If you started a company two years ago, many assumptions are no longer true

So previously the bottleneck was production. I'd wager now the bottleneck is willingness to test your hypotheses. The willingness to experience failure as soon as possible. To test and iterate.

As technology brings the cost of everything else to 0, psychological costs will predominate.

Reality testing is ultimately unavoidable, of course, but I'd guess most people still lean away from that rather than into it. (Our whole culture is set up that way, and most of us get like two decades of Pavlovian conditioning in that direction.)

Edit: Expanded here: https://nekolucifer.substack.com/p/willingness-to-fail-is-no...

The post reads like written by someone who read too much about AI rather than tried to build a startup with the help of AI that they advocate so much. I'm still bounded by system design, UX, pricing and feature decisions, if not by the speed of code output, by the review time for sure. Yes, iterating is faster, but we're nowhere near agentic AI loops spitting out working products. Technically it's possible, but then you just spent that time planning and writing the spec up front, which you'd interleave with dev time otherwise. If the product is a simple CRUD database skin, then yeah, chances of success are lower I think, but this is not the type of startups the post seems to write about.

> the bottleneck is no longer engineering, it’s ____

90% of blog articles created in the last two years are probably dead on arrival

Well of course it is, most startups are dead on arrival.

The big pinch of salt I throw in with advice like this though is that startup failure rate hasn't dramatically shifted despite two decades of lean startup methodology, accelerators, and an entire cottage industry of startup advice. It's never the fault of the framework, mind you.

It’s sad but at the same time reassuring to see more and more of your childhood “heros” revealing their ignorance and lack of wisdom.

I think Blank's story is about a guy who missed a $20B market shift in defense VC, not a guy who failed to adopt AI.

He's not saying "add AI to your product" or "use AI or die" but more that AI has shifted institutional assumptions about tech stacks, defensibility and fundability. The bottleneck moved up the stack from engineering to judgment, insight and design.

Chris lost because he was heads down building while $20B in defense VC was flowing into his exact problem space and he didn't build the boat to capture that wave.

> Founders who started pre-2025 typically have built a technical stack optimized for a world where software development was bespoke and expensive.

Of all the things that AI has changed, tech stacks aren't one of them. The bots will gladly write Typescript, Java, Python, Rust, what have you. They could not give less of a shit.

I almost feel like this is always true. Every startup is dead on arrival. Most of them fail.

You’ve always needed to constantly learn and innovate to launch a successful business.

"You better be doing something in AI" applies to Startups - businesses that are expected to spend every penny as quickly as possible, to meet the metrics needed to raise the next (bigger) round of funding.

It is also not the same as, "If you want to be a profitable company...". For that you need to somehow make more money than you are spending.

Interestingly, this was always true, it's just made more obvious when it takes less time to bring a product to a potential customer.

Launching a product was never the finish line; it was always the start line. But technical founders could trick themselves into thinking that building a product was building a business.

The same "Lean Startup" rules apply. Build something and get it in front of real people who will pay you for the thing. If they won't, back to the drawing board.

The only real "shift" I've seen is that most startups don't actually need VC at all. That's a great thing.

Building SaaS businesses has become a whole lot less capital intensive. Solo founders can go much further than they've been able to previously. New startups probably don't need funding anymore.

VC for conventional SaaS is dead.

If you started something at some point, many assumptions are no longer true, and might possibly never have been true at any moment.

That said, if you believe universe exists, chances are not null that you are correct. But solipsism might actually be right.

In case of doubt, remember that your memory might be mere illusions.

> The bottleneck is no longer engineering. It’s moving up the stack to judgment, customer insight for desired outcomes and distribution.

My posit is this: engineering never was the bottleneck, or at least hasn't been for 10 years now. Frameworks and best practices are pretty well known at this point. AI is simply exposing this reality to engineers' faces.

Proof point - most publicly traded SaaS first businesses S&M equals their R&D spend, if not dwarfs it. You're going to see this even more lopsided going forward.

This article resonated with me, especially since I've noticed the fund raising hoopla's in my circle has dramatically dropped. Either investors are tightening the belt so founder-investor fit has crossed into the realm of disillusionment

"a pricing model based on seats, a product roadmap built around features rather than outcomes [is outdated]"

I disagree with this.

On pricing, I get that agents and tokens can scale in a way that's unrelated to # of users. But for much SaaS software, AI remains helpful to a human and the human remains the receiver of value. Seat-based pricing is easy to understand and you can always layer in token/agent costs thresholds.

On features vs. outcomes, the latter is hard to define and measure in many industries. In marketing SaaS, which I know well, you can't often tell what outcome to expect. You have to try a lot of ideas and some will hit. No way a SaaS vendor can guarantee that.

> https://i0.wp.com/steveblank.com/wp-content/uploads/2026/03/...

