Congrats on reaching this milestone - it's well deserved.
I've a question:
Given its hype, managers are sometimes tasked with exploring AI's feasibility within the organization. Do you have some suggestions as to what managers should be doing more, from a developer/technical person's perspective?
Congrats on reaching this milestone - it's well deserved.
I've a question:
Given its hype, managers are sometimes tasked with exploring AI's feasibility within the organization. Do you have some suggestions as to what managers should be doing more, from a developer/technical person's perspective?
Thus far, I've approached it more as an exploration (rather than an exploitation) exercise, as the field is still new & isn't yet amenable to best practices & industry standards. This translates to incorporating confidence intervals into one's point estimates when coming up with milestones; using real options as opposed to IRR/NPV calculations when evaluating project feasibility; & maintaining skepticism when reading the news (In this regard, your substack is one of the few sources I trust), among other measures.
These measures mainly serve to manage/temper expectations up-stream (with upper-management) - the list of analytics/AI projects plagued by poor ROI is endless, even in "good" organizations.
However, this is just half the story. There's also the matter of down-stream management (of developers & technical personnel).
What might be your wishlist of things that you'd like managers of these projects to do more of?
Thank you, Anna! I think you are absolutely correct here:
"Thus far, I've approached it more as an exploration (rather than an exploitation) exercise, as the field is still new & isn't yet amenable to best practices & industry standards. This translates to incorporating confidence intervals into one's point estimates when coming up with milestones; using real options as opposed to IRR/NPV calculations when evaluating project feasibility; & maintaining skepticism when reading the news (In this regard, your substack is one of the few sources I trust), among other measures."
I think the most valuable approach for you and your company is to learn and learn and learn without yet forming a strong opinion. Listen to those who know with skepticism as you say, because it's still super new.
I'd say you are doing all of this extremely well already given how you frame your situation and your question. I'm sure those above and below you appreciate that thoughtfulness greatly.
Hi Alberto,
Congrats on reaching this milestone - it's well deserved.
I've a question:
Given its hype, managers are sometimes tasked with exploring AI's feasibility within the organization. Do you have some suggestions as to what managers should be doing more, from a developer/technical person's perspective?
Thus far, I've approached it more as an exploration (rather than an exploitation) exercise, as the field is still new & isn't yet amenable to best practices & industry standards. This translates to incorporating confidence intervals into one's point estimates when coming up with milestones; using real options as opposed to IRR/NPV calculations when evaluating project feasibility; & maintaining skepticism when reading the news (In this regard, your substack is one of the few sources I trust), among other measures.
These measures mainly serve to manage/temper expectations up-stream (with upper-management) - the list of analytics/AI projects plagued by poor ROI is endless, even in "good" organizations.
However, this is just half the story. There's also the matter of down-stream management (of developers & technical personnel).
What might be your wishlist of things that you'd like managers of these projects to do more of?
Thank you, Anna! I think you are absolutely correct here:
"Thus far, I've approached it more as an exploration (rather than an exploitation) exercise, as the field is still new & isn't yet amenable to best practices & industry standards. This translates to incorporating confidence intervals into one's point estimates when coming up with milestones; using real options as opposed to IRR/NPV calculations when evaluating project feasibility; & maintaining skepticism when reading the news (In this regard, your substack is one of the few sources I trust), among other measures."
I think the most valuable approach for you and your company is to learn and learn and learn without yet forming a strong opinion. Listen to those who know with skepticism as you say, because it's still super new.
I'd say you are doing all of this extremely well already given how you frame your situation and your question. I'm sure those above and below you appreciate that thoughtfulness greatly.
Your "...to learn and learn and learn without yet forming a strong opinion," is useful in so many areas of life besides technology.
Thanks, Alberto. I've enjoyed your insightful takes & look forward to more in the upcoming year.