Dylan Watkins creates and hosts content about n8n, AI, and workflow automation. Their posts highlight practical builds and interviews with people applying automation to areas including cybersecurity, voice agents, and enterprise AI adoption.
Dylan Watkins is most useful for practical n8n, AI, and workflow automation builds and interviews.
Best for
A B2B automation or AI tooling company using co-marketing or podcast sponsorship.
Not for
A consumer fintech app seeking mass-market US consumers via short-form video.
Key takeaways
The workflow around the model matters more than the model itself.
Teach fundamentals before adding AI.
Netwrix trained 100 non-technical employees to build 65 workflows.
Check first: Ask for episode results, disclosure terms, and publishing cadence before contacting.
Main ideas
The workflow around the model matters more than the model itself · Teach fundamentals before adding AI · Security automation should be usable outside enterprise security teams
Dylan Watkins creates and hosts content about n8n, AI, and workflow automation, including the n8n Podcast.
The posts show a practical focus: conversations and walkthroughs that connect automation tools to problems in security, lead generation, and enterprise adoption.
Follow Dylan for examples of how teams might build and introduce workflows—not just discussion of AI tools in the abstract.
Dylan’s strongest contribution in these examples is making automation concrete through guest-led builds and implementation stories.
In a security post, they highlight an incident-response workflow and a phishing-analysis walkthrough, drawing attention to the data, playbooks, and workflow structure around the AI model.
In an enterprise adoption interview, they foreground how training was sequenced and how employees could move workflows into production safely.
The podcast announcements cover a broader range, from voice agents and lead generation to choosing between agents and workflows.
The second episode announcement names the topic and guest but offers little detail about the discussion; ask for more episode information if that detail matters to your campaign.
Dylan Watkins's recurring ideas treat automation as an infrastructure and readiness problem first, and a model or tooling choice second.
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Across the posts, Watkins argues that clean data, written playbooks, trained people and a workflow that can swap models make AI useful.
The show returns to practical builds and guest-led examples in cybersecurity, enterprise training, agency lead generation, and the choice between agents and simpler workflows.
Guest views are attributed to the guests, not Watkins.
The workflow around the model matters more than the model itself
Watkins's recurring argument: teams get value from automation when they first fix the unglamorous parts—clean data, historical incident records, written playbooks and a workflow harness that can plug in whatever model comes next.
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Models keep improving, so a model advantage does not last. Watkins presents this as the main takeaway from a conversation with Viraj, described in the post as a former n8n team member turned forward-deployed engineer who builds AI-powered security systems for enterprises.
An open-source n8n incident-response workflow, with a live phishing analysis demo covering three branches of analysis, threat-intelligence lookups and remediation steps. Watkins says the session screenshares the full workflow and walks through the results end to end.
Watkins argues that automation training works when people learn the basics first.
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In the Netwrix episode, the guest deliberately kept Claude out of the first two days so participants could learn fundamentals before AI filled gaps.
Watkins also highlights a 'context, intelligence, action' pattern behind each workflow and the claim that front-line employees find automation opportunities better than a central team.
The guest is Jake Mahon, AI team lead at Netwrix.
Jake Mahon ran two five-day boot camps for two global cohorts of 100 non-technical employees, resulting in 65 workflows in production.
The post describes a GitOps setup that lets non-developers push to production, with AI code review on every pull request and credential management through Azure Key Vault.
The post reports $250,000 saved in the first month.
Security automation should be usable outside enterprise security teams
Watkins argues that n8n security workflows are not just for enterprise security teams.
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The post opens by saying home networks are being scanned right now, then pitches the builds to homeowners with smart devices and small teams protecting shared inboxes. The guest is Buddy R., described in the post as a cybersecurity professional and solutions engineer at n8n, who builds two workflows during the episode.
One workflow scans incoming Gmail for phishing links with VirusTotal and tags confirmed threats in the inbox.
