The AI Cyber Apocalypse That Isn’t Coming | Ciaran Martin

Ciaran Martin built the UK's National Cyber Security Centre from the ground up, led it for its first four years, and now teaches at the University of Oxford. Lately he's become one of the sharpest critics of the panic around frontier AI and cybersecurity. On this episode of the Resilient Cyber Show, I put his argument to the test.His case is that two things are true at once. Frontier AI is a real shift for attackers, and the reaction to it is the biggest FUD outbreak in over a decade.Look at the timeline. When the delayed release of Mythos was announced on April 7th, the warning was that defenses would be overrun within six months. Six months later, there has been no discernible rise in disruptive attacks, and disruptive attacks can't hide. Britain's worst damage still came from traditional attacks in 2025 on Jaguar Land Rover, Marks & Spencer, and the Co-op.Meanwhile, the hype is drowning out real incidents. The same week AI agents reading a few Australian websites made global headlines, the FBI appeared to have been breached by ShinyHunters, exposing case assignments, spousal addresses, and psychiatric evaluations. It barely registered.We get into why the famous 27-year-old bug wasn't worth $20,000 in tokens to any real attacker, and what OpenAI's engineers admitted about Hugging Face at Black Hat. We also cover the "cult of the machine god," alignment with whose values, and why software makers have dodged liability for decades. Ciaran also asks the question the AI debate keeps skipping: who would actually launch the catastrophe?Then he takes on the hardest question himself. What if he's wrong? His answer draws on running the NCSC through WannaCry and NotPetya in 2017. He closes with the one question every CISO should ask the board before discussing any "AI hacked X" headline.⏱️ CHAPTERS00:00 Introduction01:37 Introducing Ciaran Martin02:02 The Early Days of Cybersecurity03:04 Why Governments Lagged on Cybersecurity04:55 Public-Private Cybersecurity Partnerships06:00 Why Leaders Avoid Technical Questions07:27 AI Hype vs. Cybersecurity Reality11:22 AI Safety vs. Cybersecurity19:04 Two ways of reading the AI 25:46 The FBI Breach and AI Hype27:43 ShinyHunters and Real-World Cyber Threats29:37 Who Will Use AI to Launch Cyberattacks?29:58 Who Would Actually Launch the Catastrophe?35:00 The Devil's Advocate Case: AI-Powered Script Kiddies43:33 What CISOs Should Tell the Board45:00 ClosureSOURCES AND FURTHER READINGCiaran Martin in The Economist — Fears of AI-induced armageddon are overdone: https://www.economist.com/by-invitation/2026/08/23/fears-of-ai-induced-armageddon-are-overdone📬 SUBSCRIBE TO RESILIENT CYBERhttps://www.resilientcyber.ioIf this was useful, subscribe. I cover AI security, agentic AI, AppSec, software supply chain, vulnerability management, and cyber policy for practitioners every week.#AISecurity #Cybersecurity #FrontierAI #CyberPolicy #AISafety #NCSC #ThreatIntelligence #CISO

Itamar Apelblat was called back to reserve duty with Unit 8200 and spent hours waiting on access approvals. Then he remembered a service account his old team had set up seven years earlier. The password was a funny one, which is why he still knew it. He typed it in and became an admin on one of the most secure networks in the world.Nobody had changed that password. They hadn't forgotten about it. They were scared to touch it, because no one knew what would break.Now put that same fear in front of AI agents. When Token Security's research team checked its enterprise customers, more than 16 percent already had Muse running locally against corporate email and other resources. Muse launched three weeks before we recorded and is already the most popular productivity app in the App Store. Itamar expects agents to outnumber humans in the enterprise a hundred to one.His argument is that you can't secure agents by predicting every way they'll go wrong. An agent chases its goal like it's possessed and takes any access path that gets it there. What you can control is how much autonomy it has and what it's allowed to touch. Both come down to identity.In this episode I sit down with Itamar, co-founder and CEO of Token Security, and we get specific:→ The three things companies find the first time they look: agents wired straight into production on raw API keys, abandoned experiment agents still holding privileges, and agents still running after their owner left the company→ What intent-based access management actually means, and why an agent built to send a weekly report should never be able to delete from your database→ Why IGA and PAM fall apart here: they treat Okta or Active Directory as the source of truth, while agents live on laptops, in SaaS, and in the cloud→ What happens when a coding agent tries to connect to a production Snowflake environment, and how to decide where a human still has to approve→ Who should own agent security, and why Itamar puts most of it with the IAM teamI also put the hard question to him. We've had twenty years to get least privilege right for humans and mostly failed, so why would agents go any better? Then, at the end, he gives his advice on where security teams should start. It isn't the usual "get visibility first," and it's the part I'd most want a security leader to hear.