Can we have an agent for…
content discovery?
Content-discovery agents are basically asking "can we kill the Twitter timeline?" The answer keeps being "not yet".
1 roast so far. Verdict mix below.
Verdict distribution
Sample content discovery verdict
“You've drawn a prettier architecture diagram than most YC companies ship — now survive the multi-repo context window.”
Ship it anyway →Build the postmortem + ADR retrieval layer first and only — sell 'your org's memory injected into every plan' as the SKU. Nobody else is indexing Confluence postmortems.
Agent-Readiness Score
Build only if you have a moat. PlanMaster 9000 (aka RFC-to-PLAN.md Whisperer)'s readiness gap is real work.
- Memory ↗19/25
Some cross-session state — start with Redis, graduate to a vector store.
- Tools ↗7/25
Crowded market: at least 9 integrations to compete.
- Policy ↗9/25
Wide policy surface — full red-team pass, content filter, and human-in-loop required.
- Evals ↗16/25
Eval scaffolding doable — write 50 paired examples and grade with an LLM-as-judge.
DETERMINISTIC SCORE — DERIVED FROM EXISTING ANALYSIS, NO SECOND LLM CALL
OWASP-MCP risk profile
Which OWASP Agentic/MCP Top-10 risks content discovery agent ideas tend to carry, across the 1 real idea roasted here. Derived deterministically from each idea's analysis — not a generic checklist.
A second MCP server's output reaches the agent's context and steers it. Mitigation: source-tag every tool result, refuse cross-server instructions.
The agent has more tool privileges than the user task requires. Mitigation: per-task capability scoping, explicit confirmation for destructive ops.
Chaining tools enables an effect neither alone permits (read+exfiltrate). Mitigation: dataflow review, taint tracking, capability slicing.
Educational mapping based on the OWASP GenAI/MCP Top-10. Not a security audit of any specific product.
Best one-liner
“You've drawn a prettier architecture diagram than most YC companies ship — now survive the multi-repo context window.”
Most-shared content discovery roasts
Who's already in this space
End-to-end AI software engineer — does planning + implementation but treats the plan as internal, not an exportable artifact
Issue → plan → code pipeline inside GitHub, but no RFC ingestion, no ADR retrieval, no fan-out to downstream agents
AI-assisted issue decomposition and planning, but shallow — no codebase context, no PLAN.md artifact
GitHub Issues → code PRs, skips structured planning artifact entirely, went quiet in 2024
CLI coding agent with repo map awareness — has the codebase retrieval piece but zero RFC/ADR/postmortem ingestion or planning phase
Tried RFC-to-sprint decomposition, pivoted to generic PM tooling, quietly died — the graveyard is real
Share this verdict
Got a different content discovery problem to roast?
Roast My Problem