Tariq Deir: Writing

Sometimes the decision is outside of your control.

2026-08-24T00:00:00Z

Three weeks ago I published the empty leg analysis behind Empty Leg Finder, the SaaS platform I'm contracted to lead.

Fifty thousand empty legs deeply analysed and cross referenced coupled with a heap of customer retention data, forming the case for a discovery led marketplace over search-first marketplace.

This week the decision came back: return to V2. Shelve V3.

And as I don't own this project and many of the decisions, here's what I've learned sitting with that and processing it.

Evidence isn't mandate.

Data tells you what's true, it doesn't tell you who decides. Those are two different jobs, and confusing them is how product people break their own hearts.

Here's the shape of it: You're hired to find the answer, talk to users, run the analysis, follow the behaviour. You do the work honestly and the evidence points somewhere unexpected, perhaps somewhere better. You bring it back, certain the data will speak for itself.

It doesn't because data never speaks for itself. Someone with capital at risk speaks for it, and they're weighing things your spreadsheet can't see: sunk investment in the existing product, appetite for mid-year risk, promises already made to people you've never met. The evidence was your job, the decision was never yours to make.

That just happened to me. Three months of build and discovery work pointed clearly away from our current product toward a new concept. The stakeholders looked at the same data and chose the current product anyway.

They have a case. The existing product is revenue; my concept was a thesis. Pivots are expensive, and the people funding the risk get to price it. If I can't argue their side convincingly, I haven't understood the decision — I've just resented it and resent doesn't get you very far in life.

Concepts die. Learnings compound.

The product was never the only output. It was the container for the output.

Let me explain.

The last months of building and discovery gave me findings that don't care which product they live in. That our best-retained customers were the ones who barely touched the product, they wanted to be tapped on the shoulder, not handed a search box. That users search where they think the market is, while the actual supply sits somewhere else entirely. That the product I should have been building was a discovery engine, not a search engine.

The concept built on those findings might be dead but the findings aren't. Every one of them now shapes how I execute the product the stakeholders chose, from where I target acquisition, to what I make the conversion event, to which users I go and find. Same evidence, different vehicle.

I wrote last week that your effort isn’t the asset the learning is. It was easy to write when it cost nothing, but this month it cost me three months of work and a concept I believed in, and I found out whether I actually meant it.

I did. But I’ll be honest, as I’m only human: it took a day or two of being annoyed first. Then you have to remind yourself, principles only held in victory aren’t principles. They’re predictions.

So the shelved work sits documented and waiting, and I execute the current product with full commitment, not grudging compliance, pure commitment.

Market data doesn't expire just because a decision did and if the thesis is right, it'll still be right in six months.

Catch you in the next one.
Tariq

Sometimes your best customers barely use your product

2026-08-20T00:00:00Z

I noticed something slightly uncomfortable in my product and customer data this week.

I have been auditing flights and speaking to existing customers nonstop whilst building out version three of Empty Leg Finder.

And this latest finding stopped me dead in my tracks.

In fact, I double and triple checked it because I wasn't entirely sure I believed what I was seeing: some of my best customers barely use the product.

At first, that sounds bad.

No, scratch that.

It sounds fucking terrible.

Surely the people getting the most value should be logging in, searching constantly and clicking around like maniacs?

Well, for a product in the empty leg space, apparently not.

Now, this would have caught me completely off guard had I not already been suspicious that search was the wrong front door, I may have even shed a few tears.

When I looked at members who had stayed subscribed for three months or more, a pattern jumped out.

These users were hardly ever searching.

Most of them signed up, told us where they fly from, set up alerts and then disappeared.

Meanwhile, many of the customers who joined, searched heavily, set no alerts and tried to find a specific flight churned within 30 days. In fact, they would often churn within the first week.

It's weird when you're effectively building a case against your own product after spending so much time building it.

But such is life.

I've been in business long enough to know that the market does not care how hard you worked on something.

It cares how valuable that thing is to them.

And perhaps, for this product, in this specific market, maybe, just maybe, I've been looking at engagement completely backwards.

