{"id":9319,"date":"2026-05-19T07:24:12","date_gmt":"2026-05-19T05:24:12","guid":{"rendered":"https:\/\/bicon.li\/?p=9319"},"modified":"2026-06-18T18:14:36","modified_gmt":"2026-06-18T16:14:36","slug":"wthe-new-bottleneck-in-ai-assisted-product-creationhen-building-becomes-too-easy","status":"publish","type":"post","link":"https:\/\/bicon.li\/en\/2026\/05\/19\/wthe-new-bottleneck-in-ai-assisted-product-creationhen-building-becomes-too-easy\/","title":{"rendered":"When Building Becomes Too Easy"},"content":{"rendered":"

The new bottleneck in AI-assisted product creation<\/h3>\n\n\n\n

For a long time, digital innovation followed a fairly stable logic.<\/p>\n\n\n\n

Ideas were translated into requirements. Requirements became concepts. Concepts became backlogs. Backlogs became software. And somewhere along the way, time, budget, technical complexity and organisational friction determined what was actually built.<\/p>\n\n\n\n

This logic is now starting to change.<\/p>\n\n\n\n

During a recent AI-assisted coding experiment, I translated several structured investment and advisory concepts into working digital tools within a very compressed timeframe. The most striking observation was not simply speed. Speed is visible, impressive and easy to communicate. But the deeper shift lies elsewhere.<\/p>\n\n\n\n

The bottleneck no longer seemed to be software creation itself.<\/p>\n\n\n\n

It increasingly moved to three other areas:<\/p>\n\n\n\n

    \n
  1. Superior ideas<\/li>\n\n\n\n
  2. Structured domain expertise<\/li>\n\n\n\n
  3. Distribution<\/li>\n<\/ol>\n\n\n\n

    In other words, execution is becoming cheaper. Iteration is becoming faster. Prototypes can become usable products almost immediately.<\/p>\n\n\n\n

    That changes the strategic question.<\/p>\n\n\n\n

    \n

    Not:
    Can we build it?<\/p>\n\n\n\n

    But increasingly:
    Should we build it?<\/p>\n<\/blockquote>\n\n\n\n

    From minimum viable product to maximum valid product<\/h3>\n\n\n\n

    The traditional MVP logic was born in an environment where building software was expensive, slow and uncertain. The \u201cminimum viable product\u201d was a rational response to scarcity. Build only what is necessary, test the market, learn quickly, avoid overengineering.<\/p>\n\n\n\n

    This logic still has value.<\/p>\n\n\n\n

    But AI-assisted coding introduces a new tension. If relatively sophisticated systems can be created, tested, refined and documented in days or weeks, the boundary between prototype and product becomes less clear.<\/p>\n\n\n\n

    What once required a classical development cycle may now emerge from a structured prompt, domain logic, iteration and automated testing.<\/p>\n\n\n\n

    This may not eliminate the MVP. But it may change its meaning.<\/p>\n\n\n\n

    The relevant question is no longer only how little can be built to validate an idea. It is also how much can be meaningfully built when execution costs fall dramatically.<\/p>\n\n\n\n

    \n

    This points toward a different concept:<\/p>\n\n\n\n

    Maximum Valid Product<\/a><\/p>\n<\/blockquote>\n\n\n\n

    Not maximum because everything should be built.<\/p>\n\n\n\n

    But maximum because more of the actual product logic, user experience, analytics, controls and documentation can now be tested much earlier than before.<\/p>\n\n\n\n

    The strategic risk of building too much<\/h3>\n\n\n\n

    The paradox is obvious.<\/p>\n\n\n\n

    When building becomes easier, the risk of building the wrong things increases.<\/p>\n\n\n\n