Original Title: Your Startup Is Probably Dead On Arrival
Original Author: Steve Blank, Expert on Startup Methodologies
Original Translation: Deep Tide TechFlow
Deep Tide Guide: The author of this article, Steve Blank, is very famous in the Silicon Valley startup circle and is known as the "Father of Lean Startup." He wrote "The Four Steps to the Epiphany" and is the proposer of the Customer Development methodology.
Eric Ries's "The Lean Startup" developed on the basis of his theories. He has taught startup courses at Stanford, Berkeley, and Columbia University, and the I-Corps program of the National Science Foundation is also built on his methodology.
Recently, Steve Blank had coffee with a founder he had invested in and found that the person had been focused on work for six years without realizing that the outside world had changed dramatically.
He wrote this article based on that experience, and the core point is straightforward:
If your company has been established for more than two years, your business plan is likely outdated. AI is reshaping development speed, team size, pricing models, and competitive barriers. Founders still operating under the 2024 script are unlikely to reach the next round of financing.
For readers who are starting their own businesses or are interested in the tech and venture capital circles, firsthand observations from across the ocean are worth reading.
The following is a complete translation.
If your company has been established for over two years, many of the assumptions you made initially are likely no longer valid.
You need to pause what you are doing, whether it is coding, product development, hiring, or fundraising, and first see what is happening around you. Otherwise, the company will die.
Anxiety Triggered by a Cup of Coffee
I just had a cup of coffee with Chris. Chris is a founder I invested in six years ago, and since then he has been focused on working on:
1) A complex autonomous systems problem,
2) In an existing market,
3) Using a unique business model.
Chris is now preparing to initiate the first round of large-scale financing. I looked at his investor deck and found one problem: While he was dedicated to his work over the years, the outside world has changed dramatically.
The autonomous system software barrier he spent five years building is becoming less and less unique. Ukrainian autonomous drones and ground vehicles have spawned dozens, even hundreds, of companies that have larger teams and more funding, all doing the same thing.
Chris has been vying for customer adoption in his niche market (which indeed needs to be disrupted, but the old players are still holding on), while at the same time, the autonomous technology demand in a neighboring market, which is defense, has exploded.
Over the past five years, VC investments in defense startups have skyrocketed from zero to $20 billion annually. His product is perfectly suited for logistics support and medical evacuation in contentious environments. But he is completely unaware of these opportunities in the defense market.
Chris's team has indeed accomplished impressive system integration (deep integration with an existing flight platform, which makes his solution different from most competitors), there is still business, but it is no longer the business he initially envisioned.
After talking to Chris, I realized: Most startups that have been established for over two years have outdated business plans, and their tech stack and team configuration are likely obsolete as well.
If you haven't been paying attention lately, here's what you've missed.
What Has Changed
VC money is significantly flowing into AI. By 2025, AI projects will account for two-thirds of the total VC investment. This means that if what you are working on is not AI-related, you are competing for a smaller pool of funding. Non-AI startups must answer one question: Why can't a more well-funded AI-native competitor directly take over your market?
For software founders, AI has completely rewritten the old formula of costs, speed, and manpower. With tools like Claude Code or OpenAI Codex for Vibe Coding, an MVP (Minimum Viable Product) can be completed in days or even hours, no longer requiring months. This also means that the MVP itself no longer proves your team’s capabilities.
These tools are changing the composition of development teams: The number of engineers is decreasing, and the types of engineers have also changed, with the emergence of "Business Process Engineers" and "Deep Tech Engineers."
What used to require a development team can now be accomplished by just a few people, and sometimes even one person. Data was once a differentiation advantage and a moat, but current foundational models (ChatGPT, Gemini, Claude) are commoditizing public data sources.
Caption: Model T vs Ferrari
The very concept of agile development also needs to be rethought.
The past bottleneck was: Can we afford to build and release this product? The current bottleneck is: Do we know what to test? Can we reach users fast enough to learn? Agile is no longer a serial process. AI Agents can run multiple things in parallel at the same or even lower costs.
You can now test multiple versions of the same business simultaneously, or even test different business directions at the same time. You can simultaneously run five pricing models, ten marketing messages, and twenty UX processes. And the "user interface" may no longer be a screen; the testing goal may shift to finding the prompts that enable AI Agents to deliver the expected results.