⏱️ CHAPTERS0:00 Introduction1:49 Unit 8200 and "Which Product Do You Hate the Most?"3:58 The Seven-Year-Old Password That Still Worked6:32 Autonomy and Access: The Two Dimensions of Agent Risk8:19 Why Agents Act Like They're Possessed10:14 16% Already Run Muse: What Companies Find12:46 Intent-Based Access Management, Explained15:15 Twenty Years of Failed Least Privilege17:15 Why Your IGA Won't Scale to Agents19:04 Where the Human Stays in the Loop21:12 Who Should Own Agent Security23:33 The Security Teams That Get This Right26:35 Closing ThoughtsSOURCES AND FURTHER READINGToken Security: https://www.token.security/Itamar Apelblat on LinkedIn: https://www.linkedin.com/in/itamar-apelblat/📬 SUBSCRIBE TO RESILIENT CYBERhttps://www.resilientcyber.ioIf this was useful, subscribe. I cover AI security, agentic AI, AppSec, software supply chain, vulnerability management, and cyber policy for practitioners every week.#AISecurity #AgenticAI #IdentitySecurity #NonHumanIdentities #IAM #AIAgents #LeastPrivilege #Cybersecurity

Matt Hartley, co-founder and Chief Product Officer of BreachRx, on why the once-a-year tabletop no longer matches the incidents organizations will actually face, and how AI-accelerated micro tabletops let teams train like they fight.In this episode I sit down with Matt Hartley, co-founder and Chief Product Officer of BreachRx. Matt has spent 28 years in cybersecurity. He started in government offensive security, then moved to the cyber threat intel startup iSight Partners, where he ran product through its acquisition by FireEye, and later ran Mandiant Engineering. He watched consulting teams parachute into companies that were compromised and meaningfully unprepared, and that convinced him the real gap was the response process, not detection or tooling.We get into what a micro tabletop actually looks like and why exercises should run in the same system you will use during a real incident. We also cover how notification clocks as short as 30 minutes change what legal teams need to practice, and why the floor is shifting toward multiple concurrent incidents.In this episode:● Why the industry over-invests in technology and under-invests in the processes and procedures that carry a response● What a micro tabletop looks like, from a one-hour cross-functional session to an exercise that runs asynchronously over a week with a 30-minute hot wash● Train like you fight, and why rehearsing in your actual response platform lowers stress and folds lessons learned back into procedures● More than 200 laws with incident notification requirements, including China's 30-minute window and India's six-hour rule covering even denial of service● Starting a legal tabletop partway into a ransomware scenario to pressure test DORA, SEC, and other regulatory timelines● Why privileging everything means nothing is privileged, and separating the factual record from privileged conversations● The risk of 10 to 100 Slack or Teams channels spinning up around a single incident, and how one grouchy message can end up in evidence● Keeping exercises from becoming check-the-box by matching frequency to team size and threat, pulling scenarios from the headlines, and running two incidents at once● Why AI is raising the attack floor, from smarter background malicious traffic to lower-tier nation states making big capability jumps● A workforce of AI agents that cuts incident reporting from 20 hours to 30 minutes and turns NIST, CISA, or Gartner guidance into tailored procedures● A crawl, walk, run playbook for your first micro tabletop: three injects, one ornery stakeholder relationship, and a ten-minute debrief● What regulators and plaintiffs will ask for, and why the SEC may look at five years of incidents, not just oneChapters:0:00 – Intro1:42 – Matt's Path from Offensive Security to Mandiant2:14 – Why Response, Not Detection, Was the Real Problem3:40 – What a Micro Tabletop Actually Looks Like7:37 – Train Like You Fight in the Real Platform9:33 – Regulatory Clocks, DORA, SEC, and 30-Minute Notifications11:56 – Privilege, Discoverability, and the 100 Slack Channel Problem15:03 – Keeping Exercises from Becoming Check-the-Box17:48 – Concurrent Incidents and a Rising Attack Floor19:53 – Where AI Agents Fit in Incident Response22:01 – Running Your First Micro Tabletop Next Month24:12 – Proving Continuous Readiness to Regulators and Plaintiffs26:55 – ClosingConnect with Matt Hartley:LinkedIn: https://www.linkedin.com/in/wmhartl/BreachRx: https://www.breachrx.comBreachRx IR Exercises: https://www.breachrx.com/rex-platform/incident-response-exercises/Read my piece on BreachRx and incident response, Chaos, Clocks, and Command Centers: https://www.resilientcyber.io/p/chaos-clocks-and-command-centersResilient Cyber: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.#incidentresponse #tabletopexercise #aisecurity #ciso #cyberresilience #securityleadership

