ExpertsFMThe 9 Stages of AI Agent Adoption, Explained
The Startup Ideas Podcast · October 21, 2026
5 Selected Lessons:
framework · 3 reasoning_pattern · 1 priority · 1
Five startup opportunity categories in the agent war
Source
The Startup Ideas Podcast — The 9 Stages of AI Agent Adoption, Explained (October 21, 2026) · at 24:39 ▸
When this applies
when a major platform shift creates confusion among incumbents and you're choosing where to build a business
The takeaway
Rank opportunity-building around a disruption by targeting the specific gaps it creates: niche readiness consulting/software, vertical trust/identity infrastructure, risk-transfer products, new measurement/analytics layers, and deep specialization — while avoiding reliance on tricks that exploit the disruption temporarily.
Why it works
Platform shifts create temporary information and trust gaps that incumbents can't resolve themselves quickly, and new entrants can monetize by resolving them before the gap closes.
One level up
The most durable businesses around any gold rush are the ones solving the structural gap (trust, measurement, risk), not the ones gaming the current rules.
Where it stops holding
This stops working when the disruption resolves faster than expected (e.g., a dominant player quickly standardizes everything), closing the window before niche players can establish themselves.
Detail
hierarchy:
- 1. Agent readiness consulting/software for one niche industry (e.g., dental supply) — find and fix agent errors by hand first.
- 2. Vertical-specific 'Plaid for agents' — trusted identity/payment connector for one industry (contractors, restaurant supply, vet scheduling).
- 3. Insurance for agent mistakes — guarantee who pays when an agent orders wrong, unlocking nervous businesses.
- 4. Analytics for agent traffic — 'Google Analytics for agents' to distinguish agent visits from human ones.
- 5. Be the hyper-specialist supplier — agents reward excellence at one specific thing.
- Avoid: businesses whose edge is a trick to get mentioned by AI, since tricks stop working.
rationale: Every platform shift creates confusion, and confusion is the most profitable product there is — citing the 1998 wave of people getting wealthy building websites for local businesses as the analogous precedent.
In their words
Every platform shift creates confusion, and confusion is the most profitable product there is.
Agent = customer with a credit card and no eyes
Source
The Startup Ideas Podcast — The 9 Stages of AI Agent Adoption, Explained (October 21, 2026) · at 5:00 ▸
When this applies
when a new non-human actor (bot, API consumer, automated agent) starts transacting with a system built for humans
The takeaway
When a new class of customer can't perceive your persuasion layer, your product's underlying facts — not its presentation — become the whole pitch.
Why it works
Agents parse structured, textual information (price, specs, policies) and ignore visual/persuasive design elements, so value built for human perception is invisible to them.
One level up
Design for the actual information channel your counterpart uses, not the one you're used to broadcasting through.
Where it stops holding
This stops working when the agent itself gains richer perceptual capabilities (vision, UI understanding) that let it register visual/branded elements the way humans do.
Detail
procedure:
- Recognize the agent has a goal, rules, and a spending limit set by its human.
- Understand it reads only text-level info: price, specs, shipping cost, return policy.
- Assume all visual/marketing assets (videos, banners, countdown timers) are invisible to it.
- Design pages so the facts that matter are in plain readable text, not buried in images or late-stage checkout screens.
benchmarks: {}
rationale: If everything you built for human eyes is invisible to the agent, the only way to win the agent's business is through legible facts, not design.
In their words
So how I think about it is an agent is a customer with a credit card and no eyes.
Ladder of trust for agent permissions
Source
The Startup Ideas Podcast — The 9 Stages of AI Agent Adoption, Explained (October 21, 2026) · at 5:00 ▸ · at 21:56 ▸
When this applies
when granting an automated or delegated actor increasing levels of authority over a process
The takeaway
Segment any delegated authority into graduated rungs (research, prepare, commit) and gate controls only at the rung where real risk lives.
Why it works
Risk concentrates at the point money or binding commitment changes hands, not at the research or preparation stages, so blanket blocking punishes low-risk behavior to guard against high-risk behavior.
One level up
Match the granularity of your defenses to the granularity of the actual risk, not to the category label of the actor.
Where it stops holding
This stops working when even the 'research' or 'prepare' rungs cause real cost (e.g., scraping overload, fraudulent holds), making graduated trust insufficient.
Detail
procedure:
- Rung 1: Research — find options, compare, report back (treat like search, allow freely).
- Rung 2: Prepare — add to cart, hold a seat, get a quote (generally low risk, can allow).