If someone has to keep opening my product every day to get value from it, perhaps I haven't actually removed much work from their life? For some apps that is the correct shape, you want to create something sticky and engaging.

But it would seem my longest-standing members don't want another platform to browse.

They want me quietly watching thousands of flights and tapping them on the shoulder when something relevant appears.

The less they need to do, the better the product might actually be working.

Again, it's all so obvious in hindsight when you've got five or six months of data sitting in front of you.

I admit, that creates a strange problem for builders because we're conditioned to celebrate activity.

Sessions. Searches. Clicks. Time in product.

But those metrics only matter if activity is actually the thing the customer came for in the first place.

Sometimes the job of the product is to make the activity disappear.

I don't know yet if this observation leads to the right version of Empty Leg Finder.

But when the people who stay behave completely differently from the people who leave, you'd be an idiot not to pay attention.

So what am I going to do about it?

I've built a fresh concept on Replit that I'm deploying this week to test whether I can get 20 members paying for the service within the next 30 days.

No point burning down V2.

No point throwing away the progress we've made on V3.

And equally, no point defending either of them just because I've spent months working on them.

If this new concept runs and gains traction, it will give me a much stronger signal for how I approach finalising V3.

And that brings me to the lesson I think is probably more important than anything else in this essay.

Do not get emotionally attached to your effort.

That is how sunk cost starts creeping into your decisions.

You stop asking, is this still the right thing to build?

And start asking, how do I justify everything I've already built?

Those are very different questions.

When we start a new product, offer or concept, we have no choice but to work from assumptions.

We take risks.

We make bets.

We build things without knowing whether we're right.

That's the job.

But those assumptions should eventually be replaced by evidence, not by:

Well, I've already spent six months building this, so I might as well carry on.

I've built V2.

I'm building V3.

And now some of the data is challenging one of the assumptions sitting underneath both.

My options are pretty simple.

Ignore it and protect my ego.

Burn everything down and overreact.

Or run another small bet and let customers tell me whether there's something here.

I'm choosing the third one.

Yes, it sucks when the market challenges something you've put a huge amount of energy into.

But that's the cost of admission and, in my opinion, the privilege of getting to compete.

Your effort isn't the asset.

The learning is.

Another assumption challenged, another small bet going into the market.

We keep chipping away until we deliver something undeniably valuable for the people we're trying to serve.

Catch you in the next one.

Tariq

I analysed 50,000 empty legs and realised we were solving the wrong problem

2026-08-08T00:00:00Z

Empty Leg Finder V2 is live. People are paying for it, the product works, and I’m currently working out what V3 should become.

Today I realised we might have built the core experience around the wrong behaviour, and I've had this hunch for a while.

For anyone unfamiliar with the problem, an empty leg is created when a private jet needs to reposition without passengers. The aircraft is flying anyway, the operator would obviously rather put somebody on it, and that creates an opportunity for a traveller to fly privately for considerably less than arranging a normal charter.

In theory, that makes for a fairly obvious marketplace. Someone tells us where they want to depart from, where they want to go and roughly when they want to travel. We find an empty leg that matches.

That’s essentially how Empty Leg Finder has worked.

Except there’s one fairly significant problem: the data says those matches are incredibly unlikely to happen.

I had a hunch that something was wrong

Something about the existing search experience has been bothering me for a while.

We have supply. Quite a lot of supply, actually. But when you interact with the product like a normal travel search engine, it can still feel empty. You choose where you want to leave from, choose where you want to go and get nothing back.

From the customer's perspective, the obvious conclusion is that we simply don't have enough inventory. That’s a perfectly reasonable conclusion too, you searched for a flight and there wasn’t one.

But I wanted to understand whether that was actually what was happening. Do we genuinely have a supply problem, or have we designed a matching experience that makes perfectly good supply almost impossible to find?

So today I audited the data.

We have 50,819 raw empty-leg records collected over roughly eight months. After removing duplicates, that's 49,484 distinct opportunities. There are caveats to the dataset, which I’ll get into later, but it’s enough data to understand the basic shape of the inventory we’re trying to build a product around.

