Isabella Bedoya

In her consulting example, payment triggers an agreement; signing unlocks an AI voice agent that does intake; the system collects documents, books a meeting, sends reminders, updates the CRM, and produces a debrief before the call.

• In sales, she says an AI handled calls, web chat, texts, and email while remembering the conversation across channels, and that it flagged uncertain messages for her to edit or approve.
• Her reasoning is that AI can gather richer context than a static form, cost less per conversation, and let both sides arrive prepared.

She reports multiple 30–45 minute AI intake conversations for less than $9 each, and a sales system that handled 44 calls, 64 web chat messages, 38 texts, and 11 emails, generating 19 buyers and $4,829 against $202 in AI and subscription costs.

Read original · Original 2

She presents costs next to revenue and treats ROI as the point. She also frames content automation around a customer journey rather than posting for its own sake, saying AI influencers should become 'revenue generating machines' and that the system runs from 'content created → customer sold.'

In the sales post she adds $103 in AI credits to a $99 monthly subscription, reports $4,829 generated and a 2,291% ROI, and writes that 'ROI on AI spend is everything.'

Read original · Original 2

She says LinkedIn algorithm updates caused a decline in her reach, which pushed her to diversify. Rather than being the person making all the content, she says she built AI systems to produce and distribute it, and she describes installing the same content system into a professional services business that previously needed five people and multiple tools.

She writes that LinkedIn's harder reach made her 'unlock other channels' and that she installed the content system so a client's completed project becomes AI-repurposed content the team can approve and post.

Read original

She reports follower counts, views, posting volume, and per-video AI costs, then tests monetization. The posts show a shift from pure growth updates toward brand and UGC monetization and automating the posting schedule.

She tracks the account from 3 followers to 2,566 in 24 hours, then to 7,315 in a week with 28 reels and 2.2 million impressions. She notes $15–20 per video in AI costs, adds a friend's t-shirt business link to test traffic, and later signs the account up for brand and UGC payments.

Early posts report rapid follower and view growth; later updates say the account was signed up to be paid by brands and UGC, and that she plans to automate publishing so growth continues when she is busy.

Read original · Original 2 · Original 3 · Original 4

She says 'never quit' and links her own path from hourly work to a seven-figure AI business as evidence that documenting the journey matters.

In her six-levels post, each level moves from more work to more payment, ending with 'never quit.' In another post she recalls making smoothies for $15/hr and then speaking about her seven-figure AI business at a conference with seven-, eight-, and nine-figure entrepreneurs.

Read original · Original 2

She describes using Claude to negotiate a car lease and compare insurance, saying she did not need to become an expert because AI needed to know enough about her to help her decide better. She labels the result a personal account, not financial advice.

She lists a 2026 BMW X3 deal with $0 down, waived registration, dealership and lease-return fees, a $5,000 discount, a lower monthly payment, and a Progressive insurance policy at $113/month versus a GEICO quote of $296/month.

Read original

She says she shared a $50,000 starting rate and ended the call; the other person then sent a screenshot of a $247,000 bank balance.

• She says she has seen similar behavior from older men in business and asks whether it is because she is a woman.
• This is a standalone tension in the supplied posts, not a recurring theme, and it shows her arguing for high pricing and against accepting dismissive treatment.

The post recounts the call, the $50,000 rate, the $247,000 screenshot, and her question about whether gender was the reason for the treatment.

Read original

Start here for a concrete process, its claimed benefit, and an example that goes beyond a generic automation pitch.

Bedoya lays out the client journey in sequence: payment triggers an agreement; signing unlocks an AI voice intake; the system gathers documents, books a meeting, sends reminders, updates the CRM, and prepares a debrief. She says AI intake can gather richer context than a static form and reports multiple 30–45 minute conversations costing less than $9 each.

For brands planning a campaign

A useful starting point for a campaign about AI intake, scheduling, or CRM workflows. A partner could demonstrate the handoffs and ask viewers to assess which steps suit their own service business.

This post answers both with a specific funnel and reported numbers.

Bedoya reports that her AI handled calls, web chat, texts, and email while retaining conversation context across channels.

• She gives activity counts, offer prices, buyer counts, and AI costs, and says uncertain messages were flagged for her to edit or approve.
• The figures are her account of the result, not independently verified performance data.

For brands planning a campaign

Relevant to sales-tech brands seeking a case-led demonstration of multichannel follow-up and human approval. A campaign should make the reported figures and the role of review explicit rather than present them as a guaranteed outcome.