The other monitors firewall-blocked connections and enriches each alert with VirusTotal, URLScan and MISP in under ten seconds.
The post also covers lateral movement and ransomware in small environments, geo-blocking, dark web exposure, prompt injection risks from AI agents, and a personal security checklist with password managers and app-based two-factor authentication.
The security framing spans corporate SecOps and personal or small-business defense, broadening the audience beyond enterprise buyers.
Agencies get a faster start with voice agents and one narrow niche
In the podcast launch episode, Watkins lays out an agency playbook: voice agents are the easiest first win for an AI agency; the repeatable pattern runs from FAQ to calendar booking to CRM updates; and the way to win clients is to pick one niche and go deep.
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The guest is Zubair Trabzada of AI Workshop, discussing voice agents and RAG for lead generation.
Episode one of the n8n Podcast. Watkins asks viewers for guest suggestions and says new episodes are weekly.
Choose agents or workflows by the job, not by fashion
A later episode frames the choice between AI agents and workflow automation as a cost decision: pick the right tool or pay the price.
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The guest is Nick Saraev. The post is brief and mostly an episode link; Watkins's framing treats AI agents as one option among several, not the default.
Episode two announcement, with hashtags covering n8n, AI agents, workflow automation, no-code, demand generation, revops and operations.
The agents-versus-workflows question recurs as the show develops, connecting to Watkins's broader argument that the surrounding workflow, not the model, determines whether automation pays off.
Start here for the argument running through most of Dylan's work: the workflow around the model is what makes automation pay off.
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It also shows what an n8n security workflow looks like in a live build.
Dylan's write-up of a conversation with Viraj, described in the post as a former n8n team member now working as a forward-deployed engineer building AI security systems for enterprises.
The post walks through a live n8n incident-response workflow and an end-to-end phishing analysis demo, naming three branches of analysis, threat-intelligence lookups and a results walkthrough.
Dylan's takeaway: the model matters less than the scaffolding around it — historical incident data, playbooks and a workflow harness that can plug in whatever model comes next.
The framing also draws on a claim from the conversation: Anthropic's 'Mythos' AI found a 27-year-old OpenBSD vulnerability and was pulled days later.
Ask for the source of that claim; the post does not document it.
For brands planning a campaign
Guest-led technical builds with an enterprise security angle. A downloadable open-source workflow gives a co-marketing partner a concrete artifact to pair with an offer, rather than relying on an episode link alone.
Shows how Dylan brings enterprise automation tooling to a non-enterprise audience, and offers the clearest example of the accessible, follow-along build format used across the posts.
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A walkthrough with Buddy R., an n8n solutions engineer, building two workflows: one scans incoming Gmail for phishing links with VirusTotal and tags confirmed threats in the inbox; the other monitors firewall-blocked connections and enriches each alert with VirusTotal, URLScan and MISP in under ten seconds.
Dylan notes that both are accessible — pitched at homeowners with smart devices and small teams protecting shared inboxes, not only enterprise security teams.
The post covers lateral movement and ransomware in small environments, geo-blocking, dark web exposure tied to the National Public Data breach, prompt-injection risks from AI agents and a personal security checklist covering password managers and app-based two-factor authentication.
It points to a free step-by-step guide and a self-hosted cyber lab, with the workflow build flagged around the 27-minute mark.
For brands planning a campaign
Gated guides and lab downloads are the sponsorship inventory here. Homelab and small-business security audiences are narrower than an enterprise base, but they are specific, and the free asset gives a campaign something measurable to distribute.
The set's most concrete adoption story, with named figures and an organisation behind it.
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Read this to judge how Dylan handles enterprise reporting rather than tool demos.
An interview with Jake Mahon, AI team lead at Netwrix, about running two five-day boot camps across two global cohorts.
Dylan reports 65 production workflows built by people who had never worked with a JSON object, and $250,000 saved in the first month.