James Berthoty of Latio on why the endpoint is now the center of AI security, and why most of the real agent risk traces back to blind spots we already had.I sit down with James Berthoty, who started Latio as an engineer frustrated by how hard it was to figure out what security tools actually did. That turned into a practitioner-focused, buyer-oriented analyst firm. We dig into Latio's second AI security market report. Last year the story was browsers and proxies. This year it's the endpoint, where coding agents now run with the permissions and credentials on developer laptops.We get into what roughly 400 AI security startups are actually differentiating on and why runtime detection claims need hands-on testing. We also cover why James pushes back on the runtime-first narrative, where the new AI security budget is coming from, and how security leaders should narrow the vendor field before they ever take a demo.In this episode:● Why we are in the "pre-HTTPS era" of AI security, and how coding agents turned developer endpoints into the new pressure point● Dedicated AI security budget jumping from 8% to 37% in a year, and how it flows out of AI governance● What is already commoditized, and why intent-based runtime detection needs hands-on testing● Agent blast radius, and why your agent shouldn't be able to drop the prod DB because you shouldn't be able to either● Why recent AI safety incidents look more like misconfigurations than emergent behavior● The next M&A wave as a fight over the laptop● Anthropic's inference hooks, and why frontier labs likely won't absorb the security market● MCPs and skills as a software supply chain problem with a new delivery mechanismChapters:0:00 Intro0:31 Why James started Latio1:00 From browsers to the endpoint8:15 Do you need a purpose-built AI security platform?11:52 Where the AI security budget comes from13:53 400 startups and testing runtime claims19:28 Blast radius and runtime vs. posture23:35 M&A and the fight over the endpoint33:22 Inference hooks and frontier labs vs. vendors36:03 MCPs, skills, and software supply chain39:30 Advice for security leadersConnect with James:LinkedIn: https://www.linkedin.com/in/james-berthotyLatio: https://www.latio.com/AI Security Market Report: https://pulse.latio.tech/p/the-2026-latio-ai-security-marketResilient Cyber: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.#aisecurity  #agenticai #endpointsecurity #appsec #supplychainsecurity #mcp #cybersecurity

Zack Korman on why the AI safety debate has been captured by an extinction narrative, and why the incident everyone is calling a watershed moment looks a lot more like a preventable security failure.In this episode I sit down with Zack Korman, co-founder of Embroidery, where he uses AI to monitor AI agents, and former CTO of the cybersecurity company Pistachio. I first came across Zack on X during the controversy over fake SOC 2 reports, and he has since become one of the sharpest critics of how AI safety is being framed, funded, and investigated.We get into the effective altruism roots of the existential risk movement, why he argues METR's review of the Hugging Face incident was not independent oversight, and what an actual incident response firm would have done differently. Zack makes the case that alignment is one control among many, that there is no "safe" path in AI, only trade-offs, and that the real risk for most organizations is enterprise environments that were never ready for agents in the first place.In this episode:● How building an AI insider threat product pulled a developer and CTO into the cybersecurity community, and into picking fights on X● Effective altruism, longtermism, and how a focus on preventing extinction came to dominate AI safety● Why "just be careful" misses the point when every path involves trading one risk for another● Dario Amodei's Pacing the Frontier, independent auditors, and why Zack calls bringing in METR "bring your friend to work day"● The funding and relationships connecting METR, Redwood Research, Coefficient Giving, and the labs● True believers versus IPO hype, and why genuine belief does not make someone right● Why many AI doomers believed we were all going to die before they ever learned about computers● The Hugging Face investigation, context drop in AI-analyzed transcripts, and treating knowable facts as unknowable● What Unit 42 or Mandiant would have demanded before putting their name on the report● Eight layers of failure, from a single