Caught my agent “spinning its wheels” on task retries for an hour last night. The actual task only took 8 minutes, but for some reason it wasn’t able to decide to stop the failing retries, so I had to implement some process changes. It’s very important that you have processes in place to catch these failures.
@coreyganim Models are just a commodity & deciding which one to use is like trying to choose between a Snickers or a Reese’s Nutrageous when you’re hungry.
holy sh*t, OpenAI just dropped the Codex AI agent stack
and it exposes the biggest MCP mistake
most agents load every tool upfront:
→ 100 tools
→ 100 descriptions
→ 100 schemas
→ half the context is gone
before the agent even starts working.
the better pattern:
tool search → load only what’s needed → execute
example:
user: “refund this customer”
agent starts with:
→ search_tools(“refund customer payment”)
then loads only:
→ get_customer_context
→ create_refund_draft
→ verify_refund
not your entire fucking MCP server
this gives you:
→ cheaper runs
→ lower latency
→ cleaner prompt cache
→ less tool confusion
→ agents that don’t pick random overlapping tools
your agent should not know
every tool your company has
it should know how to find
the right 3 tools for the job
that’s the actual scalable MCP pattern
save this, then read the article below