The cost to run an autonomous AI coding agent is surprisingly low, reframing the value of developer time. A single coding iteration can cost as little as $3, meaning a complete feature built over 10 iterations could be completed for around $30, making complex software development radically more accessible.

The high price point for professional AI tools is justified by their ability to tackle complex, high-value business tasks, not just minor productivity gains. The return on investment comes from replacing expensive and time-consuming work, like developing a data-driven growth strategy, in minutes.

The cost for a given level of AI capability has decreased by a factor of 100 in just one year. This radical deflation in the price of intelligence requires a complete rethinking of business models and future strategies, as intelligence becomes an abundant, cheap commodity.

A paradox exists where the cost for a fixed level of AI capability (e.g., GPT-4 level) has dropped 100-1000x. However, overall enterprise spend is increasing because applications now use frontier models with massive contexts and multi-step agentic workflows, creating huge multipliers on token usage that drive up total costs.

Frame your product's value not around the underlying AI, but around the premium insight it unlocks. The key is to instantly provide an answer—like a valuation or diagnosis—that previously required significant time, money, or human expertise.

Even for complex, multi-hour tasks requiring millions of tokens, current AI agents are at least an order of magnitude cheaper than paying a human with relevant expertise. This significant cost advantage suggests that economic viability will not be a near-term bottleneck for deploying AI on increasingly sophisticated tasks.

The true power of tools like Manus isn't in its generic, suggested prompts, but in a skilled marketer's ability to ask specific, domain-aware questions. An expert can dig into details like channel-specific bounce rates to find competitive arbitrage, a level of inquiry the AI won't suggest on its own.

Big tech companies are offering their most advanced AI models via a "tokens by the drink" pricing model. This is incredible for startups, as it provides access to the world's most magical technology on a usage basis, allowing them to get started and scale without massive upfront capital investment.

While the cost for GPT-4 level intelligence has dropped over 100x, total enterprise AI spend is rising. This is driven by multipliers: using larger frontier models for harder tasks, reasoning-heavy workflows that consume more tokens, and complex, multi-turn agentic systems.