package proxy at egress to missing monitoring, classifiers, and kill switches● Alignment failure versus containment failure, and why alignment belongs inside defense in depth● The real risks: threat actors misusing AI, enterprise agent deployments, and new attack chains● Why security's risk-averse, laggard culture may be its biggest vulnerabilityChapters:0:00 Intro0:54 Zack's Background1:43 What Turned a CTO Into an AI Safety Critic3:31 Effective Altruism and the Extinction Narrative5:53 No Safe Path, Only Trade-offs6:40 METR, Redwood, and Bring Your Friend to Work Day10:23 True Believers, Hype, or Both12:49 How Doomers Find Their Way Into AI14:39 Taking AI Risk Seriously When It Is Ideological16:56 What an IR Firm Would Have Asked21:10 Eight Layers of Failure in the Hugging Face Incident22:49 Alignment Failure Versus Containment Failure24:32 Alignment as One Layer of Defense in Depth26:22 Why Enterprise Environments Are Not Ready for Agents29:10 Security's Laggard Culture29:19 ClosingConnect with Zack Korman:X: https://x.com/ZackKormanEmbroidery: https://embroidery.ioWebsite: https://zkorman.comResilient Cyber: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.#aisafety #aisecurity #agenticai #incidentresponse #effectivealtruism #cybersecurity

Jonathan Rende of Checkmarx on why the model writing your code cannot also be the control that validates it, and why rules-based and AI-driven scanning turn out to find almost entirely different bugs.In this episode I sit down with Jonathan Rende of Checkmarx. Jonathan worked with Fortify and SPI Dynamics back in the day, spent most of the last decade leading product teams in developer and DevOps tooling, and came back to security eighteen months ago because, as he puts it, this is the heart of the hurricane. His argument is that AI is a bigger disruption than the internet, SaaS, or mobile were, not because of any single capability, but because it hits roles, process, and productivity all at once.We get into the two waves he has watched play out with CISOs and their CEOs, why the pendulum has swung back toward program and posture questions in the last quarter, what his research team found when they benchmarked deterministic and probabilistic scanning side by side, and why he thinks agentic AppSec raises the profile of the security team rather than automating it away.In this episode:● Why the first half of 2026 became a real inflection point rather than another AI talking point● The two waves: engineering told to run at any cost, then the pendulum swinging back toward posture and program design● Why functional AI-generated code and secure AI-generated code are still two different things● Separation of church and state, and the conflict of interest in letting the model that generates code also validate it● Benchmarking deterministic and AI-based scanning across dozens of open source projects, and why the overlap stayed consistently under 10%● Fidelity, F1 scores, and the absence of real standards or shared benchmarks in AppSec● Why an incentive to reduce risk and an incentive to sell tokens are not the same incentive● Why agents free AppSec professionals for higher-order work, and why this is not a dark factory● Shadow IT becoming shadow AI, and early scans where half surfaced models, agents, and MCP servers security teams did not know existed● Why new threat vectors show up first in fast-moving unregulated companies while regulated ones see more code-level issues● Low-priority vulnerabilities chained into real impact, and why backlogs now matter as much as incoming code● What to change first: metrics defined up front, in-workflow AppSec, and security reviews that went from annual to monthlyChapters:0:00 Intro0:18 Fortify, SPI Dynamics, and a decade in developer tooling1:24 Why he came back to AppSec2:54 Why the first half of 2026 was the inflection point5:27 Two waves, and the pendulum swinging back9:08 Functional AI code versus secure AI code11:58 Layered defense and the condensed lifecycle15:04 What agents free AppSec teams to actually do17:50 Separation of church and state20:15 Fidelity, F1 scores, and not selling tokens23:25 New threat vectors and organizational maturity25:47 Shadow AI and what the inventory scans found27:58 What to change first in your AppSec program30:44 ClosingConnect with Jonathan:LinkedIn: https://www.linkedin.com/in/jonathanrende/Checkmarx: https://checkmarx.comResilient Cyber: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.#appsec #aisecurity #devsecops #shadowai #vulnerabilitymanagement #ciso