Caption: The Shift from UI to AI Agent
The bottleneck is no longer engineering capability, but has shifted to judgment, insight into customer expected outcomes, and distribution capability.
AI Agents Will Rewrite All Software Categories
AI Agents will change every software category, including the one you are in.
Today's software applications operate like this: they display information to users and then wait for users to act through dashboards, alerts, workflow tools, and reports. But customers buy software to get a job done, not to view more screens. Getting the job done effectively is something AI Agents (orchestration through tools like OpenClaw) will autonomously accomplish.
What does this mean?
If your product currently tells users "what to do next," AI Agents will ultimately do that step for the users. If your competitor's product can automatically complete the task while yours is still waiting for a user to click the mouse, you will no longer be competitive.
The next generation of applications will not just display information on the screen; they will operate like employees: solving tickets, booking meetings, filtering sales leads, automatically restocking supplies. As products shift from "software as interface" to "software as results," pricing will shift from per seat to per outcome: per ticket resolved, per meeting booked, per lead closed.
(The pursuit of Product/Market Fit will become the pursuit of AI Agent/Customer Outcome Fit. MVP will transform into MPO (Minimum Deliverable Outcome). I will elaborate on this topic in the next article.)
Hardware Also Cannot Escape
For hardware founders, the changes are equally drastic. Hardware is still constrained by physical laws, capital, supply chains, and manufacturing cycles, and you cannot bypass cutting metal, prototyping, or chip fabrication.
But AI allows you to more quickly eliminate bad ideas. You can now simulate more design variations, create digital twins, and pressure test various hypotheses earlier and cheaper before manufacturing physical prototypes. The result is an accelerated pace of learning and discovery (sometimes leading to a quicker failure), and in startups, failing faster is an advantage, not a drawback.
Once AI is embedded into the system, the product itself changes. Adding an AI backend to a camera transforms it into a surveillance system, vibration sensor, or machine fault prediction system. Robots become factory workers. The moat is no longer just the hardware itself but also what the hardware can sense and what decisions and actions AI can take using that data.
The Sunk Cost Trap
Companies founded before 2025 typically have tech stacks optimized for an expensive and customized world of software development. Agile development and DevSecOps have made us lean, but they operate serially, and team sizes are structured accordingly.
Companies that have spent years building "proprietary code and feature moats" are discovering that AI is commodifying most of their tech stack. This places fundraising startups in an awkward position: their business models may be partially or fully outdated.
When you are focused on building a product and searching for Product/Market Fit, these changes may not be readily visible.
Tech stack, product features, user interfaces, employee counts—these sunk costs become reasons for you to resist transformation: How can we throw away years of work? Our VC invested in this direction. Customers still want UI. The team believes in this roadmap. Our customers are not ready.
(Chris is a typical example. He created something truly impressive and probably still has competitiveness, but the business model surrounding it needs to change.)
Some sunk costs are actually assets: deep domain knowledge, customer relationships, proprietary data, hard-won regulatory approvals, physical integrations. These are worth keeping. Chris's flight platform integration falls into this category.
The truly burdensome sunk costs are: large engineering teams built for slow software cycles, per seat pricing models, and product roadmaps built around features instead of outcomes. These are the so-called "dead moose on the table," obvious problems that no one wants to address.
Surviving founders are those who can look at what they have done and ask: If I were to start over today with today’s tools in today’s market, what would I do?
This question is uncomfortable when you are already committed to financing a specific direction. But it is better than having investors tell you they do not plan to invest in the next round, and then you close your doors with an outdated plan.
Conclusion
· You cannot run a 2026 track with a 2024 (or earlier) script. Financing, technology, and business models have all changed. Agile development is transitioning to parallel development.
· The pursuit of Product/Market Fit will become the pursuit of AI Agent/Customer Outcome Fit. MVP will become MPO (Minimum Deliverable Outcome).
· A sunk cost mentality could lead to your closure.
· Defensible moats may still exist in: proprietary data, deep understanding of customer outcomes, regulatory lock-ins, or becoming a Program of Record.
· If you can still sleep soundly, it means you haven't figured out what is happening.
· Surviving founders will step out of the office, assess the situation, transform, and correct their course.
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