The do-or-die situation for agents: 80% of entrepreneurs fail at this stage.
Recently, someone left a message in the background, hoping that I could talk about the current agents. I remembered that a friend seemed to have shared a Baidu agent with me for experience, saying that it was an "industry - general analysis agent" developed after half a year of hard work...
To be honest, when I used it, I had to compare relevant data and conclusions additionally, for fear of making mistakes.
With the attitude of evaluation, I used it continuously for two days. As a result, I found that this AI analyst can both make empty promises and offer useless results.
80% of entrepreneurs stumble at the crucial step of verifying the authenticity of market demand, and the applicability of this statement is increasing.
Many people are full of enthusiasm. They use cool large - model technologies to create eye - catching demos, and users also praise them as "interesting" and "cool" during the trial. But what's the result? Once it comes to charging or in - depth application, users run away faster than anyone else. Why? Because what they create is often "pseudo - intelligence" - either they complicate simple problems and force an agent shell on them, or they are obsessed with solving "potential future needs" while ignoring the real pain points of users today. The free data looks as beautiful as a flower, but it withers as soon as money is mentioned. It's obvious whether the demand is real or not.
Entrepreneurs often underestimate the "tough nuts" of enterprise - level applications: integrating an agent into a customer's intricate and outdated systems (such as CRM and ERP) is as difficult as a heart - bypass surgery, and the cost and time far exceed expectations. Even if it is integrated, when the agent "spits out" a report or suggestion, it often still needs human final review and modification. If this "last mile" cannot be completed smoothly, quickly, and cost - effectively, the value will be greatly discounted immediately.
When you tell enterprise customers about "efficiency improvement" and "decision - making assistance", smart bosses only care about one thing: "How many people can be saved? How much money can be saved? How much can the error rate be reduced? Show me the numbers!" If the value cannot be calculated clearly, the business cannot be done.
Then, what do the surviving 20% rely on?
Tencent Cloud recently achieved a remarkable result in the BIRD - Bench, known as the "world's most difficult NL2SQL exam" - ranking third globally and first in China, setting an excellent example for us.
How difficult is this exam? It throws the contestants directly into the "data quagmire" of 37 real industries such as finance and healthcare - 33GB of "dirty data" mixed with various incomplete and contradictory information, and tens of thousands of tricky questions. It requires the agent not only to understand human language (such as "find the orders that failed the quality inspection") but also to quickly and accurately "fish out" the answers from the chaotic database.
Tencent's agent is said to have scored 75.74 points. The key lies in its firm grasp of the "real pain points" and "quantifiable value", and it has deeply penetrated into the specific industry scenarios like digging a well. It doesn't dream of being a "universal assistant" but focuses on becoming an "expert" in the vertical field, solving visible, tangible, and calculable return problems in the customer's real business process.
Therefore, I think when starting an agent - related business now, don't just focus on how dazzling the technology is. The key is to see if it solves real problems and creates real value in real scenarios. Those "universal fantasies" floating in the air will eventually take root in the vertical deep wells.
The ones that survive are not the smartest but those who understand customers best, are the most practical, and can calculate the accounts most clearly.
Those who can enjoy the fruits of the agent business are always those who engrave the word "value" in their bones.
Technical feasibility ≠ Market demand
According to my communication with some people who have also developed agents, they generally fall into a big pit: "self - indulgence in technology and getting lost in demand".
The starting point for them is "what I can do" rather than "what is the most painful and urgent problem that users need to spend money to solve at the moment?" They are deeply fascinated by the advancement and possibilities of the technology itself, which becomes a form of self - admiration. They may take a problem that can be easily and efficiently solved with simple rules, clear buttons, or existing tools (such as ordering takeout or querying data) and force it into the "agent" fancy package.
As a result, users find that this so - called "intelligent assistant" may be more troublesome and complex to operate, and the answers to the questions may be ambiguous. It is far less convenient and fast than directly opening a mature app and clicking a few times. Users don't feel the convenience and value improvement brought by real "intelligence", so they are naturally reluctant to pay.
As far as I know, most entrepreneurs, especially small and micro - entrepreneurs who have only a superficial understanding of AI technology, are often attracted by the grand and distant story of "everyone will have an agent in the future". They bet on solving "imaginary and potential future needs" while ignoring the real and urgent pain points of users today.
In order to educate the market and cultivate this "future demand", they may go all out and burn a huge amount of money. However, the cruel reality is that the company's cash flow often cannot support it until the "dawn" arrives, and they collapse in the darkness before dawn.
"False prosperity and ineffective verification" is another huge pitfall, and it is also a trap that such entrepreneurs generally step into accurately. That Demo/POC that makes them and investors excited is, to put it bluntly, just a performance of technical ability. It proves that "we can make it", but it completely fails to answer the most crucial questions: "Do users really need it?" "Are users willing to pay for it continuously?" All this information is completely unknown.