They single out the sequencing decision — deliberately keeping Claude out of the first two days so fundamentals came first — and a GitOps system that lets 100 non-developers ship to production with AI code review on every pull request.
The post also covers a 'context, intelligence, action' pattern behind each workflow, credential management through Azure Key Vault across a large cohort, why front-line employees find automation opportunities better than a central team, and two common enterprise AI failure modes.
Dylan calls it the most practical enterprise adoption blueprint they have seen.
The savings and workflow counts are figures from the interviewee, as relayed in the post.
For brands planning a campaign
A strong fit for enterprise automation platforms and AI enablement vendors. An interview with an internal AI lead can support a co-branded adoption playbook or benchmark, while the boot-camp structure offers a hook for a webinar or workshop series.
Shows the format Dylan built and the agency-facing half of the subject range — useful when deciding whether the audience is agencies or in-house operations teams.
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The announcement of the n8n Podcast, with episode one featuring Zubair Trabzada of AI Workshop on voice agents and RAG driving lead generation.
Dylan highlights voice agents as the easiest first win for AI agencies, a scaling pattern from FAQ to calendar booking to CRM updates, and a 'pick one niche and go deep' playbook for agencies.
The post asks for guest suggestions and says new episodes are weekly.
For brands planning a campaign
Episode-level sponsorship and guest-slot placement on a weekly cadence, easier to plan around than intermittent posts. Voice-agent and agency-tooling vendors have an obvious topical match.
Confirms the agents-versus-workflows debate as a recurring theme for Dylan, while the hashtags sketch the operational audience the show targets.
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Open the episode if that decision is your actual question.
A short announcement for episode two of the podcast, framed around choosing between agents and workflow automation, with Nick Saraev as guest and the pitch 'pick the right tool or pay the price'. The post text is mostly an episode link and hashtags covering n8n, AI agents, workflow automation, no-code, demand generation, revops and operations.
For brands planning a campaign
Use this to assess how consistently the show covers agents, no-code, revops and operations, and whether a campaign theme recurs rather than appearing in a single post.
Cybersecurity automation for teams and small businesses2
Enterprise AI adoption by non-technical staff1
Voice agents as a first win for AI agencies1
Agents versus workflows as a buying decision1
Put the data and playbooks before the model
Watkins returns most often to the idea that AI is the second-order part of an automation project.
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In the incident response episode, the point is that models keep improving, but teams get value from clean data, written playbooks, and a workflow harness that can swap in whatever model comes next. The same idea appears in the enterprise training episode, where the lead deliberately kept Claude out of the first two days so participants learned fundamentals before AI filled gaps.
Watkins makes the argument through a guest who built the system, then restates the takeaway in the post.
For brands planning a campaign
A tooling vendor selling on model quality will not land with this audience through Watkins.
A stronger angle is infrastructure and readiness: how a team's data, incident history, or process documentation makes any model usable.
Co-marketing content should lead with the unglamorous prerequisites, not a benchmark.
Cybersecurity automation for teams and small businesses
Two episodes cover security work directly.
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The first is an open-source incident response workflow built in n8n, with a live phishing analysis demo covering threat intelligence, remediation steps, and how AI chains vulnerabilities in an attack.
The second covers a home and small-business setup: scanning incoming Gmail for phishing links with VirusTotal and tagging threats in the inbox, plus firewall monitoring that enriches blocked-threat alerts with VirusTotal, URLScan, and MISP in under ten seconds.
Both posts argue that the workflows are usable outside enterprise security teams.
Screen-shared workflow walkthroughs, with the guest building each branch live.
The security framing spans corporate SecOps and personal or small-business defense, broadening the audience beyond enterprise buyers.
For brands planning a campaign
This is the most concrete subject for a security or automation platform partnership.
The format already includes downloadable workflows and a free guide, so a sponsor can attach to a build rather than a discussion.
Lead with a working artifact viewers can install, not a category overview.
One episode offers a blueprint for rolling out automation inside a large company.
