Pyth Network is one of the most notable on-chain oracles, with a strong focus on bringing real, reliable, and high-frequency financial data to multiple blockchains. Here I summarize its roadmap up to what has been done, what is in progress, and what they have planned for the future. If you want, I can update it with the latest (2025) for your country/region.
✅ What has been achieved so far
Some goals that Pyth has already achieved:
Mainnet launch (on Solana) with high-fidelity price feeds obtained directly from financial institutions.
Expansion to other chains (blockchains), beyond Solana. Support in EVMs and other L1/L2 networks.
Technical improvements to reduce latency of price feeds, increase the number of data providers per feed, optimize gas costs for users.
Launch of the protocol governance: DAO component, with the Pyth DAO Constitution, on-chain votes for key decisions such as which feeds are listed, which providers can participate, fees, etc.
Introduction of additional products, for example Pyth Entropy (service for generating random numbers on-chain) for use in gaming, NFTs, or other cases that require randomness.
🔄 In progress / recent goals
What Pyth is developing or has announced as next steps:
Increase data coverage: including more asset classes, such as futures, currencies (FX), volatility, and broader TWAP-style metrics.
Continue expanding the network of data providers, both in quantity and quality. More feeds, greater reliability, lower chances of interruptions.
Improve integration with more blockchain chains: both L1s and L2s. That Pyth's data is accessible in more environments, for more dApps.
Introduce staking, rewards, feed curation, that is, allowing PYTH token holders to participate more actively in security, validation, and governance with incentives.
Introduction of fees and 'slashing' mechanisms for data providers if they do not meet certain standards.
🔭 Future plans
These are some of the milestones expected from Pyth in the coming years:
Further expand the types of data published: not only cryptocurrencies but also traditional financial products, international stocks, commodities, economic macrodata, etc.
Continuous technical improvements: lower latency, more precision, optimization of operational costs, perhaps new data aggregation architectures.
More mature governance: more decentralized decisions, that PYTH token holders have more voice regarding fees, software updates, selection of data providers, etc.
More token unlocks / vesting schedule until 2027. This is relevant to understand future dilution and the distribution of incentives.
⚠️ Risks and factors to consider
Token unlocks: Every time large amounts of $PYTH are released, it could affect the price or circulating supply.
Competition with other oracles (e.g. Chainlink, Band, etc.): data quality, latency, integrations, reliability, costs.
Regulatory compliance, especially regarding traditional financial data (stocks, macroeconomics) in different jurisdictions.
Scalability: keep latency low and ensure that providers meet standards.