What's even more terrifying is the "shallow feedback" from early users, such as evaluations like "cool" and "interesting". It's easy for entrepreneurs to be deceived by this superficial interest and polite praise, mistaking it for real market demand and a purchasing signal from users.
When entrepreneurs rely on the "free" model to attract users, the data reports will present an alluring "false prosperity".
Indicators such as the number of registered users and the daily active users (DAU) may look very good, and the charts are all in the green. The team is overjoyed. However, once you try to charge or lock the core functions and require payment to unlock, the cruel truth is exposed: the vast majority of users will immediately turn around and disappear without a trace.
These beautiful free data actually cover up the essence of "pseudo - demand" - users are just here to take advantage, not really recognize the core value of your product.
At the same time, entrepreneurs often ignore tracking the most core "key behaviors". It doesn't count if users register and open the app. What really matters is whether users really use your agent to complete their core tasks (for example, whether they can really write a usable first draft with the agent for report - writing instead of needing major revisions)? Whether users have significantly saved time or money costs because of this agent? Whether users like it enough to recommend it to friends or colleagues voluntarily? Whether users are willing to pay for more advanced and powerful functions?
If these "key actions" that reflect the real value of the product do not occur or the data is dismal, then no matter how high the activity level is, it is just false prosperity, like a castle on the beach that cannot withstand the market's storms.
Seriously underestimating the last mile
I've seen too many entrepreneurs with dreams of disruptive technologies smash against the rocks of reality. In the current booming wave of agent - related entrepreneurship, besides pseudo - demand, another pair of deadly "invisible killers" also repeatedly appear in this field.
Someone in an agent communication group complained that after going through great hardships, he finally verified a seemingly real demand, and his agent prototype also worked. The technical demo won high praise, but in the end, very few people were actually willing to pay.
All he could think about was his sophisticated agent model and algorithm. However, the enterprise customer's back - end is often an intricate IT "jungle" built over years or even decades: the old ERP system is like a rusty pipeline, the complex CRM database is like a maze, the knowledge bases privately held by various departments are like scattered islands, and there are also various self - developed, customized, and half - dead internal systems...
Previously, he thought: "Isn't it just connecting a few APIs? Just connect them." But in fact, to really integrate his "futuristic" agent into the enterprise's existing workflow and smoothly obtain the required data and trigger the correct actions is no less than a huge "heart - bypass surgery".
Incompatible data formats? Outdated system interfaces without documentation? Long permission - application processes? Stringent security and compliance reviews? Departments shifting blame?
These unexpected "pits" keep emerging one after another. The implementation cycle has been extended from the expected three months to one year, and the cost is rolling up like a snowball. Only then did he realize that he had seriously underestimated the complexity of the enterprise IT environment and the huge resistance to internal change implementation.
The IT manager in charge of the connection on the customer side may have changed from initial enthusiastic support to frowning and full of complaints. Many projects have exhausted the funds and the customer's patience at this "connecting the meridians" stage and died silently in the womb.
Even if his agent finally manages to integrate into the system after great efforts and starts to "spit out" results - such as a market analysis report, a list of potential customers, or a fault - diagnosis suggestion - it often encounters an even more distressing "last mile" dilemma.
The dilemma lies in that the output of the agent can rarely directly become the "final product" that the customer can use.
The report may have a good logical framework, but the key data needs to be manually checked and corrected; the customer list needs experienced salespeople to judge which ones are "real gold" based on their experience; the fault suggestion still needs the approval of experienced engineers before final implementation.
The efficiency, cost, and reliability of this crucial "last leg" - manual review, modification, and decision - making - truly determine the net value that the agent brings to the customer!
If customers find that after using the agent, although the first draft of the report is generated faster, the time spent on subsequent manual correction is more than the time they originally spent writing it from scratch; or the quality of the customer leads recommended by the agent is uneven, and the sales team still has to spend a lot of time screening, then this agent is not a helper but a burden.
Many people are full of enthusiasm to develop an "intelligent brain" but stumble at this seemingly simple yet fatal "last mile" of how to smoothly integrate its "thinking results" into and optimize the customer's existing "limbs".
What troubles entrepreneurs is that when they try to prove the value of the agent to smart enterprise buyers, they often fall into the embarrassing situation of "value ambiguity".
Vague adjectives and grand visions are powerless in the face of real - money enterprise procurement decisions. If entrepreneurs cannot use quantifiable and verifiable specific indicators to anchor the real business value created by the agent, no matter how cool the technology is, it is difficult to impress those enterprise buyers who are used to all kinds of "tech gimmicks". If the value cannot be clearly measured, it cannot be effectively priced and sold.
