May 10 · 13 min read · Uber’s AI team ran out of budget in April. Their fiscal year started in January. That sentence appeared on Hacker News and hit the front page in under two hours, accumulating hundreds of comments from engineers who recognized the pattern immediately....
Join discussionMay 10 · 13 min read · Uber’s AI team ran out of budget in April. Their fiscal year started in January. That sentence appeared on Hacker News and hit the front page in under two hours, accumulating hundreds of comments from engineers who recognized the pattern immediately....
Join discussionMay 9 · 13 min read · Uber’s AI team ran out of budget in April. Their fiscal year started in January. That sentence appeared on Hacker News and hit the front page in under two hours, accumulating hundreds of comments from engineers who recognized the pattern immediately....
Join discussionMay 9 · 13 min read · Uber’s AI team ran out of budget in April. Their fiscal year started in January. That sentence appeared on Hacker News and hit the front page in under two hours, accumulating hundreds of comments from engineers who recognized the pattern immediately....
Join discussionMay 7 · 8 min read · The fundamental problem with Model Context Protocol servers and large APIs is one of scale. A typical enterprise API has hundreds to thousands of endpoints. Representing each one as a separate MCP tool means tens of thousands of tokens just for the t...
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May 5 · 8 min read · Last month, I published a comparison: MCP Servers vs. CLI. Single server (GitHub), controlled test, clear conclusion: Native MCP wastes 99.7% on schema tax in typical sessions. But that's a lab test.
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Apr 27 · 23 min read · As Large Language Models (LLMs) evolve into autonomous coding agents, one of the most consequential architectural decisions is deceptively simple: how should an AI agent talk to external services? Tra
SSuny commented