Rock Lambros, Co-Lead of the 2026 OWASP Top 10 for LLM Applications, on why prompt injection would have fallen out of the top 10 based on incident data alone, and why the community kept it at number one anyway.In this episode I sit down with Rock Lambros, longtime security leader, former CISO, core team member of the OWASP GenAI Security Project, and Co-Lead of the 2026 OWASP Top 10 for LLM Applications, to dig into the new list and the harder questions underneath it. We get into the letter from the project leads that opens the document, why the LLM and Agentic lists are converging, what a year of messy incident data actually told the working group, and why Rock argues that agency is not authorization.In this episode:Why the LLM Top 10 and the Agentic Top 10 are merging in practiceThe opening letter, and why the industry was slow to admit the model was never the thing to secureWho benefits from a model-centric framing of AI securityPrompt injection ranked number one by practitioners and out of the top 10 by the incident dataWhy incidents get reported by outcome rather than by initial vectorMisinformation, the widest gap between the vote and the dataHidden Context Exposure, soft guardrails, and why instructions and data share one context windowContext rot and why context window management matters for agents doing critical workUsing AI to govern AI, and the dual-layer approach in the Agentic Control StandardAgency versus authorization, and why OAuth is what we have rather than the answerHow to get involved in the OWASP GenAI Security ProjectChapters: 0:00 Intro and Rock's background 1:17 What the agentic work changed about the LLM Top 10 3:59 The opening letter and "It Was Never the Model" 8:48 Incident data and the prompt injection ranking 11:23 Misinformation and the limits of the data 14:24 Hidden Context Exposure and soft guardrails 17:18 The context window and context rot 19:57 Using AI to govern AI 22:49 Excessive agency, and agency versus authorization 27:09 How to get involved with OWASPConnect with Rock:LinkedIn: https://www.linkedin.com/in/rocklambrosOWASP GenAI Security Project: https://genai.owasp.orgGet involved: https://genai.owasp.org/contributingOWASP Top 10 for LLM Applications 2026: https://genai.owasp.org/resource/owasp-genai-llm-top-10-2026/Read my piece on the new list, It Was Never the Model: https://www.resilientcyber.io/p/it-was-never-the-modelResilient Cyber: https://www.resilientcyber.io

Ondrej Vlcek, CEO of AISLE and former CEO of Avast, on why AI vulnerability discovery is not as commoditized as the industry thinks, and why remediation is still the real bottleneck.In this episode I sit down with Ondrej Vlcek, Founder and CEO at AISLE. Ondrej spent roughly 30 years in cybersecurity, joining Avast as employee number six or seven doing kernel-mode driver work on Windows 95, eventually becoming CTO and then CEO, taking the company public and selling it to NortonLifeLock in a nearly $9 billion transaction. He co-founded AISLE in the fall of 2024 to close the loop from discovery through triage, remediation, and verification. His team has now disclosed 350 plus CVEs across projects like OpenSSL and curl.We get into why the moat sits in the system and not the model, why the gray market price of vulnerabilities has not collapsed even as models get cheaper, and what it actually takes to ship a patch a maintainer will accept.In this episode:- Going from Avast intern to CEO, and why vulnerability management was the next problem- The jagged frontier, and why bigger models do not always mean better results- Which classes of bugs got cheap to find and which are still genuinely hard- Why vulnerability prices have not collapsed despite all the model progress- Building a model-agnostic system with bespoke benchmarks for model selection- Sovereign AI, on-prem and air-gapped deployment, and why findings are the real crown jewels- Triage, reachability, and why most findings are not actually exploitable- Patch verification, regression risk, and mitigations for embedded systems that cannot be patched- How AISLE earned trust from curl after Daniel Stenberg killed the bug bounty- Whether a CVE count is a vanity metric- Build versus buy as model capability keeps getting cheaper- What breaks first in the CVE and open source maintainer ecosystem- What AppSec leaders should change next quarterChapters0:00 Intro0:24 From Avast employee number six to a $9 billion exit3:26 Why vulnerability management, and why now5:15 The jagged frontier and what bigger models miss10:36 The economics of finding bugs, and why prices have not collapsed12:11 Building a model-agnostic system with real benchmarks14:30 Sovereign AI, air-gapped deployment, and who sees your findings19:42 Triage, reachability, and why remediation is the bottleneck24:48 Patches that break things, and systems you cannot redeploy25:39 curl, Daniel Stenberg, and death by a thousand slops29:35 Is a CVE count a vanity metric?31:34 Build versus buy when capability keeps getting cheaper34:41 What breaks first in the next 18 months39:46 What AppSec leaders should do next quarter41:13 ClosingOndrej Vlcek on LinkedInAISLEAISLE research and blogResilient Cyber SubstackSubscribe for more conversations with security practitioners and leaders.