And the shape is weird.

Across those empty legs there are more than 22,500 different directional routes. Of those routes, 64.8% appeared exactly once.

Not once a month. Once in the entire dataset.

The top ten routes combined account for just 2.6% of all supply, and the top 50 only account for 7.7%. Even the single busiest directional route I found — Las Vegas to Van Nuys — appeared 282 times across the dataset.

That sounds like plenty until you remember we’re looking across roughly eight months. One of the strongest exact routes in the entire marketplace still only shows up at around once per day on average.

Now imagine you aren't searching one of the strongest routes. You're searching whatever combination happens to fit your plans next Thursday.

The odds get ugly very quickly.

Then I removed the destination

This was the test that changed how I'm thinking about V3.

Instead of asking, “How many empty legs match this departure and this destination?”, I asked a different question: “How many empty legs are available from this departure if the traveller is flexible about where they go?”

I tested it against high-, medium- and lower-volume airports.

From Teterboro, the most common exact destination produced 79 opportunities in the dataset. Remove the destination requirement and there were 1,706 departures.

That’s roughly 22 times more inventory.

At Centennial Airport near Denver, the strongest exact route produced 28 opportunities. Allow any destination and there were 348 — more than 12 times as many.

Kansas City showed the same thing. Its strongest exact route produced 11 opportunities, versus 141 when the destination was flexible. Nearly 13 times more.

The important thing here is that I'm deliberately comparing flexible discovery against the best-performing exact route from each airport. Those aren't randomly chosen destination pairs. They're the routes where traditional search has the best possible chance of succeeding.

A typical route is substantially worse.

In practical terms, requiring somebody to specify both an origin and destination can hide more than 99% of the available supply around them.

That was the penny-drop moment for me.

Maybe people aren't supposed to search empty legs.

Maybe they're supposed to discover them.

We may have built the interaction backwards

Normal travel starts with intent. I know where I am, I know where I want to go and I know roughly when I want to travel. An airline or hotel search engine then shows me the inventory that satisfies those requirements.

That works because commercial aviation operates predictable schedules between predictable destinations.

Empty legs don't.

The aircraft isn't flying because of your travel plans. It’s flying because an operator needs the aircraft somewhere else. Your opportunity exists when your plans happen to intersect with where that aircraft is already going.

Writing that down makes it sound annoyingly obvious.

But it has fairly significant implications for the product.

V2 effectively begins with: Where do you want to go?

I'm increasingly convinced V3 should begin with: Where are you?

From there, we can show you what's actually possible.

If you're in New York, maybe there are aircraft leaving from Teterboro, White Plains, Morristown or another nearby private aviation airport over the next few days. One might be going to Miami, another to Nashville, another to the Caribbean and another somewhere you hadn't considered at all.

The important thing is that we're starting with the inventory that actually exists rather than asking the customer to guess the route on which it might exist.

That isn't really search anymore.

It's discovery.

And when I look at the supply through that lens, the marketplace suddenly looks very different.

We’ve also been making people understand private aviation geography

Another interesting problem turned up in our search data.

Users tend to search the airports they know.

Again, this is completely reasonable. Someone in Los Angeles searches LAX. Someone in New York searches JFK. Someone in Miami searches MIA.

But that's often not where the private aviation inventory sits.

In Los Angeles, significant empty-leg supply sits around Van Nuys and other business aviation airports. In New York it’s heavily concentrated around Teterboro. In South Florida, Opa-locka matters considerably more than most normal travellers would ever realise.

So you can have a situation where a customer is geographically very close to an empty leg, but because we've asked them to specify an airport rather than a location, the product decides there isn't a match.

That isn't a supply problem either. It's a product problem.

We're effectively asking customers to understand private aviation's airport network before we're willing to show them what’s available.

Which, when I put it like that, is a pretty crap user experience.

If somebody tells us they're in Los Angeles, the product should understand what "Los Angeles" means in the context of private aviation. The customer shouldn’t need to know which airport an operator prefers or what its ICAO code is.

