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  • Preparing for Defi interview as developer: Need help

    Andria Shines

    Member

    Updated: Apr 19, 2025
    Views: 1.0K

    Hey everyone! I’m preparing for a technical interview with a DeFi protocol and working on upskilling my knowledge on securing price feeds for lending systems. For same,

    My findings are most protocols use decentralized oracles (Chainlink, Pyth) + TWAPs to avoid price spikes and aggregating data from multiple DEXs/CeFi sources to reduce manipulation risks.

    But I’m not able to overcome beyond the basics ummmm like  do top protocols use sneaky-smart tricks like outlier detection, secondary checks, or emergency price freezes?

    And if they do so how they handle real time pricing when market meltdowns without getting rekt by stale data or flash loans.

     Are protocols experimenting with stuff like UMA’s “optimistic” oracles or ZK proofs for extra security?

    Can anyone suggest me about the these facts so that I will be able to upgrade my knowledge,

    Just to mention, this defi protocol is a dream company for me

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  • Rashad Collins

    Member • 5mos

    Impermanent loss affects liquidity providers when token prices in a pool change. Several strategies help reduce this risk and improve outcomes for both protocols and users.

    Stablecoin pools are a reliable method. Since stablecoins have minimal price fluctuations, the chances of value divergence are low. Curve Finance uses this approach effectively. Dynamic fee structures, like those in Uniswap v3, also help. Fees increase during volatile periods, compensating for potential losses.

    Some protocols, like Bancor, include impermanent loss protection directly in the smart contract. Providers earn full protection over time, encouraging long-term participation. This balances risk and rewards.

    Choosing token pairs with strong price correlation, like ETH and stETH, can further reduce risk. Single-sided liquidity options offered by some platforms allow users to avoid exposure to a second token altogether.

    Multi-asset pools, such as those on Balancer, spread risk by including several tokens in a single pool. This diversification reduces the impact of one token’s price movement.

    The best results come from combining these approaches. Understanding how liquidity, fees, and price volatility interact is essential. Data analysis of historical pool performance also helps liquidity providers make informed decisions.

    By applying these strategies, protocols can retain liquidity while reducing risks for users, creating a more sustainable DeFi ecosystem.

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  • Varun Mehta

    Member • 5mos

    Building on the points mentioned earlier, could you recommend any tools or strategies for analyzing historical pool performance data? This was a significant challenge in my last project, and I struggled to find an effective solution. I would greatly appreciate any insights. Thanks in advance!

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