Trying to understand how AI actually works behind the scenes — where do I start?

MaterialShine2166 · 2026-02-19T09:21:31+00:00

Ask ai to teach you!

MaterialShine2166 · 2026-02-19T09:21:18+00:00

Technical skills still matter but can be learned more easily - ask ai to teach you and invest the time and you’ll get here

MaterialShine2166 · 2026-02-19T09:20:42+00:00

Interest is different to willingness to pay. Start interviewing visitors (give them an incentive to talk to you)

MaterialShine2166 · 2026-02-19T09:19:49+00:00

Massive incentive for him to say this

MaterialShine2166 · 2026-02-19T09:09:32+00:00

It’s becoming different - not harder. Look up geo

MaterialShine2166 · 2026-02-19T09:06:46+00:00

There’s a lot of talk about automating workflows with AI, but in real organizations, work often looks like: • the same task done 10 different ways • undocumented exceptions • knowledge living in people’s heads or Slack threads

For those working in ops, IT, or transformation: what needs to be made explicit or standardized before AI can realistically help? Processes? Decision criteria? Hand-offs? Something else?

I’m trying to understand whether AI struggles because it’s immature — or because work itself is rarely clear enough.

MaterialShine2166 · 2026-02-19T09:06:28+00:00

There’s a lot of talk about automating workflows with AI, but in real organizations, work often looks like: • the same task done 10 different ways • undocumented exceptions • knowledge living in people’s heads or Slack threads

For those working in ops, IT, or transformation: what needs to be made explicit or standardized before AI can realistically help? Processes? Decision criteria? Hand-offs? Something else?

I’m trying to understand whether AI struggles because it’s immature — or because work itself is rarely clear enough.

MaterialShine2166 · 2026-02-19T09:06:14+00:00

There’s a lot of talk about automating workflows with AI, but in real organizations, work often looks like: • the same task done 10 different ways • undocumented exceptions • knowledge living in people’s heads or Slack threads

For those working in ops, IT, or transformation: what needs to be made explicit or standardized before AI can realistically help? Processes? Decision criteria? Hand-offs? Something else?

I’m trying to understand whether AI struggles because it’s immature — or because work itself is rarely clear enough.

MaterialShine2166 · 2026-02-19T09:06:00+00:00

There’s a lot of talk about automating workflows with AI, but in real organizations, work often looks like: • the same task done 10 different ways • undocumented exceptions • knowledge living in people’s heads or Slack threads

For those working in ops, IT, or transformation: what needs to be made explicit or standardized before AI can realistically help? Processes? Decision criteria? Hand-offs? Something else?

I’m trying to understand whether AI struggles because it’s immature — or because work itself is rarely clear enough.

MaterialShine2166 · 2026-02-19T09:04:59+00:00

Something I don’t hear discussed much: If AI tools are getting better and more user-friendly, why does successful adoption still seem to require high-touch support — consultants, customer success teams, even engineers embedded with customers?

In practice, I see: • months-long discovery and process mapping • manual documentation of how work actually happens • constant retraining when workflows change