That’s our job.

The radius matters more than I expected

Once I started thinking geographically rather than in exact airport pairs, the obvious next question was how far the product should look.

At around a 50-mile departure radius, the amount of available inventory increased by roughly 1.3 to 1.8 times in the markets I tested. Push that radius out to 150 miles and it can increase by two to four times.

Sounds great. Keep expanding the circle.

Except that eventually you start lying to people.

At 150 miles you're frequently pulling in an entirely different market. Denver starts picking up airports around Aspen and Eagle. Other cities start bleeding into neighbouring metros. Technically there may be a jet within the radius, but “private jet deals leaving near you” becomes a fairly generous interpretation of the word near when somebody has to drive for three hours.

So I'm currently leaning towards roughly 50 miles as the default interpretation of nearby, with perhaps a separate regional option for somebody willing to travel further for the right aircraft or destination.

I don't know exactly where we'll land yet, which is partly why I'm writing this now rather than six months from now with the benefit of hindsight.

The point is that geography has clearly turned out to be a better way of understanding the supply than exact airport matching.

This is also an incredibly short-fuse product

Another number from the audit that matters is 4.4 days.

That's the median time between an empty leg being listed and the aircraft departing. A quarter of the inventory appears less than a day before departure.

So this isn't just discovery-led inventory. It’s short-fuse discovery-led inventory.

That potentially changes how I think about the customer relationship too.

Perhaps the useful question isn't, “Where would you like to fly next month?”

It might be, “What's leaving near me this week?”

And if there isn't anything interesting today, the product should remember where you are and surface something when it appears.

Tell us where you live. Tell us where else you regularly spend time. Perhaps tell us how far you'd travel to catch the right aircraft. Then let Empty Leg Finder watch the market rather than requiring you to repeatedly search it.

That starts to feel much closer to the behaviour of the underlying supply.

I don't think this works equally well everywhere

There is a temptation here to turn “empty legs near you” into a universal marketing promise.

The data doesn't support that.

Within 50 miles of New York, the dataset contained 2,690 opportunities across 412 destinations. Las Vegas had 1,990. Miami had 1,706, Dallas 1,418 and Los Angeles 1,303.

Those markets have enough recurring supply to support a fairly compelling discovery experience.

Portland had 141 opportunities over the same period. Minneapolis had 189.

That's a very different product.

Rather than pretending otherwise, I think the right experience in those markets is probably something like: there isn't anything particularly interesting near you right now, but save your location and we'll tell you when there is.

This is one of those areas where I think marketplace products get themselves into trouble by trying to make the same promise everywhere. Our supply isn't distributed evenly, so the product experience shouldn't pretend that it is.

The stronger version of Empty Leg Finder might actually be one that knows when not to show you a load of rubbish.

There are also several things this data doesn't tell me

Having nearly 50,000 opportunities in a spreadsheet creates the dangerous feeling that you know more than you actually do.

There are some important limitations here.

Our feed coverage changed significantly over the period I analysed, particularly after a new source came online in May. That means I cannot look at the increase in listings and tell you that the empty-leg market is rapidly growing. Much of that increase is simply us seeing more of the market.

Pricing is another one. Only 5.5% of the opportunities had a usable published price. Among those that did, the median was around $5,500, which is interesting, but the priced subset is heavily skewed towards particular feeds and aircraft categories.

So I'm definitely not about to start publishing “the average empty leg costs $5,500” all over the internet.

Most importantly, our data tells us that an operator listed an empty leg. It doesn't tell us whether that aircraft was still available when a customer enquired, whether somebody eventually booked it, whether the operator repositioned it differently or whether something else happened.

Listed supply is not necessarily actionable supply.

That is probably the biggest hole in the dataset today, and it's something V3 needs to help us measure.

Such is the joy of answering one question and creating another five.

So where does that leave V3?

I started today trying to understand how we could make search better.

I'm ending it questioning whether search should be the primary experience at all.

My current thinking is that Empty Leg Finder should become a discovery-led marketplace rather than a search-led one.

