Despite ALL the noise about AI disrupting software, and even being relatively technical myself, I havenât built any software with AI.
Since Iâm not a developer, using software to solve issues or create new things just wasnât an available option to me.
I tried Lovable, Bolt, and Replit a long time ago, but for whatever reason, could not really figure out how to do what I wanted.
I had a meeting on Friday with a software company we may deploy for a client, and they had spun up an entire custom front end on top of their base software just a few days after our initial meeting.
They even modified it during the call when I pointed out something I wanted to see done differently.
It was so easy and fast!
One of my favorite Stoic phrases is âif a human can do it, you can do it.â Seeing these guys spin this up really lowered the barrier for me to try.
During the call it triggered a spark of inspiration: I want a âkarmaâ bot for my companyâs Slack instance đ
If you donât know what that is, itâs just a way to give magical internet points to your colleagues. You say something like â@joe +++++â and it gives Joe âpointsâ. These points are stored in a perpetual database.
I knew Anthropicâs Claude was supposed to do coding well, and I also knew they recently released a desktop app, but I didnât know how to start.
SoâŚI asked Claudeâs normal AI chat interface how to start. After talking with it for a while, including details about what I wanted to build, it gave me a project brief to paste into the Claude Code interface (which is just a tab in the desktop app).
I worked back and forth with the Code and Chat interfaces. Code would do the work, then Iâd get stuck on what to do next, so Chat moved me through it.
I had to sign up for and use things Iâve never used before (e.g. Docker). I had to trust some of the commands Code asked permission to run, or that it told me to run in my own Terminal. But in the end? Iâve got a functional karma bot that I built âmyself.â
My karma bot in my Slack instance! Logo done by AI, too.
Start to finish this took less than a calendar day to do, and 2-3 hours of actual work.
Iâm not done yet. My solution is running locally, so my computer has to be up with services active, or it doesnât work. The next step is to figure out how to run this on cloud services so that itâs perpetually on.
Iâm sharing all of this with you in the hopes that it also demystifies the process for you. Youâve probably also got some ideas - or could come up with some - for how software could make your life easier.
This process also put in stark relief the challenge that software companies will face. The market is hammering software companies right now in part on AI concerns. I knew AI would disrupt software, but I thought it would be a few years from now - it might be a lot faster.
If I can go from not knowing what Iâm doing, to a functional simple app in 2-3 hours, what can people who know what they are doing accomplish? What can I accomplish with a few more reps under my belt?
The future is going to be disruptive, and fascinating.
If you build something, let me know how it goes!
Kevin
A Quote
â
Think of learning broadly, so youâre not just accumulating factual information but also deriving insights and meaning from it. Learn about your business, about yourselfâyour behaviors, how your mind works, what youâre good atâand about other people. That means taking in lots of informationâand also reflecting on it. Thatâs when it will take you to a different place.
â Ram Charan in "The High Potential Leader"
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3 - đŻââď¸ The âGet Back Coachâ Did you know thereâs a âget back coachâ on each team in the NFL? Once you know this exists, itâs super funny when you finally see it on a live broadcast.
(Please enjoy this 7ď¸âŁ minute read)
Deep Dive on Speech Acts
Three years ago, Iâm sitting in a monthly business review (MBR) my team has prepared. Weâve got 100s of programs, and 100s of people working across the business, so this is Important Stuff. And as the leader Iâm accountable to make sure the work runs as smoothly as it can, we have high velocity, and hit our goals.
But most of the time Iâd sit there with a scrunched up forehead, trying to figure things out, but not really following. These meetings were very cognitively draining.
I wasn't in a suit and I don't look like this, but this is similar to my experience.
I was doing a lot of the mental work. Decoding meaning. Guessing at what matters. And ultimately figuring out what, if anything, should happen next.
Thereâd be a line like âticket resolution is 90%.â Iâd have to think: What was it before? Whatâs the goal? On what timeframe? Have we tried everything, or have we not even intervened yet? Whatâs causing that number? Do we need to do anything about it?
Iâd leave tired, and the work was only moderately clearer to me. It was both inefficient and ineffective.
As someone keen on personal responsibility, agency, and learning, I first looked inward. What do I need to figure out? How do I get smarter? How can I better prepare?
I also looked structurally. Do we change who is in the meeting? Do I change the template and what Iâm asking for?
It turns out the problem wasnât really me, or the structure. It wasnât about intelligence, effort, or templates.
It was about how people use language.
Language Moves Work
Language doesnât just describe work, itâs how work moves forward. Itâs how we coordinate action in teams.
The work to decompose language, known as speech acts, comes from John Searle, and others, starting in the 1950s. Searle called them illocutionary acts đ¤ˇââď¸, but now youâll find sources that have evolved the descriptors (e.g. 1, 2) to just call them speech acts, and gave the acts better modern names.
It turns out that some speech helps us understand reality, and some speech creates commitments.
In a team, you need both.