This post introduces the experiment and the business use she says she is testing.

Bedoya reports that an AI-generated influencer account reached 7,315 followers in a week after 28 reels, with 2.2 million impressions.

• She connects the project to IzzyOS to automate content, comments, direct messages, and funnels, and describes applying a related content system to a professional-services business.
• The post frames the results as an experiment and says she will report back.

For brands planning a campaign

A strong fit for a campaign exploring AI-assisted content operations or creator-led social experiments. Ask for the workflow and subsequent results; the post alone does not establish sustained growth or sales from the account.

This post shows the move toward brand and UGC monetization, while making clear that the result is not yet reported here.

In an earlier update on the project, Bedoya reports 19 reels, 1.8 million views, and 6,116 new followers in four days.

• She says she signed the account up to begin getting paid by brands and user-generated-content work, while planning to automate publishing around her own schedule.
• The post describes a monetization plan, not confirmed brand revenue.

For brands planning a campaign

Useful for a campaign about testing AI-generated creator accounts, with a clear distinction between audience growth and monetization. A partner could explore what safeguards, disclosure, and performance measures belong in such a test.

This personal example broadens her use case and shows how she turns a detailed experience into a readable story.

Bedoya describes using Claude to negotiate a car lease and compare insurance, listing the discounts and monthly costs she says she obtained.

• She presents AI as help with everyday decisions, not only workplace tasks, and notes that the car photo uses an AI-generated background.
• Her post is a personal account, not proof that the same savings are repeatable.

For brands planning a campaign

A possible example for consumer AI products or campaigns about decision support. Keep the story framed as one person’s experience and avoid implying financial advice or guaranteed savings.

In one post, an AI spoke with 30 people across calls, web chat, text, and email; it handled 44 calls, 64 web chat messages, 38 texts, and 11 emails, and produced 19 buyers and $4,829 against $202 in AI and subscription costs.

• She notes the AI remembered the conversation across channels and asked for approval when unsure.
• Another post documents a step-by-step consulting intake flow where payment, agreement, AI voice intake, scheduling, CRM updates, and call debrief all run before the meeting.

Connect payment, agreement, AI voice agent, calendar, and CRM so AI collects context and routes exceptions to a human.

For brands planning a campaign

A sales-tech, AI voice, or CRM vendor can use Bedoya as a creator who demonstrates concrete ROI, multi-channel memory, and human-in-the-loop guardrails rather than abstract AI claims.

Examples: Source 1 · Source 2

Posts track an AI influencer from 3 followers to 2,566 in 24 hours, then 7,315 in a week, with 2.2M impressions and 28 reels; per-video AI costs are $15-20.

• She connects the account to IzzyOS to automate content, comments, DMs, and funnels, and later signs the account up to be paid by brands and UGC.
• She also says she installed the same content system into a professional services business.

Post AI-generated reels at volume, monitor views and follower demographics, add a monetization link, then automate posting, DMs, and funnels.

She documents an early monetization test with a friend's t-shirt business, so revenue from the AI influencer is not shown as a settled offer.

For brands planning a campaign

AI content, social automation, or creator-commerce brands can evaluate her for builds that combine rapid audience testing with automated content-to-customer workflows.

Examples: Source 1 · Source 2 · Source 3 · Source 4

She lists $0 down, waived fees, a $5,000 discount, a lower monthly payment, and a Progressive policy at $113/month versus a GEICO quote of $296/month. She frames this as AI helping her make better decisions without becoming an expert.

For brands planning a campaign

An AI assistant or LLM brand can use Bedoya as a creator who shows practical, personal decision support, though this is a lighter B2B fit than her sales automation work.

Examples: Source 1

A separate list post reduces entrepreneurship to six levels of work and payment, ending with "never quit." The posts position her as a founder who documents the journey and speaks from experience.

For brands planning a campaign

A founder-focused, conference, or business education brand can use her for motivational and credibility-led content aimed at entrepreneurs and operators, rather than product-led AI demos.

Examples: Source 1 · Source 2

Bedoya says she shared a $50,000 starting rate and ended the call; the other person then sent a screenshot of a $247,000 bank balance.

• She says she has experienced similar behavior from older men in business and asks whether it is because she is a woman.
• This is a standalone exception in the supplied corpus rather than a recurring content theme.

This is the only supplied post centered on gender dynamics or a negative sales call, so it should not be generalized into a broader content pattern.

