation
• 66% are deployed in latency-tolerant workflows
The top challenge isn't model intelligence. It's reliability.
The vendors selling "fully autonomous, fine-tuned, instant-response" agents are pitching the opposite of what's working in production.
The winners are simple, controllable, human-in-the-loop systems with measured handoffs.
Effect is making the worker experience clearer, faster, and easier to navigate.
A refreshed dashboard, improved task campaign layout, and simpler flow for connecting, working, and getting paid are coming soon.
More in the next development update.
Alpha 5 Jedis, your bonus will arrive.
This week, we will be rewarding the top Effect workers who mastered the tasks, stayed sharp, and brought the Force to the network.
May the 4th be with you, Alphas
Phase 5 of Effect Alpha is wrapped.
From new task types to real-world dataset testing, this phase pushed the platform further than ever.
Here’s what we built, what broke, and what comes next 👇
https://t.co/l89Q6WkMVf
Phase 5 has officially wrapped up! 🍾We're crunching numbers and will post a recap of everything we built, everything alpha testers accomplished, and a sneak peek of what's next. Stay tuned 👍