{"id":9033,"date":"2026-05-06T08:07:35","date_gmt":"2026-05-06T06:07:35","guid":{"rendered":"https:\/\/bicon.li\/?p=9033"},"modified":"2026-05-15T08:32:13","modified_gmt":"2026-05-15T06:32:13","slug":"the-end-of-the-mvp-era-as-we-know-it","status":"publish","type":"post","link":"https:\/\/bicon.li\/en\/2026\/05\/06\/the-end-of-the-mvp-era-as-we-know-it\/","title":{"rendered":"The End of the MVP Era as We Know It"},"content":{"rendered":"

From Scarcity to Abundance<\/h3>\n\n\n\n

For more than two decades, the concept of the Minimum Viable Product<\/a> shaped how digital products were designed, prioritised, and implemented. The underlying logic was highly rational. In a world where software development was expensive, slow, and organisationally fragmented, reducing scope was essential. Products had to be stripped down to their absolute core functionality in order to validate ideas without consuming excessive time and resources.<\/p>\n\n\n\n

This principle became deeply embedded into startup culture, innovation frameworks, and increasingly also into large enterprises attempting to become more agile. Build small. Launch early. Learn fast. Iterate continuously.<\/p>\n\n\n\n

But this logic was built for a different technological reality.<\/p>\n\n\n\n

Today, AI-assisted coding, agentic workflows, and massively accelerated implementation cycles are beginning to alter the economics of software development fundamentally. What previously required specifications, alignment workshops, project structures, implementation teams, and long development cycles can increasingly emerge directly from structured domain logic combined with AI-supported execution.<\/p>\n\n\n\n

This shift is not incremental. It is structural.<\/p>\n\n\n\n

One of the most remarkable aspects is that the traditional distinction between prototype and operational system is beginning to dissolve. In many cases, what starts as an experiment already evolves within days into something highly functional, visually polished, operationally usable, and surprisingly comprehensive.<\/p>\n\n\n\n

\n

The historical danger of underbuilding is increasingly being replaced by the opposite problem: overbuilding.<\/p>\n<\/blockquote>\n\n\n\n

For the first time in software history, organisations may need to actively resist the temptation to add too much functionality too early.<\/p>\n\n\n\n

Historically, adding functionality carried friction. Every additional feature implied implementation effort, budget discussions, prioritisation conflicts, testing requirements, and deployment complexity. Functionality therefore had a natural economic filter.<\/p>\n\n\n\n

AI-assisted development dramatically weakens this filter.<\/p>\n\n\n\n

Additional workflows, dashboards, integrations, analytics layers, simulations, visualisations, or automation components can now often be implemented at extraordinary speed. What previously represented weeks or months of work may increasingly become a matter of hours.<\/p>\n\n\n\n

As a result, many modern systems no longer resemble Minimum Viable Products.<\/p>\n\n\n\n

They increasingly resemble Maximum Viable Products.<\/p>\n\n\n\n

Not because organisations intentionally seek complexity, but because the baseline speed of creation has shifted so dramatically that scope expansion becomes almost automatic.<\/p>\n\n\n\n

The Bottleneck Is No Longer Coding<\/h3>\n\n\n\n

This changes the bottleneck of software development itself.<\/p>\n\n\n\n

For decades, implementation capacity represented the central limiting factor. The key question was whether something could realistically be built within available time and resources.<\/p>\n\n\n\n

That question is becoming less dominant.<\/p>\n\n\n\n

The new bottleneck is increasingly elsewhere.<\/p>\n\n\n\n

It moves towards judgment, focus, prioritisation, and the quality of the underlying domain logic.<\/p>\n\n\n\n

Because when implementation friction collapses, almost everything becomes technically possible. The strategic challenge therefore shifts from creation towards selection.<\/p>\n\n\n\n