And the last straw that breaks the camel's back often comes from the lingering "universal fantasy" in entrepreneurs' minds. Especially those founders with a technical background are most easily attracted by the grand blueprint of creating an "all - powerful" universal intelligent assistant.
They dream of creating a "super brain" that can understand and handle all tasks, covering all industries and scenarios.
As a result, more and more functions are added to the product in an attempt to meet all the needs of all people, but it ends up being a "jack - of - all - trades" that knows a little about everything but is not proficient in anything.
However, the agents that can truly take root in enterprises, create significant value, and make customers willing to pay continuously are almost without exception those "experts" deeply rooted in extremely vertical, specific, and even narrow business - scenario "deep wells".
For example, a compliance - review agent specifically developed for a particular industry (such as cross - border medical device trade) that is well - versed in the complex regulations and customs - clearance processes of that field; an automatic - processing agent that only handles a certain type of high - frequency and standardized work orders (such as rescheduling installation appointments for a certain brand of home appliances); a report - generation agent that is only good at generating specific types of reports (such as anti - money - laundering reports that meet the fixed template requirements of a certain financial regulatory agency).
The value of these "experts" in the "vertical deep wells" is clearly visible, and the effects are immediate. Why? Because they solve the urgent pain points of a specific group of people in a specific link. To become such an "expert", entrepreneurs must have or be deeply integrated into the industry know - how of that vertical field - understand the unique business processes, obscure professional terms, unwritten rules, and the most core pain points.
An agent that doesn't understand legal terms and case - law logic will make a fool of itself when reviewing contracts; an agent that is not familiar with the operating data and maintenance history of factory - workshop equipment may give absurd suggestions when doing fault diagnosis. Without such in - depth industry knowledge, the created agent can only scratch the surface, cannot truly understand the business context, let alone seamlessly integrate into the core workflow and create irreplaceable value for customers.
How to become one of the surviving 20%?
Looking at it rationally, "agent - related entrepreneurship" is still a minefield this year, and most people have stepped on mines and fallen.
What you need to do is not to run blindly with your eyes closed and pray for good luck, but to hold a mine detector and scan inch by inch to find an extremely narrow but real and existing safe passage.
I call the cornerstone of this passage "extreme focus".
In fact, in any industry, the first iron law for entrepreneurial survival is to firmly hold on to "real pain points" and "quantifiable value".
Where can you find them? Look for those "loyal users" who are currently tortured by a specific problem and are willing to pay in advance for a solution or sign a letter of intent in black and white! Their pain points are so real because they are extremely severe. The real money they pay or the names they sign are the most solid trust votes from the market, which are more valuable than ten thousand "cool" comments.
I suggest that before you think about developing an agent, dissect your idea thoroughly: If you peel off the fancy label of "agent", does the core demand of users still exist? Is it still strong enough to make them restless? Compared with the users' current makeshift methods, clumsy tools, or competitors' products, does your solution bring a ten - fold improvement in efficiency, cost reduction, or experience leap? Can this improvement be clearly presented with numbers (such as saving 8 hours per week, reducing the error rate from 5% to 0.5%, and increasing the conversion rate by 20%) like nailing a nail in front of the customer?
From the first day of entrepreneurship, you must define and stick to several "key value indicators" like guarding your lifeline - whether users really use your agent to complete the core tasks (task completion rate)? Whether the completion speed has significantly increased (average processing time decreased by %)? Whether the number of manual follow - up operations has been greatly reduced (manual intervention rate)? How much money has been saved or earned for the customer in the end (customer cost savings/newly - added revenue)?
These solid data improvements are your only ticket to survival.
After having a focused direction, the next step is to completely innovate your method of verifying value. You must forget those fancy demos that can only impress yourself and investors. They are like beautiful cakes in the window, visible but inedible, and cannot verify whether anyone is really willing to pay for them.
The way to survive is to build a "value closed - loop". The most effective and ruthless move is to launch a "paid MVP" as early as possible. Don't be afraid of it being crude! It only needs to have one function as sharp as a cone, which can deeply penetrate the most core pain point you have targeted. Even if it is a beta version at a 50% or 30% discount, you should charge! This is the ultimate touchstone to tear off the mask of "pseudo - demand" and test users' real willingness to pay.
If no one is willing to pay for a semi - finished product, it probably means that the pain point is not painful enough, or the value of your solution is not strong enough. In terms of implementation, you should be as precise as a skilled surgeon. Don't dream of achieving everything at once and using the agent to replace the customer's entire complex process.
Instead, you should be like implanting a tiny intelligent chip and find a highly repetitive, annoying, and relatively independent link in the customer's existing workflow (such as manually processing hundreds of messy - formatted consultation emails every day or manually extracting key data from dozens of PDFs).
Use the agent to make a breakthrough in this "point" and make it a "super small tool" that the customer cannot do without, thus proving your real value.
You can't just be complacent about the "output" of the agent. A report generated