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Jake Mahon of Netwrix ran two five-day boot camps for two global cohorts of 100 non-technical employees and ended with 65 workflows in production. The post details a GitOps setup that lets non-developers push to production with AI code review on every pull request, credential management through Azure Key Vault, a 'context, intelligence, action' pattern used to structure every workflow, and the claim that front-line employees find automation opportunities better than a central team.
Interview structured around a repeatable rollout sequence, not a product demo.
The post attributes the savings figure and workflow count to the guest's program; the results are not independently verified.
For brands planning a campaign
For an automation or AI tooling company targeting operations leaders, this is the episode to license or re-cut for a mid-funnel audience. The numbers (100 employees, two cohorts, 65 workflows, $250,000 saved in the first month) give a campaign concrete proof points to cite, and the guest is a natural second voice in a co-hosted webinar.
The podcast launch episode covers voice agents and RAG with Zubair Trabzada of AI Workshop.
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The focus is agency economics: why voice agents are the easiest first win for an AI agency, the patterns that scale (FAQ to calendar booking to CRM updates), and a 'pick one niche and go deep' approach to lead generation.
For brands planning a campaign
A voice, CRM, or lead-gen vendor can reach agencies and freelance builders through this episode. The niche-depth argument also gives a sponsor a natural hook for a partner or reseller recruitment campaign, rather than a pure awareness push.
A later episode with Nick Saraev frames the choice between AI agents and workflow automation as a cost decision: pick the right tool or pay the price.
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The post is short and points to the episode, but the subject is a recurring decision point for operations and revenue teams evaluating automation tooling.
For brands planning a campaign
Positioning content that helps buyers decide when an agent is warranted and when a deterministic workflow is cheaper fits this audience. A vendor with a strong opinion on that trade-off can supply the argument, while Watkins hosts the comparison.
The posts launch and promote the n8n Podcast, feature n8n staff and alumni as guests, and share links to n8n-hosted workflow downloads.
They don’t say whether Watkins works for, owns, or contracts with n8n; ask Watkins to clarify the arrangement.
Other companies appear as subject matter rather than partners: Anthropic’s security research frames one episode, and enterprise software company Netwrix is the employer of an interview guest.
No post carries a sponsorship, affiliate, or paid-partnership disclosure.
n8n
Disclosed partnership
n8n is the throughline of Watkins’s posts.
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They launched and host the n8n Podcast, point readers to n8n-hosted downloads such as an open-source incident response workflow and a free home-security workflow bundle at go.n8n.io, and feature n8n people as guests, including solutions engineer Buddy R. and former n8n team member Viraj.
The posts show a working relationship with n8n but don’t state whether Watkins is an employee, owner, or contractor.
Anthropic’s security research is the news hook for an episode on AI-driven cyberattacks: Watkins cites Anthropic’s Mythos AI finding a 27-year-old OpenBSD bug and the model being pulled by the US government.
Netwrix appears as the employer of an interview guest.
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Watkins talks with Jake Mahon, AI team lead at the roughly 1,000-person cybersecurity company, about running AI boot camps for 100 non-technical employees. The post doesn’t state a commercial relationship between Watkins and Netwrix.
Dylan Watkins's work is best explored through the n8n podcast, where each episode pairs a practitioner guest with a concrete build or rollout.
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Start with the cybersecurity automation episodes for an open-source incident-response workflow and a live phishing analysis demo, or a home and small-business setup that scans Gmail and monitors firewall alerts.
The Netwrix episode covers an enterprise training rollout: 100 non-technical employees, two five-day boot camps, and 65 workflows in production.
The voice-agent and agents-versus-workflows episodes cover agency lead generation and tool-selection decisions.
Across the episodes, clean data, playbooks, and training come before model choice.
The tags below group the subjects, formats, and audiences; the similar creators section suggests other people to follow for ideas in security automation, resilience, and AI operations.