For brands planning a campaign

For brands considering partnerships around women in business, sales, or AI, this post shows a candid audience-facing stance on gender and pricing; it should be treated as a sensitive, personal topic, not a general campaign hook without her direction.

Examples: Source 1

She reports an AI-run sales process that generated $4,829 in sales against a $99/month IzzyOS subscription. The posts show the platform as the system she uses and recommends, and describe installing the same setup for other businesses, but they never state her role in IzzyOS: ownership, employment, and compensation are all unstated, so the commercial relationship cannot be pinned down from this material.

View example

She frames this as evidence that AI now shapes her personal as well as professional decisions. The post is an account of using the product, not a disclosed commercial tie to Anthropic.

View example

Brady Kirkpatrick walks through a client-onboarding automation that updates a CRM, creates folders, spins up a project board, sends a welcome email, notifies the team, and schedules a kickoff. Isabella Bedoya documents similar end-to-end systems for consulting intake and sales conversations.

Kirkpatrick's retained posts center on client onboarding and wealth-management meeting prep. Bedoya ranges wider, with AI-run sales conversations, an AI influencer growth experiment, and entrepreneurship posts.

Read original · Original 2

Othmane Khadri describes wiring an agent to review lost deals, cluster objections, score open deals, and draft follow-ups, plus a playful agent for AI comments. Bedoya documents AI voice intake and multi-channel sales follow-up.

Khadri's retained posts focus on GTM and revenue operations and the Yalc.ai agent harness. Bedoya covers a broader set of business and content systems, including AI influencer monetization.

Read original · Original 2

Max Thilén lists practices for an AI-native marketing team, from self-improving loops to agent safety and orchestration. Bedoya gives similar step-by-step systems for sales intake, content production, and customer journeys.

Thilén emphasizes marketing-team architecture, orchestration, and model economics. Bedoya emphasizes sales conversations, client intake, and AI-driven social growth.

Read original · Original 2

The supplied posts document a repeatable onboarding build: a contract or payment triggers a CRM update, folder creation, project board setup, welcome email, team notification, and kickoff scheduling.

• A second post describes meeting prep, document organization, post-meeting follow-ups, milestone triggers, and personalized client updates for advisory practices.
• That makes Brady a stronger choice if the vendor wants to reach financial advisors, professional-services firms, or operations leads with a domain-specific automation story.

The tradeoff is narrower domain evidence.

• Brady's supplied examples center on financial advisory and client onboarding, while Isabella Bedoya's fit evidence centers on AI handling multi-channel sales conversations, voice intake, and human approval of uncertain messages.
• Brady's posts also include a discovery-call offer and a downloadable workflow document, so the campaign may need to separate education from direct lead generation.
• No audience demographics, rates, or campaign results were supplied.

Examples: Source 1 · Source 2

The supplied posts describe a Claude Code and Yalc.ai agent that pulls closed-lost deals from Attio, reads lost reasons and recent activities, clusters objections, scores open deals on losing patterns, and drafts personalized reactivation messages.

• Another post documents an open-source agent built to detect AI comments and run DM conversations.
• That is a stronger match if the campaign needs CRM-integration credibility, lost-deal analysis, or a builder-led demonstration for revenue operations and sales leaders.

The tradeoff is that Khadri's evidence is less about a service-business owner receiving AI follow-up and more about building agents for GTM teams.

• The AI-comment prank may not suit a vendor that wants a cautious, brand-safe campaign about responsible automation.
• The supplied posts do not show the human-approval guardrail that anchors Bedoya's fit, and no audience demographics or commercial terms were supplied.

Examples: Source 1 · Source 2

The supplied posts lay out self-improving loops, a shared context layer, agent access to ad accounts and CRM, skill-based workflows, orchestration, model selection by task, agent safety rules, and quality measurement.

• Another post explains why OpenAI's $200 Pro plan signups paused and lists automated jobs for CRM maintenance, ad-creative tagging, call analysis, competitor monitoring, and landing-page personalization.
• That is a stronger fit if the vendor wants thought leadership for marketing leaders, agency operators, or AI transformation buyers.

The tradeoff is abstraction and audience.

• Thilén's examples are operating principles and portfolio-level uses, not a step-by-step service-business follow-up demo.
• The supplied posts do not show the same level of sales-conversation conversion detail or human approval step that Bedoya documents, and no audience demographics, rates, or campaign results were supplied.
• The campaign would need a concrete product tie-in to avoid becoming general AI commentary.

Examples: Source 1 · Source 2