Lovable CISO Igor Andriushchenko on soft guardrails vs. hard boundaries, securing vibe coding for non-developers, and building a security program at a 10x company.I sit down with Igor Andriushchenko, Head of Security and CISO at Lovable, the AI development platform behind one of the fastest growth stories in the space. Igor joined as the first security hire when the company was around 40 people. A year later he is running a 20+ person team covering product security, GRC, IT, and platform safety for a company with 400 laptops in MDM and no sign of slowing down.We get into what it actually takes to secure AI-native development, both inside a hypergrowth startup and on a platform where most of the people shipping software are not developers and definitely not security practitioners.In this episode:Building a security program for the company you will be in 12 months instead of the one you are in todaySoft guardrails versus hard guardrails, and how to decide which one a problem deservesWhy hard blocks push AI-assisted workflows into the shadowsRooting guardrail decisions in business goals, risks, and threats rather than tool defaultsDemocratized development without democratized security, and what a platform owes the 99%Lovable's auto-fix toggle, per-app threat models, and the goal of an app with no security tab at allWhether models will ever produce secure code by default, and why defense in depth still carries the loadGoverning the reality that every employee vibe coding an app looks a lot like a new vendorGRC engineering as the way to measure control efficiency layer by layer against AI-powered attackersCRA, NIS2, and the EU AI Act landing on citizen developers who never thought of themselves as software manufacturersChapters: 0:00 Intro 0:23 Igor's background from DevOps to CISO 3:54 Scaling security at a 10x company 6:07 Reinventing the team when growth breaks it 08:26 Soft guardrails versus hard blocks 14:05 Tying guardrails to business risk 17:32 Democratized development, undemocratized security 18:52 Shared responsibility on an AI dev platform 21:16 Auto-fix, per-app threat models, and no security tab 25:21 Will models produce secure code by default? 29:56 Every employee vibe coding is a new vendor 30:57 Enterprise controls, publishing gates, and PII scanning 36:39 AI-powered attackers and why good enough changed 40:43 GRC engineering and measuring control efficiency 46:19 CRA, NIS2, and the citizen developer 52:41 Trust centers for builder apps 54:08 Closing thoughts on the vibe coding communityGuest links: Igor on LinkedIn: https://www.linkedin.com/in/igor-andriushchenko Lovable: https://lovable.devResilient Cyber: Newsletter and episode archive: https://www.resilientcyber.io Subscribe for more conversations with security practitioners and leaders.

CISOs have a stack of tools but no system built to run the security program itself. Mike Armistead wants to fix that.In this episode I sit down with Mike Armistead, co-founder and CEO of Pulse Security AI and a longtime security founder behind Fortify and Respond Software. We dig into why the security leader has never had a system of truth the way the CFO has an ERP and the CRO has a CRM, and how an agentic layer on top of the existing tools can finally close that gap. Mike is measured about where AI gets to decide and where the human stays in the seat, and he shares what surprised him most from research with more than 80 senior practitioners and corporate directors.In this episode:- Why two exits later Mike came back to build a third company around the AI wave- The silos that left CISOs with an acronym soup of tools and no way to run the program- What a system of truth for the CISO actually means and how it layers on top of existing structured and unstructured data- Where agents do the heavy lifting on regulatory monitoring, vendor intelligence, and status reporting- Governing the guardrails, not the keystrokes, and why closing the loop still involves people- What corporate directors actually want to hear in the 15 to 20 minutes a CISO gets each quarter- The findings that stood out, including that 55% of boards have never defined the cyber risk they are willing to accept, and only 12.5% of CISOs are very confident the board leaves with a true picture of the risk- Institutionalizing the tribal knowledge every security program runs onChapters:0:00 Intro0:18 Mike's background and two prior exits1:08 Why the AI wave pulled him back2:21 Why the CISO has no system to run the program4:09 Starting at the program level, not the SOC or AppSec5:28 What a system of truth for the CISO means8:19 Speaking the language of the business9:09 Where AI does the heavy lifting on a typical Tuesday11:57 Govern the guardrails, not the keystrokes15:44 Bringing deputies into the conversation16:46 What the research with senior practitioners found20:37 Boards, risk tolerance, and the reporting gap24:57 AI as a double-edged sword for security leaders25:35 Joanna Burkey and institutionalizing tribal knowledge27:31 A year from now for the security leaderGuest links:Mike Armistead on LinkedInPulse Security on AIMore Resilient Cyber:Substack: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.