Desai writes about the same shift Watkins covers: AI is changing security operations, and automation can compress the time from detection to action.
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Both discuss operational friction—fragmented tools, manual steps, incomplete visibility—and argue for closing the gap between signal and response. Desai's Zscaler Agentic SecOps post also frames AI agents as tools shaped by frontline experience, echoing Watkins's guest-led episodes on AI in security operations.
Desai's posts explain a commercial platform and its capabilities from a product-launch and vendor perspective.
Watkins hosts an interview podcast and demonstrates open-source n8n workflows, often for practitioners and smaller teams, including homeowners and small businesses.
Desai focuses on enterprise SOCs and a unified platform; Watkins's work is more project-by-project and guest-driven.
Richards writes about practical resilience questions in the same territory Watkins explores: ransomware, phishing, vulnerability management, identity protection, and the gap between known risks and remediation.
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Both use specific incidents to argue that disciplined process matters more than buying more tools, and address what teams should do before an attacker reaches a trusted account.
Richards writes from a customer success and MSSP perspective at Atruent, often pointing readers to a TechDecanter newsletter and asking diagnostic questions about their environments.
Watkins demonstrates automation workflows, usually with a guest explaining the implementation on screen.
Richards's posts offer enterprise incident commentary; Watkins's are podcast episodes with downloadable workflow assets and extend to home and small-business security.
Ali S. and Watkins both examine what happens when AI tools scale inside security and data teams.
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Ali S.'s Mythos post argues that the real challenge is not finding vulnerabilities but managing the noise, false positives, and staff capacity that automated discovery creates. That focus on operational readiness aligns with Watkins's recurring argument that the workflow and the people around it matter more than the model.
Ali S. writes from a data protection and compliance angle at KEWDATA, using examples such as automated DSAR requests and the demand for deep technical cybersecurity skills.
Watkins builds episodes around n8n and screen-shared automation.
Ali S. offers short opinion and risk analysis; Watkins offers practitioner interviews and step-by-step workflow walkthroughs.
The only published audience figure is a LinkedIn follower count of 7,856, recorded 8 October 2026.
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The five posts, published between 4 October 2025 and 5 August 2026, are episode announcements for a podcast Watkins hosts and distributes on LinkedIn.
They interview practitioners: a former n8n team member now doing forward-deployed security engineering, a solutions engineer at n8n building phishing and firewall monitoring workflows, an AI team lead who trained 100 non-technical employees, and an agency founder working on voice agents and RAG for lead generation.
The recurring subjects are enterprise and small-business security automation, rolling out AI to non-technical staff, and voice agents for lead generation.
This content appears aimed at automation, security, and operations practitioners, as well as the agencies and vendors serving them; it does not establish who actually follows or watches.
For a B2B automation or AI tooling company seeking operations leaders exploring AI adoption, the subject matter is a fit.
Before committing to a co-marketing or podcast sponsorship, ask Watkins for recent results from comparable episodes and formats: views or listener counts, completion or retention if tracked, engagement per episode, and any audience survey covering job function, seniority, company size, and geography.
Ask specifically about episodes at similar technical depth to the sponsored placement, since the posts span security operations, corporate AI training, and agency voice-agent work, and performance may differ across them.
LinkedIn followers
7,856
LinkedIn account record for linkedin.com/in/dylanjwatkins, alongside the reviewed posts; the follower figure is not stated in any of the post texts. · 2026-10-08
Dylan Watkins' partnership activity in the posts here runs through podcast episodes rather than standalone sponsored posts.
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Each episode pairs them with a guest who demonstrates a working build on screen — a phishing-analysis workflow, a firewall alert enrichment flow, an enterprise training rollout — and ships with a free resource the audience can download and run themselves.
The promotional post that follows lists what the episode covers topic by topic, plus a guest-specific resource link and a link to the full video.
That format sets the practical requirements for a brand: supply a practitioner who can build or explain something real, and something the audience can take away and use.
