AI-Proof
@aiproofhq.bsky.social
ai-proof helps people and businesses cut through the AI noise.
We focus on practical, high-value uses of AI - not hype, gimmicks, or over-promised tools.
• Clear explanations
• Real-world use cases
• Tools that actually deliver value
We focus on practical, high-value uses of AI - not hype, gimmicks, or over-promised tools.
• Clear explanations
• Real-world use cases
• Tools that actually deliver value
The companies that actually win with AI aren't the ones with the smartest code.
They are the ones with the CLEANEST DATA.
A simple model with excellent data discipline outperforms a complex model learning from garbage.
They are the ones with the CLEANEST DATA.
A simple model with excellent data discipline outperforms a complex model learning from garbage.
January 12, 2026 at 10:00 AM
The companies that actually win with AI aren't the ones with the smartest code.
They are the ones with the CLEANEST DATA.
A simple model with excellent data discipline outperforms a complex model learning from garbage.
They are the ones with the CLEANEST DATA.
A simple model with excellent data discipline outperforms a complex model learning from garbage.
The fancy AI model was effectively LEARNING FROM NOISE.
The outputs looked precise... but they were wrong.
We realised the "AI value" was a mirage because the foundation was made of sand.
The outputs looked precise... but they were wrong.
We realised the "AI value" was a mirage because the foundation was made of sand.
January 12, 2026 at 10:00 AM
The fancy AI model was effectively LEARNING FROM NOISE.
The outputs looked precise... but they were wrong.
We realised the "AI value" was a mirage because the foundation was made of sand.
The outputs looked precise... but they were wrong.
We realised the "AI value" was a mirage because the foundation was made of sand.
Then we looked under the hood.
The models weren't the problem. The data was.
It was fragmented.
Inconsistently labelled.
Manually overridden by staff who didn't trust the workflows.
The models weren't the problem. The data was.
It was fragmented.
Inconsistently labelled.
Manually overridden by staff who didn't trust the workflows.
January 12, 2026 at 10:00 AM
Then we looked under the hood.
The models weren't the problem. The data was.
It was fragmented.
Inconsistently labelled.
Manually overridden by staff who didn't trust the workflows.
The models weren't the problem. The data was.
It was fragmented.
Inconsistently labelled.
Manually overridden by staff who didn't trust the workflows.
We looked at a company that was was for sale which claimed an "AI-driven pricing engine."
The demos were slick.
The narrative was compelling.
The price tag was high.
The demos were slick.
The narrative was compelling.
The price tag was high.
January 12, 2026 at 10:00 AM
We looked at a company that was was for sale which claimed an "AI-driven pricing engine."
The demos were slick.
The narrative was compelling.
The price tag was high.
The demos were slick.
The narrative was compelling.
The price tag was high.
So, look at your digital strategy.
Are you relying on third-party AI for verification or access?
If that black box breaks, do you have a manual override?
If the answer is no, you are vulnerable.
Are you relying on third-party AI for verification or access?
If that black box breaks, do you have a manual override?
If the answer is no, you are vulnerable.
January 11, 2026 at 10:00 AM
So, look at your digital strategy.
Are you relying on third-party AI for verification or access?
If that black box breaks, do you have a manual override?
If the answer is no, you are vulnerable.
Are you relying on third-party AI for verification or access?
If that black box breaks, do you have a manual override?
If the answer is no, you are vulnerable.
We are building a digital world where access is granted by probability, not certainty.
For businesses, this creates a new liability:
Your growth is now dependent on a gatekeeper you don't control and can't interrogate.
For businesses, this creates a new liability:
Your growth is now dependent on a gatekeeper you don't control and can't interrogate.
January 11, 2026 at 10:00 AM
We are building a digital world where access is granted by probability, not certainty.
For businesses, this creates a new liability:
Your growth is now dependent on a gatekeeper you don't control and can't interrogate.
For businesses, this creates a new liability:
Your growth is now dependent on a gatekeeper you don't control and can't interrogate.
When AI decides who gets in...
Who and how do they decides when the AI is wrong?
If a facial scan fails, or an age check creates a false positive, does the customer have recourse?
Or do they just hit a digital brick wall?
Who and how do they decides when the AI is wrong?
If a facial scan fails, or an age check creates a false positive, does the customer have recourse?
Or do they just hit a digital brick wall?
January 11, 2026 at 10:00 AM
When AI decides who gets in...
Who and how do they decides when the AI is wrong?
If a facial scan fails, or an age check creates a false positive, does the customer have recourse?
Or do they just hit a digital brick wall?
Who and how do they decides when the AI is wrong?
If a facial scan fails, or an age check creates a false positive, does the customer have recourse?
Or do they just hit a digital brick wall?
The risk here isn't just privacy.
It's ACCOUNTABILITY.
What if
"You can't explain why a system made a decision, you haven't automated a process. You've abdicated responsibility."
It's ACCOUNTABILITY.
What if
"You can't explain why a system made a decision, you haven't automated a process. You've abdicated responsibility."
January 11, 2026 at 10:00 AM
The risk here isn't just privacy.
It's ACCOUNTABILITY.
What if
"You can't explain why a system made a decision, you haven't automated a process. You've abdicated responsibility."
It's ACCOUNTABILITY.
What if
"You can't explain why a system made a decision, you haven't automated a process. You've abdicated responsibility."
I've spent 25 years in tech strategy.
In some areas we are moving from an open web to a GATED ecosystem.
And the bouncer at the door isn't a human.
It's sometimes opaque algorithm.
In some areas we are moving from an open web to a GATED ecosystem.
