The Lead Exposure Elimination Project's story reveals a potential weakness in GiveWell's model. Its preference for proven, repeatable interventions can lead it to decline funding for more uncertain but potentially higher-impact "hits-based" approaches like policy reform, which Open Philanthropy, with its different risk tolerance, was able to support.

Alexander Berger argues that even by long-termist standards, "near-termist" work in global health is valuable. It builds crucial infrastructure—like policy advocacy experience, trusted grantee relationships, and feedback loops on what works—that can later be leveraged for long-termist goals like biosecurity, creating optionality and reducing risk for the overall portfolio.

After an intervention like cash transfers has been validated by over 100 randomized trials, spending more money on another study is unethical. That funding is being taken from potential beneficiaries to measure something already known, preventing more lives from being improved.

Philanthropy often addresses symptoms because the market won't pay to solve the root problem. True, lasting progress comes from innovating to create a self-sustaining economic engine around a solution, proving its value in a marketplace where people vote with their money.

A critical flaw in philanthropy is the donor's need for control, which manifests as funding specific, personal projects instead of providing unrestricted capital to build lasting institutions. Lasting impact comes from empowering capable organizations, not from micromanaging project-based grants.

Thought experiments like the 'River of Drowning Children' suggest strict altruism requires sacrificing your entire life. However, most plausible ethical theories reject this maximal demandingness. They acknowledge that your own well-being, family, and personal projects also hold moral weight and should not be entirely sacrificed.

Frame philanthropic efforts not just by direct impact but as a "real-world MBA." Prioritize projects where, even if they fail, you acquire valuable skills and relationships. This heuristic, borrowed from for-profit investing, ensures a personal return on investment and sustained engagement regardless of the outcome.

The 'effectiveness' in Effective Altruism creates a bias toward quantifiable problems like global health, while overlooking harder-to-measure but potentially higher-impact areas. For instance, preventing political dysfunction or misinformation among influencers could have a far greater downstream effect than many targeted donations, but it's not a typical EA cause because its impact is difficult to quantify in advance.

For any development problem, a program should either be based on strong existing evidence ("use it") or, if such evidence is absent, be designed as an experiment to generate new findings ("produce it"). This simple mantra avoids redundant research and ensures all spending either helps or learns.