Ask for the sponsor policy, rate card, audience demographics, inquiry route, pricing, lead times, and booking terms; the posts provide none of these.
Podcast episode with a practitioner guest
Buyer requirement
Bring someone who can screen-share a working build rather than just describe a product.
The episodes are structured around live demos — an n8n incident-response workflow, a Gmail phishing scan using VirusTotal, a firewall monitor enriched with VirusTotal, URLScan and MISP — with a walkthrough of the build and its results, followed by discussion of how the guest applies it.
Expect the episode to be framed around a concrete claim or number the guest stands behind.
The launch post says new episodes weekly, but the interview episodes appeared between roughly one and three months apart.
Confirm cadence before setting a launch date.
A free, usable resource tied to the episode
Buyer requirement
Provide an asset the audience can self-host and run: an open-source incident-response workflow, a guide plus a self-hosted cyber lab, or a step-by-step build document.
It is given away through a tracked partner link, so the value sits in the usable asset rather than the episode itself.
You need to be able to hand it over and support it after publication.
A pure brand-awareness slot with nothing downloadable does not match the pattern in the posts here.
Episode-linked promotion on LinkedIn
Buyer requirement
Work within the post format: an opening hook with a specific result or claim, a short description of the guest and their role, a bulleted list of topics covered, pointers to the walkthrough section where relevant, a link to the episode, and a link to the resource.
Commercial detail is limited to the resource link.
The posts carry no sponsor labels, discount codes, or disclosure wording you could reuse, so agree any labelling or disclosure requirements separately.
Recommended, with conditions. The subject matter and sponsorship unit fit the brief, but the posts do not establish audience size, per-episode reach, pricing, or disclosure terms. Confirm those before committing budget.
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Brief
A B2B automation or AI tooling company wants to reach operations leaders evaluating AI adoption through a co-marketing or podcast sponsorship partnership with Dylan Watkins.
Reasons
The topics closely match the brief. Reviewed episodes cover rolling out automation inside a large company with non-technical staff (Netwrix: two five-day boot camps, two global cohorts, 65 workflows in production), security automation built live on screen, voice agents and RAG for agencies, and the choice between agents and workflows. The episodes address operations and revenue teams deciding what to automate and how.
The sponsorship unit is a build, not a read. Each episode pairs Watkins with a guest who screen-shares a working system — an n8n incident-response workflow with a three-branch phishing analysis demo, a Gmail phishing scanner using VirusTotal, or a firewall monitor enriching alerts with VirusTotal, URLScan and MISP in under ten seconds. Each also offers a free asset the audience can download and run (an open-source workflow, or a step-by-step guide plus a self-hosted cyber lab). A tooling vendor has something concrete to attach an offer to.
The recurring argument suits an infrastructure or readiness pitch better than a model-quality pitch. Watkins's point across the posts is that clean data, written playbooks, and a workflow harness that can accept whatever model comes next determine whether an automation project pays off; the model itself is nearly secondary. A sponsor selling readiness, integration, data hygiene, or orchestration fits that frame; one selling on benchmark scores does not.
The posts offer usable mid-funnel proof points, with attribution. The Netwrix interview supplies named numbers — 100 non-technical employees, 65 workflows, $250,000 saved in the first month — plus a repeatable pattern ('context, intelligence, action'), a GitOps setup that lets non-developers ship to production with AI code review on every pull request, and credential management through Azure Key Vault. These are the guest's reported figures as relayed in the post, so cite them as the guest's claims.
Conditions
Choose the placement before pitching: a guest slot on a build episode, an episode sponsorship, and licensing and re-cutting the enterprise adoption episode for a mid-funnel audience are three different commitments with different costs.
Bring a practitioner who can build or walk through something real on screen, plus a downloadable asset the audience can self-host. The reviewed pattern offers a working resource through a tracked link; a brand-awareness mention with nothing to hand over does not match it.
