Decentralized Autonomous Organizations (DAOs) face systemic challenges that undermine their goals of participatory and transparent governance, particularly due to delegation mechanisms that lead to a severe concentration of voting power. Despite the intent of delegation—to mitigate voter apathy by allowing token holders to assign their votes—its current implementation, often on popular platforms like Tally, reinforces structural biases and results in skewed decision-making. A key finding of a new study is that DAO governance suffers from a "rich-get-richer" dynamic. Delegation interfaces frequently rank delegates by Voting Power or Received Delegations, promoting a few highly visible delegates who accumulate disproportionate influence regardless of their alignment with the broader community's interests. The study, which combined on-chain archival data from five major protocols (Uniswap, Aave, Arbitrum, ENS, and Compound) with off-chain discussions from 14 DAO governance forums, demonstrated that current delegation choices are frequently misaligned with token holders' expressed priorities. Analysis revealed extreme levels of centralization across DAOs: Token ownership is highly unequal, with Gini coefficients above 0.99 for major protocols like Aave, Compound, ENS, and Uniswap. This imbalance is amplified when tokens are delegated, with Gini coefficients for voting power all exceeding 0.94. In both Compound and Uniswap, as few as 13 to 16 delegates are needed to control the 50\% threshold of delegated power. Modeling delegation as a directed graph confirmed a disassortative "hub-and-spoke" structure. This topology shows many low-degree delegators connecting to a few high-degree delegates, which is a key mechanism for consolidating influence. The common practice of delegators assigning power to only a single delegate also contributes to this concentration. To measure misalignment, the study developed a methodology to quantify voter interests: A precise process was used to link forum usernames to on-chain addresses via Tally delegate profiles and ENS registration, enabling the connection of discussions to voting behavior. LLM-Powered Extraction: Large Language Models (LLMs), specifically a variant of GPT-5, were applied to over 15,000 forum posts to extract topic keywords, sentiment, and ideological signals. These keyword profiles were converted into semantic vectors and clustered, revealing five distinct groups of voter interests, including Finance-Driven (treasury, accountability), Governance-Driven (principles, public goods), and Arbitrum DeFi-Driven (risk management, liquidity). Conclusion The findings demonstrate that existing interfaces, by promoting visibility over alignment, exacerbate centralization. The research argues that incorporating interest alignment into delegation processes, perhaps by making alignment more transparent to users, could help redistribute delegator support more equitably and improve the fairness and representativeness of DAO decision-making. Since much the same applies to all proof of stake and dPOS networks they have universally failed in all their objectives. PoS and DAOs mean the rich get richer at the expense of invisible small investors.