Tell us where you are. We'll understand the private airports around you, surface the empty legs leaving nearby and let you explore where those aircraft could take you. If there isn't anything useful today, we'll keep watching.

There will still be search. I'm not deleting a perfectly sensible feature because I got excited by a spreadsheet.

But I increasingly think search should be secondary rather than the organising principle of the entire product.

The bigger lesson for me is that what looks like a marketplace liquidity problem can sometimes be a matching problem.

We had thousands of flights in the database and users could still quite reasonably conclude there was nothing available. The inventory wasn't necessarily missing. We were just asking customers to describe their intent in a way that had almost no chance of intersecting with it.

Destination flexibility exposes 12 to 22 times more inventory. Nearby airports add another meaningful increase. Exact routes are extraordinarily fragmented. And customers themselves are already telling us, through the airports they search, that they think geographically rather than in terms of the private aviation network.

That's enough evidence for me to continue building V3 in this direction.

It isn't enough evidence to tell me whether customers will actually behave the way I think they will.

I'll find that bit out by putting V3 in front of them.

Catch you in the next one,

Tariq

Why did I start this site?

2026-07-28T00:00:00Z

I have forgone coming up with a fancy hook to draw you in. The temptation was there, but sometimes you just want to write for writing’s sake instead of trying to optimise this or maximise that.

And as I’m constantly optimising and iterating in my day-to-day life, I’ve given myself permission to just blurt words onto a page, and it’s incredibly refreshing, in fact it's almost cathartic.

Perhaps I should end the essay there, because that is reason enough, but that would be incredibly selfish of me.

Although there is some truth in that last sentence, and If we were being completely honest with ourselves, the vast majority of what we do is a selfish pursuit to improve our own lives.

Is that not why many of us became business owners, founders, creators, makers or indie hackers in the first place?

We rejected what the world was lining up for us, or perhaps we sampled the 9-to-5 life, recoiled and thought: “Not for me, there must be another way”

That was certainly my experience.

I knew pretty early on that working for somebody else would not suit my wiring very well as I hated not being in control. I was rebellious, and I found the day-to-day experience of school lacklustre outside of socialising, chasing girls and playing sport.

Later in life, I could put much of that down to ADHD as my brain works on urgency, novelty, challenge and interest, rather than importance in the way many neurotypical brains seem to.

Already dropping fun facts.

I digress.

Founder life

The pursuit of being a founder, as painful as it can be, is incredibly rewarding, painful, but incredibly rewarding.I felt repeating that would generate more impact, you’ll have to let me know whether it worked.

There is no feeling quite like working through a challenge, figuring something out, hitting a breakthrough, failing, retrying, failing again and then finally winning.

But it's also an incredibly lonely experience.

Very few people understand the day-to-day reality, the difficult decisions, or the fact that you often have to make those decisions with 60%, perhaps 70%, of the information available.

That is simply the risk we accept.

And I want to get back in that seat after spending the last four years of building for others.

So what do I want to get out of this?

When I combine all of that and ask myself the question again, why did I start this site? I think the answer is something like this.

I want to create leverage and expand the opportunities available to me by building a body of work around my name.
I want to own something again, something that I have total creative control over and which direction to point in next.
I want to improve my thinking, clarify my ideas and become better at expressing them.
I want to connect with other founders who, much like me, enjoy eating glass and occasionally question whether they are masochists.
I want to create a public record of my thinking, the experiments I run and how my beliefs or frameworks change over a long enough period of time.
I want to help other founders by providing a real and present view of building, running and acquiring customers for their own products.

Tired of polished BS

And I am genuinely tired of the slop all over the web and social media in addition much of what we read is polished backwards.

The result is already known, the story has been cleaned up and the difficult decisions, uncertainty and wrong turns have been edited out until the whole thing looks inevitable.

Fucking inevitable.

I want to share the present moment instead and all of the uncertainty of the present, you know, how to think about a rapidly changing environment as it's rapidly changing.

What I am doing now, what I think will happen, what actually happens and how I respond when those things are not the same.

