Build vs buy for internal AI agents: framework or platform?
LangGraph/CrewAI-style frameworks versus packaged agent platforms from the big vendors. If you have tried both, where did each win on time-to-value, control and cost?
This is where people who run enterprise technology compare notes before a decision: what they’re evaluating, what they’d pick again and what went wrong. Most members are practitioners. Anyone who works for a vendor carries their company’s name on every post.
The bar is specifics over opinions: what you ran, at what scale and what you learned. Moderators check each new member’s first posts.
LangGraph/CrewAI-style frameworks versus packaged agent platforms from the big vendors. If you have tried both, where did each win on time-to-value, control and cost?
Vector search, time series, queues, analytics: many teams now start with Postgres extensions. Where has that worked, and where did you need a dedicated engine?
If you have run more than one, compare them on cost at your scale, time to value and on-call experience.
For teams in financial services, government or healthcare: which did you choose and what tipped it: compliance evidence, support, cost or skills?
Share the use case, the approach you chose and the results.