- Rung 3: Pay — actually spend money (highest risk, add verification/limits here).
- Decide what agents can do on each rung rather than binary block/allow.
benchmarks: {}
rationale: Almost every company is fine with rung 1; the entire war is happening on rung 3, so blocking all three is a mistake when the real risk only lives in one.
In their words
I think a lot of businesses are making a mistake by blocking all three when the real risk only potentially lives within one.
Nine-stage prediction for AI agent adoption war
Source
The Startup Ideas Podcast — The 9 Stages of AI Agent Adoption, Explained (October 21, 2026) · at 17:06 ▸
When this applies
when a new intermediary technology threatens incumbents' control over a customer relationship and you want to map how the conflict will likely evolve
The takeaway
Expect conflicts between incumbents and disintermediating technology to progress through blocking, arms-race workarounds, market segmentation by business model, emergence of a trusted identity/payment layer, competitive capitulation, normalization, and finally new monetization (ads) re-emerging in the new channel.
Why it works
Each stage is driven by misaligned incentives (ad/data revenue loss) resolving progressively as trust infrastructure, competitive pressure, and new monetization emerge — mirroring prior platform shifts.
One level up
Disruptive channels are rarely permanently blocked; they get re-monetized once trust infrastructure matures, following patterns seen in prior tech/advertising shifts.
Where it stops holding
This stops working when agents never reach sufficient reliability/trust for payments, stalling the progression before a trusted middle layer can emerge, or if regulation freezes the market at an early stage.
Detail
procedure:
- Stage 1: Companies block agents because agents skip ads/upsells (today).
- Stage 2: Agents learn to act more human to get through; arms race of blocks vs workarounds.
- Stage 3: Market splits — sales-driven companies open up, data-driven companies charge, giants build their own agent platforms.
- Stage 4: A trusted middle layer for agent identity/payments emerges (the 'Plaid moment'); Visa, Mastercard, Cloudflare race for it.
- Stage 5: Companies that welcome agents start winning customers from those that block.
- Stage 7: Universal competition for agents — better prices, faster checkout, agent-targeted SEO/product pages.
- Stage 8: Ads return inside agent recommendations as companies pay to be recommended first.
- Stage 9: Selling to agents becomes normal, like having a website; businesses that can't be bought by an agent look obsolete.
benchmarks: {}
rationale: I've seen this fight before (Mint/Plaid); companies will not stay blocked forever once a trust layer and competitive pressure make opening the door profitable.
In their words
In a few years, a business that can't be bought by an agent is going to look like a business without a website looked in, I don't know, 2005.
Infer company strategy from market position relative to incumbent
Source
The Startup Ideas Podcast — The 9 Stages of AI Agent Adoption, Explained (October 21, 2026) · at 2:09 ▸ · at 12:57 ▸
When this applies
when multiple competitors face the same disruptive channel and you want to predict who opens the door vs. who closes it
The takeaway
Map each player's position (dominant owner of the destination, challenger seeking share, or neutral infrastructure/toll layer) to predict whether they'll block, open, or arbitrage a disruptive channel.
Why it works
A company's revenue model (store-owner vs. audience-owner vs. toll-collector) and its market rank (incumbent vs. challenger) determine whether a new channel threatens or helps it, so behavior is predictable from structure.
One level up
Structural incentives, not stated values, determine strategic posture toward disruption.
Where it stops holding
This stops working when a company's position is genuinely mixed (e.g., a strong data business with weak sales motive), making the simple block/open mapping less predictive.
Detail
approach: For each major player, identify whether its core revenue depends on being the destination (blocks), on owning the audience/agent (opens), on being the challenger (opens to steal share), or on being payment/security infrastructure (wants to be the toll booth regardless of outcome).
signals:
- Walled-garden destination with its own storefront and ads → blocks and builds in-house agent (Amazon)
- Owns billions of users across apps, wants open standards it can plug into → welcomes and pushes interoperability (Meta)
- Is the #2 player → opens door to take share from #1 (Walmart)
- Infrastructure/payment layer → stays neutral, builds trust/verification tooling regardless of winner (Visa, Mastercard, Cloudflare, Shopify)
rationale: The companies with the biggest stores are blocking, the companies with the biggest audiences are opening the door, and the payment/security companies want to be the toll booth no matter who wins.
In their words
The companies with the biggest stores are blocking. The companies with the biggest audiences are just opening the door. And the payment and security companies want to be the toll booth no matter who wins.