Agree on labelling and disclosure separately. Dylan Watkins's posts provide no sponsor labels, discount codes, disclosure wording to reuse, or sponsor policy; ask for the terms before committing.
Ask for results from comparable technical episodes — views or listener counts, retention where tracked, and engagement — before setting a budget. The only measured figure available is a LinkedIn follower count of 7,856, recorded 8 October 2026; it is not a reach estimate.
Confirm publishing cadence. The launch post says new episodes are weekly, but the episode announcements reviewed suggest wider, uneven spacing, which affects launch dates and campaign windows.
Settle commercial terms directly with the creator. The posts provide no rate card, media kit, contact page, or inquiry route, so ask for pricing and lead times.
Not a fit. The mismatch is in format, subject, and mechanics, not effort or budget; more money or a longer commitment would not close the gap.
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Brief
A consumer fintech app wants to reach a mass-market US consumer audience through short-form video, with a code-driven offer and a fixed monthly posting commitment.
Reasons
The subject range is professional tooling, not consumer finance. The reviewed episode subjects are enterprise and small-business security automation, rolling AI out to non-technical employees, voice agents and RAG for lead generation, and the agents-versus-workflows buying decision. A consumer fintech offer has no natural entry point in these topics.
The posts show a podcast distributed through LinkedIn text posts that summarise episodes and link out to them, not a short-form video channel. A short-form commitment would therefore require evidence of that format and its performance before it could be assessed.
The giveaway mechanic is technical and self-hosted: an open-source workflow, setup guide, or self-hosted cyber lab distributed through a tracked link. A consumer app has nothing of that shape to offer, and the posts contain no discount codes, promo mechanics, or offer codes to use instead.
The only audience figure available is a LinkedIn follower count of 7,856, recorded 8 October 2026. Ask for per-episode views or listener data and audience demographics or survey results before assessing mass-market consumer reach.
The posts do not confirm a fixed monthly cadence or provide commercial terms, disclosure details, or an inquiry route. Ask the creator to confirm cadence and provide those details before committing.
Evidence of consumer-facing segments or formats, such as episodes aimed at individual consumers rather than practitioners, or a short-form video presence with performance data.
Per-episode audience figures showing substantial consumer reach, or an audience survey showing consumer composition.
A downloadable asset suited to a consumer offer and a disclosure policy covering code-driven placements. Ask Dylan Watkins for both; the posts mention neither.
A worked campaign example
Asset
Offer a downloadable resource the audience can run themselves, matching the pattern of an open-source incident-response workflow and a free guide plus self-hosted lab. A readiness checklist or importable workflow template could audit a company's automation prerequisites: whether incident data is centralised, playbooks are written down, credentials are managed, and non-developers can ship changes safely. Distribute it through a tracked partner link and support it after publication.
Brief
The B2B automation or AI tooling company in the fit recommendation wants a co-marketing or podcast sponsorship partnership reaching operations leaders evaluating AI adoption.
Campaign angle
Sponsor a build episode on the prerequisites for AI adoption rather than the tools. Watkins's recurring argument is that data, incident history, and written playbooks decide the outcome, while the model is nearly secondary. The incident-response episode makes this point through a live workflow; the enterprise training episode does so through a deliberate sequencing choice, keeping Claude out of the first two days so participants learned fundamentals first. A sponsor selling a platform for building, running, and monitoring automations can host that conversation without arguing about model benchmarks.
Guest profile
A practitioner who can screen-share a working build from start to finish and explain the rollout—not a product marketer. The reviewed episodes work because the guest builds live: a three-branch phishing analysis with threat-intelligence lookups, a firewall monitor that enriches alerts in under ten seconds, and a GitOps pipeline with AI code review on every pull request.
Open questions
Ask for the episode price, lead time, booking terms, and inquiry route; no rate card or inquiry route appears in the posts here.
Ask for the current cadence and next available slot: the launch post says weekly, but the reviewed announcements suggest wider spacing.