And the bouncer at the door isn't a human.
It's sometimes opaque algorithm.
January 11, 2026 at 10:00 AM
I've spent 25 years in tech strategy.
In some areas we are moving from an open web to a GATED ecosystem.
And the bouncer at the door isn't a human.
It's sometimes opaque algorithm.
In some areas we are moving from an open web to a GATED ecosystem.
And the bouncer at the door isn't a human.
It's sometimes opaque algorithm.
Don't wait for the next lawsuit to define your strategy.
Audit your AI tools now.
Demand transparency on training data.
Ensure you aren't building your brand on borrowed land.
The playbook is being written right now.
Make sure you're reading it.
Audit your AI tools now.
Demand transparency on training data.
Ensure you aren't building your brand on borrowed land.
The playbook is being written right now.
Make sure you're reading it.
January 9, 2026 at 10:00 AM
Don't wait for the next lawsuit to define your strategy.
Audit your AI tools now.
Demand transparency on training data.
Ensure you aren't building your brand on borrowed land.
The playbook is being written right now.
Make sure you're reading it.
Audit your AI tools now.
Demand transparency on training data.
Ensure you aren't building your brand on borrowed land.
The playbook is being written right now.
Make sure you're reading it.
This settlement signals a transition.
From: "Can we generate this?"
To: "DO WE OWN THIS?"
Business leaders need to move from a reactive stance to a proactive strategy.
From: "Can we generate this?"
To: "DO WE OWN THIS?"
Business leaders need to move from a reactive stance to a proactive strategy.
January 9, 2026 at 10:00 AM
This settlement signals a transition.
From: "Can we generate this?"
To: "DO WE OWN THIS?"
Business leaders need to move from a reactive stance to a proactive strategy.
From: "Can we generate this?"
To: "DO WE OWN THIS?"
Business leaders need to move from a reactive stance to a proactive strategy.
I often tell clients: "Data quality beats AI sophistication every time."
That now applies to LEGAL QUALITY too.
If your AI vendor can't explain their data lineage...
You are inheriting their risk.
That now applies to LEGAL QUALITY too.
If your AI vendor can't explain their data lineage...
You are inheriting their risk.
January 9, 2026 at 10:00 AM
I often tell clients: "Data quality beats AI sophistication every time."
That now applies to LEGAL QUALITY too.
If your AI vendor can't explain their data lineage...
You are inheriting their risk.
That now applies to LEGAL QUALITY too.
If your AI vendor can't explain their data lineage...
You are inheriting their risk.
The question isn't just "Is this tool powerful?" anymore.
The critical question is now:
Is your intellectual property fully protected, or exposed to emerging legal challenges?
The "Wild West" of data scraping is closing down.
The critical question is now:
Is your intellectual property fully protected, or exposed to emerging legal challenges?
The "Wild West" of data scraping is closing down.
January 9, 2026 at 10:00 AM
The question isn't just "Is this tool powerful?" anymore.
The critical question is now:
Is your intellectual property fully protected, or exposed to emerging legal challenges?
The "Wild West" of data scraping is closing down.
The critical question is now:
Is your intellectual property fully protected, or exposed to emerging legal challenges?
The "Wild West" of data scraping is closing down.
Warner Music didn't just settle.
They created a LICENSING FRAMEWORK.
This is the template for how AI and intellectual property will coexist.
If you are using AI to create content, the ground just shifted beneath your feet.
They created a LICENSING FRAMEWORK.
This is the template for how AI and intellectual property will coexist.
If you are using AI to create content, the ground just shifted beneath your feet.
January 9, 2026 at 10:00 AM
Warner Music didn't just settle.
They created a LICENSING FRAMEWORK.
This is the template for how AI and intellectual property will coexist.
If you are using AI to create content, the ground just shifted beneath your feet.
They created a LICENSING FRAMEWORK.
This is the template for how AI and intellectual property will coexist.
If you are using AI to create content, the ground just shifted beneath your feet.
Where in your business is headcount being used to compensate for missing decision rights?
Rewire the business logic first.
The staffing will follow.
Rewire the business logic first.
The staffing will follow.
January 7, 2026 at 9:04 AM
Where in your business is headcount being used to compensate for missing decision rights?
Rewire the business logic first.
The staffing will follow.
Rewire the business logic first.
The staffing will follow.
Define the decision rights in writing.
Where does AI decide?
Where does it advise?
Where is it BANNED?
Example: "The AI drafts the credit memo, the manager signs it, compliance audits 5% weekly."
Where does AI decide?
Where does it advise?
Where is it BANNED?
Example: "The AI drafts the credit memo, the manager signs it, compliance audits 5% weekly."
January 7, 2026 at 9:04 AM
Define the decision rights in writing.
Where does AI decide?
Where does it advise?
Where is it BANNED?
Example: "The AI drafts the credit memo, the manager signs it, compliance audits 5% weekly."
Where does AI decide?
Where does it advise?
Where is it BANNED?
Example: "The AI drafts the credit memo, the manager signs it, compliance audits 5% weekly."
Standardise your inputs.
Fix the data and process inputs the model relies on before you try to scale the output.
Garbage in at speed is just faster failure.
Fix the data and process inputs the model relies on before you try to scale the output.
Garbage in at speed is just faster failure.
January 7, 2026 at 9:04 AM
Standardise your inputs.
Fix the data and process inputs the model relies on before you try to scale the output.
Garbage in at speed is just faster failure.
Fix the data and process inputs the model relies on before you try to scale the output.
Garbage in at speed is just faster failure.