Back from Singapore after a week around @token2049. Justify founder and first creator @TufekciDaryl met investors, founders and teams building across prediction markets. P.S. Especially good to meet Herbert R. Sim (@HerbertRSim) - The Bitcoin Man - in Singapore!

Proud to have @hackenclub supporting Justify on the security side. Our token sale smart contracts have been independently audited by one of the leading Web3 security firms. Building trust into the infrastructure from day one. Justify × Hacken. Security first.

Imagine you've finally got a place to have a REAL talk with your audience. Just Justify. More soon 👀

We don't think the trade ticket is the final interface for agent-native prediction markets. We'd invert it: humans author and revise a strategy; agents execute continuously. Trades are the output. If the trade ticket becomes an output, what belongs in the human interface?

The next prediction-market dashboard may show a portfolio of strategies—not a list of trades. Our thesis: humans choose and fund prediction market strategy mandates; agents execute them. If strategies become the interface, what should humans always keep direct control over?

Agents won’t remove the bottleneck. They’ll move it. We think prediction market agents may shift scarcity from execution to judgment: resolving ambiguity, making trade-offs and knowing when worldviews break. When execution becomes abundant, what becomes the scarce human skill?

Justify thesis: The durable identity in an agent-run market may be the strategy—not the agent. In agent-executed prediction markets, a versioned strategy could persist across executors—and compete. What belongs on its profile: version history, mandate, provenance—or what else?

If AI trading agents make execution abundant, human judgment becomes the scarce layer. Our bet for prediction markets: value shifts from constant attention to a differentiated thesis—and the human-authored strategy behind it.

The most important trading interface may stop being the Buy button. We think it could become a strategy compiler: translate human judgment into a prediction market strategy an agent can follow—when to enter, resize, pause, or exit as prices and evidence change.

The future prediction-market trader may keep a strategy changelog, not a trading diary. We think prediction market strategy design could live in versions: what changed, and why. Strategy versions are the human craft; transactions are the agent’s execution log.

If agents execute, the trade button may stop being the center. We think the prediction economy could center on a two-layer interface: human intent becomes an agent mandate; execution returns as legible feedback. What must an agent show before you'd delegate execution?

In the agent era, the “Trade” button may become secondary. We think the order ticket becomes a canvas: humans author a prediction market strategy and its limits; agents continuously execute that mandate. If the order ticket became a strategy canvas, what control would it need?

We think AI agents in prediction markets could create a paradox: the more agents trade, the more human coordination may matter. Two interfaces may emerge: People ↔ People to exchange strategies Agents ↔ Markets to carry them out The product may be the handoff itself.

The most important prediction market interface may stop being the order ticket. We think strategy could become the control surface: humans set and revise intent; agents execute it continuously. If strategy becomes the interface, what must remain under explicit human control?

The next trading edge may be knowing where not to deploy an agent. Agents may scale execution. That doesn't make every uncertainty worth automating. We think prediction market strategy starts with market selection: choose the game before encoding the moves.

Could an agent tell what would change your mind? If not, you have a take—not an executable prediction market strategy. Our test: • thesis + horizon • update signals • action + invalidation rules • risk boundaries Humans revisit assumptions. Agents monitor and execute.

The prediction-market trader of the future may place far fewer trades by hand. We think the role moves up the stack: humans form theses, apply judgment, and design strategies. Agents handle continuous execution. Stop trading. Build better agents.

We think the next human edge in prediction markets won’t be faster clicking. It’ll be better judgment and strategy design—while agents handle continuous execution. People talk. People design strategies. Agents trade.

We think the goal isn't to remove humans from prediction markets. It's to move human judgment upstream. People should form theses and design strategies. Agents should continuously monitor markets and execute those strategies. Competition could become strategy vs. strategy.

Meet Justify: a social prediction platform where opinions become markets.