Agree on disclosure and labelling requirements for a sponsored episode or segment rather than copying prior posts.
Confirm whether the sponsor must supply the guest, the downloadable asset, or both.
Ask whether formats beyond the podcast are available, such as explainer posts, licensed episode segments, or co-hosted webinar material; these are not demonstrated in the reviewed work.
Placement
Book a guest slot on a single build episode, plus episode-linked promotion on LinkedIn in the established post format: an opening hook with a specific claim or number, a short description of the guest and their role, a bulleted list of episode topics, and two links—one to the episode and one to the downloadable asset. Re-cut the enterprise adoption material for a mid-funnel audience around the same episode.
Proof points
100 non-technical employees across two global cohorts completed two five-day boot camps, producing 65 workflows in production (guest-reported).
$250,000 reportedly saved in the first month (guest-reported).
AI assistance stayed out of the first two training days so fundamentals came first.
GitOps with AI code review on every pull request let non-developers ship safely.
Credential management through Azure Key Vault across a large cohort.
'Context, intelligence, action' applied to every workflow.
Threat enrichment in under ten seconds using VirusTotal, URLScan, and MISP.
For a co-marketing or podcast partnership targeting operations leaders evaluating AI adoption, Deepen Desai is the better choice when the offer is aimed at enterprise security buyers, CISOs, SOC leaders, and threat researchers, and the message depends on authority in security operations rather than automation adoption.
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Their posts show a vendor executive speaking directly about an agentic security operations launch, frontier-model testing, and the gap between signal and action in security operations. That makes them a closer fit for a security platform or threat-intelligence sponsor than an operations-leader AI tooling pitch.
The posts are company launch and product commentary, not a creator-led show with a guest build, a screen-shared workflow, or a downloadable audience asset.
Choosing Deepen Desai trades the build-and-giveaway sponsorship format and the operations-leader audience evaluating AI adoption for security-domain authority.
Ask for follower count, per-post performance data, sponsorship availability, a rate card, and a contact route; none is published in the posts here.
For a co-marketing or podcast partnership targeting operations leaders evaluating AI adoption, Bradley Richards is the better choice when the offer addresses vulnerability management, patch discipline, identity protection, ransomware resilience, or MSSP and customer-success workflows.
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The audience is cybersecurity practitioners and customer success teams, rather than general operations leaders buying automation. Their posts tie ransomware and Active Directory attacks to known, unpatched vulnerabilities and privileged-account protection, making them a fit for a security readiness or remediation sponsor.
The posts offer short analytical commentary on security incidents and customer-success lessons, not an episode format with a practitioner building live on screen or a downloadable tool.
The audience is narrower, focused on security and customer success rather than operations leaders considering AI adoption.
Ask for audience and per-post performance figures, a reusable sponsorship unit, disclosure terms, and an inquiry route; none appears in the posts here.
For a co-marketing or podcast partnership targeting operations leaders evaluating AI adoption, Z Ali S. is the better choice when the campaign needs a skeptical, practitioner-facing argument about AI security automation, especially noise, false positives, analyst fatigue, cybersecurity hiring demand, and data governance.
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Their posts challenge the assumption that AI vulnerability discovery is the main problem and argue that managing the resulting volume and securing AI adoption are harder issues. That suits a sponsor selling governance, compliance, or security operations capacity rather than a general automation platform.
The posts offer commentary and prediction, not a podcast or co-marketing format with a guest build, a live workflow, or a giveaway asset.
Choosing Z Ali S. trades the operational, build-first audience and downloadable-resource mechanic for a security and data-governance argument.
Ask for follower count, per-post performance data, sponsorship availability, pricing, and a contact route; none is published in the posts here.
This profile draws on five LinkedIn posts published between 4 October 2025 and 5 August 2026, alongside the page’s other sections.
Descriptions of podcast episodes, workflows, and guides are based on Watkins’s posts; the underlying episodes and materials were not independently reviewed.
