Agentic AI is BPA reborn — with harder governance problems
@joaomdmoura argues that "agentic" AI is business process automation under a new name, with genuinely improved capabilities but the same unsolved governance challenges from 15 years ago.
Score breakdown
The post reframes agentic AI adoption as a governance and reliability challenge inherited from the BPA era, not a greenfield problem — meaning teams without that institutional memory risk repeating costly mistakes at greater scale.
- 01@joaomdmoura frames embedded AI / agentic process automation as business process automation with more capable underlying technology.
- 02Old BPA and RPA ran critical repeatable enterprise processes on rules engines for decades.
- 03The key capability difference: embedded AI can reason through exceptions, learn from past runs, and extract meaning from unstructured data.
@joaomdmoura draws a direct line between today's "agentic" AI movement and the business process automation (BPA) and RPA era that preceded it. The core ambition — taking a critical, repeatable process and making it run reliably — is unchanged. What has changed is the underlying capability: where old BPA could only follow deterministic rules, embedded AI can reason through exceptions, extract meaning from unstructured data, and learn from prior runs. That, the post argues, is not merely a rebrand but a genuine capability leap that justifies the new terminology.
The twist is that these problems now apply to systems that are simultaneously more powerful and less predictable than their predecessors.
However, the post is equally emphatic that the hard engineering and organizational problems are identical to those BPA teams faced 15 years ago: governance, observability, human-in-the-loop checkpoints, and failure management at scale. The twist is that these problems now apply to systems that are simultaneously more powerful and less predictable than their predecessors. The teams shipping fastest, the post observes, tend to be those who lived through the BPA era and already learned not to treat governance as an afterthought.
Key facts
- 01@joaomdmoura frames embedded AI / agentic process automation as business process automation with more capable underlying technology.
- 02Old BPA and RPA ran critical repeatable enterprise processes on rules engines for decades.
- 03The key capability difference: embedded AI can reason through exceptions, learn from past runs, and extract meaning from unstructured data.
- 04The hard problems — governance, observability, human-in-the-loop checkpoints, failure management at scale — are the same as 15 years ago.
- 05Agentic systems are described as more powerful and less predictable than prior BPA systems.
- 06Teams shipping fastest are those who learned from the BPA era and don't treat governance as an afterthought.
- 07The post acknowledges the agentic industry frequently renames existing concepts, but argues the capability this time justifies the new name.
Topics
Summary and scoring are generated automatically from the original article. We always link back to the publisher and never republish images or paywalled content. Last processed Jun 13, 2026 · 08:58 UTC. How this works →