That's just the way the world is.
Now, software is hard because the complexity isn't as visible to most of the org, but also because software people tend to be less than good at explaining that complexity to the rest of the org.
Tech debt is real, but so is the downside of building a system that has constraints that do not actually align with the realities of the business: optimizing for too much scale, too much performance, or too much modularity. Those things are needed, but only sometimes. Walking that line well (which takes some luck!) is what separates good engineering leadership from great engineering leadership.
You want the senior people focusing on the problems, strategy, and comms and not data aggregation and power point formatting.
Half the time it doesn't actually matter who the consultant is, the business is just looking for an arbiter to provide a second opinion or justify a decision.
In what world of hiring would passing an interview be considered a failing interview? If it's too poor for hire then it's a fail.
Cutting the people without cutting the programs won't do much and is (IMO) a problem in that you should be able to access government services in a way that the writers of the laws (house/senate) have clearly agreed to. When you're cutting this widely, it's hard to believe you're not throwing the baby out with the bathwater.
If someone asks you for something, it could be something with undefined scope or priority. An "ask" signals "this is official". Same thing with learnings: lesson is personal, learnings means ways things are changing.
Are there dumb business terms, absolutely, but these aren't bad IMO.
Because right now AI companies are losing their asses - it costs significantly more than what they are charging.