I'm going to fuck up, I'm going to miss a publication date, I'm going to publicly make a few large mistakes while sharing the receipts with you.

And as scary as typing that out feels, there is something romantic and strangely addictive about it.

Anyway, less ranting and more focused writing will follow.

But I wanted to explain why I started this site without framing it as a perfectly optimised, entirely selfless pursuit designed to maximise your engagement and goodwill.

It is very much a selfish pursuit.

My intention is to make it useful and valuable to you too.

Catch you in the next one,
Tariq

Letting go of desires

2025-09-13T00:00:00Z

Originally published September 2025. Part of the Archived Essays collection.

During my Sunday reflection, I revisited a quote from James Clear I’d captured earlier in the week:

“It doesn’t make sense to continue wanting something if you’re not willing to do what it takes to get it.

If you don’t want to live the lifestyle, then release yourself from the desire.

To crave the result but not the process is to guarantee disappointment.”

Let that sit for a moment.

Then think about where you are right now — and whether your behaviour and habits actually match your desires.

Borrowed desires

Often, our goals and dreams aren’t really ours.

We adopt them because they sound impressive, or because everyone around us seems to be chasing the same things.

The 8-figure business
The shredded physique
The “I only work 4 hours a day” setup

Some of those might be genuinely yours.

Others are just borrowed desires.

They feel good to say out loud. They look good in a bio. But you don’t actually want the process they require.

Drifting into other people’s goals

There’s another, riskier path: the goalless traveller.

You don’t define what you want, so you drift.

And drifting means you’re quietly absorbed into other people’s desires.

The company you work for
The friends you keep
The accounts you follow

It feels harmless in the moment.

It isn’t.

The cost shows up later, when regret asks why you never tried harder for the things that were truly yours.

My own version of this

When I was younger, I lived in that first camp.

I’d say things because they sounded ambitious. It felt good — a quick dopamine hit.

But that’s where the goal lived and died.

I didn’t want the work.

I wanted the feeling.

That quote from James Clear is brutal because it’s honest:

“If you don’t want to live the lifestyle, then release yourself from the desire.”

It’s a line worth revisiting at least once or twice a year — especially before you start declaring big goals you have no real intention of living the process for.

A question worth sitting with

Ask yourself:

Which desire do you need to release because you won’t live the process it requires?

There’s no shame in letting it go.

In fact, it might be the most productive thing you can do.

Less fake desire.
More honest effort.

—Tariq

When execution becomes cheap

2025-09-10T00:00:00Z

Originally published September 2025. Part of the Archived Essays collection.

“Holy shit.”

Those were the first words out of my mouth when I revisited Replit after Agent 3 dropped.

From ideation to coding to debugging, a swarm of agents collaborated like a relay team passing the baton:

The Fullstack Agent handled the backend
The Architect reviewed and tweaked
The Tester hunted down the bugs

In under two hours, I had a functional app that would’ve cost five figures three years ago.

I’ve been into tech and building for years, but this felt different.

It felt like watching the future assemble itself in real time.

Ideas, knowledge, execution

Every week, new capabilities land and every week, it gets easier to build and ship.

AI isn’t a silver bullet and currently there’s more hype than signal, but ignoring what’s happening now would be as foolish as believing every headline.

We’re just not wired to grasp exponential change.

The “build stack” used to look like this:

Ideas
Knowledge
Execution
Distribution

Now it’s shifting.

Ideas

Ideas have always been abundant.

Everyone has them, good, bad, brilliant but few are brave enough to expose their ideas to reality.

We all know the person who says:

“I had that idea years ago.”

Cool. But you didn’t ship.

Ideas were never the bottleneck.

Knowledge

Knowledge used to be a moat.

In the early 2000s, it lived behind university walls and paywalled journals.

By 2010, it exploded: YouTube, blogs, online courses, forums. The internet handed anyone motivated enough a near-free education.

Knowledge went from privilege to commodity.

Execution

For the longest time, execution was a huge area of leverage.

You could have the idea and the knowledge, but you still needed capital, talent, and operational skill to turn it into something real. That’s where the founder’s edge lived.