The author didn't spend more than, maybe, 30 seconds thinking this through? Information I could've gotten in 3 seconds by opening a screen and looking at a line item, I now have to extract by writing a paragraph to an AI agent (and cross my fingers that nothing I said was ambiguous or misunderstood). And that's supposedly an upgrade?

Note the mention of "systems of record" being unsuitable for the present level of AI. The real question is whether the costs of AI mistakes and hallucinations can be dumped on some external party who can't impose costs on you. If not, there's a problem.

I read it less as “every startup now needs an AI feature” and more as “your assumptions expire faster than they used to.” That part feels true even if the examples are a bit overstated imo...

> How can we throw away years of work?

This trap has killed many startups, well before AI.

Now that code is cheaper to write, hopefully it becomes less of a problem?

In either case, founders should never fall in love with their solutions.

One assumption that's also changed: small teams no longer need dedicated QA. Tools like Autonoma (open source, getautonoma.com) use AI agents to generate and run E2E tests in real browsers, and tests self-maintain as your app evolves. One of the things making the solo-founder path more viable.

Seems like the headline should have been "is now dead on arrival". As currently written, it fails to convey the temporal aspect that is the focus of the blog post.

It also fails to convey that he's actually only talking about startups that were created 2+ years ago, rather than the many AI startups founded in the last 2 years.

the best/worst part of this is that it is obviously not written by steve blank. it does not look, read, or track like a steve blank blog piece

he obviously generated large parts of this with claude or chatgpt or whatever.

i don't know what that means for the rest of us, but boy it's a big ole spike of signal

Why not both? When the chat interface fails, you still need a UI to fix things.

If it was stretched before it's definitely snapped now. The only place I see convincing opportunity is resources and commodities.

Not being AI focused might mean fewer competitors.

> Now, before you build a physical prototype, you can simulate more design variants, create digital twins, and stress-test assumptions earlier and much cheaper than before.

Hahahahahahahaha no you can't. The rise of LLMs has done little to nothing in this area because it's very much compute-limited. Digital-twins and other ML-based strategies predate ChatGPT by a long shot. There are definitely places in hardware design where LLMs and agentic workflows will help, but that's largely because the existing tooling is utter garbage, and now the industry has a fire under its ass to make things automatable so they can build their own agents.

I dig MPO as a term and that's exactly what I think of implementing agentic systems.

Chris has been so focused for 5 years that he had no clue about anything else going on in the industry?

" In the last five years VC Investment in defense startups has gone from zero to $20 billion/year. " Really? No investment in weapons startups 5 years ago? Not even by the CIA-backed VC firms or other SoCal weapons manufacturer networks?

I think this is a lot of fluff supported by a weak anecdote.

Chris' company's assumptions are no longer true, but that doesn't apply to everyone's startup. This is mostly a Chris problem.

No, not every product can just be a chat window like in the silly little screenshot.

If the author actually wrote software they'd realize that, no, AI isn't speeding up development by any more than a modest amount. It's great that we have it and it's removing tedium but it has replaced zero engineers at my company or at any other company of anyone else I know.

And no, your company laying off some people isn't because of AI, your startup idea not getting funding is not because of AI, it's because we've been in a regular old recession which is now a developing oil crisis. Interest rates aren't 0% so nobody wants to lend money to infinite startups.

It used to be 90% of startups would unfortunately fail.

Now with AI, it is likely going to be 98%.

'Design for automation.'

depends on assumptions. thats the load bearing element. 99.99% of what was true then is still true. its mostly on the fractal churning edges where hyped change happens. things flip-flop too:

2021-2024: good time in US for EV startup

2025: terrible time in US for EV startup

2026 March/April: AWESOME time in world for EV startup

focus on fundamentals, not flakey ephemerals

2020: wise to have smart elite software engineers on your team

2021: ditto

2022: ditto

2023: ditto

2024: ditto (is this when ChatGPT launched? dont care. snore)

2025: ditto (what are YC/HN/VC hyping now? snore)

2026: ditto

2027+: ditto, likely

It is insane to me that anyone could look at the US Economy right now and think this was a good time to start a business. Between the war, AI, a pending economic recession (look at bond prices), all I see is failure. Maybe a funeral home, but that is all I can think of.

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I find the story of a startup founder who entirely missed the developments of the last two years and did absolutely nothing with AI difficult to believe. If that actually happened it's the exception, not the rule. Most startup founders are way more in-tune with AI developments. This makes it sound like Chris (the mentioned founder) is behind marketing people who use LLM bots to post slop on LinkedIn.

In that case, yes their startup is most certainly DOA.

Not if you’re launching a startup based in the real world. Tell me how AI will make a laundromat business DoA?

If your business is selling services at 40% margin that are entirely digitally based, then maybe you’ll need to cut some margin, sure.