Two Kinds of Speech
There are six different speech acts, which can be divided into two groups:
Sense-Making Speech â - Assertions - Describes the current state of reality. - Assessments - Explains whether that state is good, bad, or acceptable. - Declarations - Officially sets or closes the status of something.
Coordination Speech â - Requests - Asks someone else to do something. - Offers - Proposes an action you are willing to take. - Promises - Commits you to a future outcome.
Assertions and assessments help us understand whatâs happening. Declarations end interpretation and make coordination possible. Requests, offers, and promises coordinate action.
Examples of each speech act.
If speech only contains the sense-making elements, itâs a conversation that goes nowhere. Itâs those meetings where you end it and wonder what the action items are. Itâs those meetings where you feel like youâre going around in circles.
If your speech is only in the coordination side (less common), itâs very efficient, but people wonât have the context behind the action. Itâs the meeting where everyone is being told what to do, and they nod, but donât really understand what was being asked or why it needs to be done.
The Common Failure Mode
Going back to my MBR meeting, remember the example of âticket resolution is 90%â. This is a fact that describes reality, so weâd call this an assertion.
By itself, you can see how this does nothing!
Itâs why I had to work so hard in those meetings. I had to uncover other assertions (facts), assessments (judgments on those facts), and declarations (e.g. done, not done) before I could even begin to get into the language of coordination and action.
When teams only use assertions, it puts all the load on the leader. The leader has to uncover more research, decide if itâs good or bad, infer expectations, and guess whether action is required.
Teams hang out in assertions A LOT. Theyâre safe. Theyâre objective. Theyâre non-political. In theory thereâs little argument about an assertion.
Ticket resolution is or is not 90%. You either have two developers on a project or you donât. Excel sheet A is or is not connected to sheet B.
Assessments, in contrast, are risky. Theyâre subjective. Youâre sticking your neck out. Someone else in the room may very likely disagree with it.
And declarations? Thatâs presumptuous. âWho am I to decide whether this is done or not?â
Requests/offers/promises can feel like overstepping.
So teams retreat back to facts, and nothing gets done. But facts donât run businesses.
Before / After Examples
Letâs look at a few examples of what full coordination might look like.
Example 1: Metrics
Before: Ticket resolution is 90%
After: Ticket resolution is 90% this month, down from 96% last month. Our target is 95%. We believe the drop is driven by enterprise complexity. Weâre testing an escalation change this month. No decision needed yet.
Example 2: Staffing
Before: We have two developers on this.
After: We staffed two developers, which matches the original plan. Velocity is meeting expectations, and weâre on track to recover the slip by end of quarter. No additional staffing needed.
Example 3: Delivery Work
Before: Hereâs the latest version.
After: Attached is the fully updated version of the file. All QA issues are resolved. This version is final. Iâll send it to the client by 2:00 PM unless I hear that you have a concern.
Even just writing out these hypothetical âafterâ examples lowered my cortisol! As a leader, they feel much more full. I have all the context, and I know whatâs needed. I can follow the thread, assess risk, and know I can ask questions if needed.
Practical Rules for Daily Work
Every business update should answer three questions explicitly: 1. What is happening? (assertion) 2. So what? (assessment) 3. Now what? (request / offer / promise / declaration)
If any one of those is missing, the update is incomplete.
Never make your audience guess what something means or what should happen.
Artifacts donât close loops. Files, dashboards, and links need speech acts attached; donât Slack or email a file and think youâre done.
Useful Patterns
Effective communication alternates between the two groups. Think in pairs of speech acts operating together.
Assertion â Assessment â Request This sheet isnât connected. Thatâs causing the totals to be wrong. Can you link it and recheck the outputs?
Assertion â Assessment â Declaration All QA issues are resolved. Iâm confident in the numbers. This model is final.
Assessment â Offer I think this could be clearer. I can rewrite the assumptions section if you want.
Assertion â Request The client hasnât received the model yet. Can you send it now?
Leadership Implications
Executives are the most expensive sense-makers in the system. Protect them and their time. Donât pull them down into your world, send them off to do a better job in theirs.
Teams scale when they interpret their own work, and leaders make better decisions when meaning is already made.
Teams should be doing more than gathering facts and organizing them. They need to do the subjective work of assessments; judgment and meaning. They need to declare and close loops.
If both leaders and teams do the work to make this happen, work becomes more fun, things happen more clearly, and people arenât getting burnt out from unnecessary cognitive load.
Call to Action
For the next week, pay attention to moments where work feels stuck.
Find out whatâs missing. Are you just getting facts (assertions), but missing judgment (assessments)?
Does the team need you to make a declaration (this is done / not done, do this / do that)?
Is it time to move out of sense-making and coordinate action? Move the team into requests, offers, and promises.
Donât assume anything is implied. This isnât overcommunication, itâs fully structured and complete communication.
Work moves forward when commitments are explicit.
Kevin
PS - Like the drama triangle and forms of mind, this is one of those fundamental frameworks I use and love. It makes sure things are moving operationally. If you find that it helps you, Iâd love to hear about it. Share it with me at heykev@kevinnoble.xyz.
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