That edge is eroding.

I’ve seen it firsthand: it cost me ~£50 of compute, an hour of planning, and an hour of tinkering to build a functional MVP with AI agents.

No team, minimal risk, just prompts and an agent network doing the work.

Yes, humans still have to be in the loop—especially on hard, technical or domain-specific problems, but the baseline cost of execution is falling fast.

Execution is on a fast track to join knowledge and ideas in the commodity bin.

Which leads to the next question:

When everyone can build almost anything, what still matters?

Discernment & distribution: the new edge

The edge is moving from execution to discernment and distribution.

When building and writing code get close to free, your advantage becomes:

Knowing what not to build
Seeing which problems actually matter
Translating those problems into clear instructions for agents and systems
Designing environments that feel stable, meaningful, human
And getting the product in front of the right people

Because in a world where everyone can make, the only thing that matters is whether anyone cares.

Execution and speed will continue to level out.

Discernment and distribution is where the gap reappears.

The implications

When execution becomes cheap, the value moves elsewhere:

Into meaning – why this product or system should exist at all
Into trust – why anyone should rely on it
Into discernment – how you decide where to aim your energy
Into distribution - how do I get this out to the right avatar at the right time

We’ll need to redefine what “creating value” means when anyone can spin up an app, newsletter, or agent army on a weekend.

We’ll have to untangle identity from output:

If a machine can do a task faster, what is your role?
If tools handle the busywork, what do you measure yourself against?
If execution is easy, what do you choose to build anyway?

That’s where it gets uncomfortable—and where the real work starts.

As tools become more intelligent, the humans who thrive will be the ones who stay intentional:

Clear on their lens
Clear on their constraints
Clear on what they’re optimising for

Where the edge lives now

So where does the edge live today?

It’s still early, but my current bet:

The edge belongs to those who can move fluidly across disciplines, see clearly, and decide precisely.

People who can:

See patterns across domains
Frame problems in ways agents + humans can work on
Design simple, elegant systems around those problems
Tell compelling stories about why those systems matter
Distribute those stories to the right people

Well-rounded generalists and multi-skilled operators are going to rise:

Strategic organisers of systems, data and experience across all slices of business
Translators between business, tech and humans
People who weave coherence from chaos and build communities around it

In one of my recent projects, discernment meant ditching a flashy AI feature that demos well for a “boring” one that built user trust.

The result?

Stickier engagement, better retention and much less noise in support.

FAQ: navigating commoditised execution

What is “discernment” in the context of AI building?

It’s the discipline of prioritising what matters over what’s possible.

The temptation in an AI-rich world is to add every shiny capability. Discernment is asking:

“Does this solve a real problem?”
“For a real person?”
“In a way that fits the system and business I’m building?”

It’s turning down 90% of what you could build so you can go all-in on the 10% that matters.

How does this shift impact founders specifically?

It democratises MVP creation but raises the bar on strategy and clarity.

You can build faster. You can test more ideas. But:

You need a sharper ICP
You need clearer constraints
You need better judgment on when to say “no”

You’re no longer rewarded for “I built this”; you’re rewarded for “this meaningfully moved the needle.”

What edges remain for humans in an AI-heavy landscape?

Focus on traits machines don’t replicate well:

Curiosity
Empathy
Cross-domain pattern recognition
Taste
Community building

AI investments will keep ramping, tools will keep getting better, but people still buy from, follow, and build with humans they trust.

Should I be worried about my skills becoming obsolete?

Only if you treat them as fixed.

Treat your expertise like software:

Update or obsolete.

The founders who thrive will be the ones who learn, unlearn, and relearn—continuously.

Not in frantic panic, in steady, deliberate cycles.

The beauty of building right now

This is just the beginning of what’s next.

We’re all going to have to figure out:

How we build alongside machines
Where our edges move
How we keep meaning alive as tools accelerate

The world isn’t fixed, you can push it, shape it, and something will move.

That’s the beauty of building in this moment: You don’t need permission.

You need curiosity, intent, and the courage to ship.

—Tariq