Categories
Artificial Intelligence Conferences Security

“Culture eats cyber strategy for breakfast”: Notes from 813 Tech Day’s Security Panel

I spent the morning and early afternoon of 813 Tech Day at Hotel Haya in Ybor. I’m still thinking about the Fortifying the Digital Frontier: Cybersecurity at the Forefront of Fintech Innovation session, largely because of the twist that host Michael Hall introduced, which made it different from every other “Cyber is important, yo!” panel I’ve sat through. About two-thirds of the way in, he stopped running the panel and turned it into a consulting engagement. On stage, for free, for a random attendee. And it worked!

Read on, and you’ll see.

A show of hands

Michael started by asking everyone who runs a company or product that touches money, customer data, or both to raise their hands.

Some hands went up, which wasn’t surprising.

Then he asked: “Keep them up if you have a single person whose actual job is nothing but security.”

All hands down.

And that moment was the panel in summary. A room full of people founding or working at companies (or hoping to found and work at them) handling money and PII, and essentially zero dedicated security headcount among them. To be fair, a number of them were solopreneurs. Still, Michael’s follow-up question was  an important one: “So what are you going to do about cyber warfare?”

Introducing the panel

The panel had unusually good coverage of the problem space: economic development, defense-grade compliance, offensive security, and someone who actually runs a bank.

They were, from left to right onstage:

The gap between passing the audit and actually defended

Michael’s next question was a good one: “What’s the widest gap between how secure fintechs think they are and how secure they actually are?”

Alexei’s answer was the cleanest formulation of the compliance trap: compliance does not equal security. You can check every box and still be wide open. His diagnosis of why startups get this wrong:

“We identify the target, then we fire, and then we aim.”

Speed first, aim later. But in banking, “later” can be expensive in ways founders don’t model. He mentioned that for an average-sized bank, a single day of downtime can put the bank’s license at risk.

Candace, coming from the defense side, made it concrete with the ATO, the Authorization to Operate. You bring in an assessor, they verify you’ve got your asset labeling and your SSO and your password policy, and you get the shiny gold star.

And then what?

“Are you updating your AV definitions after you have the ATO? Are you patching on a specific cadence? Are you continuously monitoring the controls you got a check box for?”

Compliance is a still-frame snapshot. Security is the whole movie. Everyone optimizes for the snapshot because that’s what gets audited, but forgets about the movie.

“Too small to matter” is not a security posture

Michael asked Aaron to scare the room, and to Aaron’s credit, he skipped the horror stories and reached for stats.

An attacker can get into essentially any internet-facing machine at almost any company inside an hour. Depending on whose telemetry you’re reading, that number is more like a few minutes. Someone in the audience called out CrowdStrike’s breakout-time figure, which is measured in seconds now.

Aaron’s framing:

“A breach is inevitable. Not if, but when. Your worst day is my every day. If it’s going to rain, you bring a raincoat, not an umbrella.”

That’s why “we’ll deal with it when it happens” isn’t a plan.

What AI did and didn’t change

Aaron summarized it well:

“AI lowered the skill floor for attackers and accelerated the execution timeline. It did not invent new attack classes.”

Phishing, smishing, and credential reuse: these are the same failure modes we’ve had for a couple of decades now. Attacks are just cheaper, faster, and automated now. All this means that your unpatched, password-shared, over-permissioned environment didn’t get more vulnerable; it just got found sooner.

He also had a nice riff on password policy whiplash. We spent years pushing everyone to 15–16 characters, guidance loosened again, and meanwhile the real-world state of the art is that password123 became password12345.

Alexei’s defensive take was the one that fintech founders in the room needed: his bank is doing “baby steps” on AI. Instead of a tool, the first step an AI policy and an AI strategy with actual guardrails. Because the failure mode isn’t anything as melodramatic as a rogue superintelligence, but something more mundane, such as an employee pasting client data into a public chatbot:

“Yes, you can get the answer. But now you’ve already lost that client data. It’s somewhere, and you don’t know who can get it.”

He also noted, matter-of-factly, that some of the adversaries in this space are state-funded. A small bank in Tampa versus a government-backed team is not a fair fight, which is precisely why the guardrails have process over motivation; policy and architecture over vigilance.

The compliance question founders actually care about: Which one pays?

When Michael asked which single compliance framework a founder should chase this year to unlock the most enterprise revenue, Aaron flagged it as a contentious opinion and we got the most useful ninety seconds of the panel:

  • SOC 2 Type II is the one. Depending on your market, it can move your ability to capture revenue by somewhere between 5% and 40%. Nearly everyone selling to enterprise ends up needing it anyway.
  • HIPAA is self-assessed. Draw your own conclusions about how rigorously that’s happening across the industry.
  • PCI DSS: If you’re doing payments and processing, you can largely offload it. Stripe already has it. Use their pipes; as a startup you can’t afford to build that infrastructure yourself.
  • Then there’s the practitioner’s trick: security people maintain crosswalks that map controls across frameworks. Do SOC 2 first and you’re roughly 70% of the way to ISO 27001. Do them in order and stop paying for the same control four times.

Candace added the necessary caveat: the right framework depends on your industry, and in defense you don’t get to choose; there are non-negotiable requirements.

Alexei pointed out that PCI DSS matters for finance the way HIPAA matters for healthcare, so “which framework” is downstream of “which industry.”

Candace’s advice for taking this to a board is deceptively simple: explain it in their language…

  • Bad: “We need to implement AC-2.”
  • Better: “We sell Cracker Jacks, here’s the system that keeps the Cracker Jack business running, here’s why this control protects it.”

The panel turned into a live advisory board

This is the part I’ve never seen at a conference.

An audience member who’s a consultant mentioned he’s got a client (transfer agents, handling bank relationships and a mountain of shareholder PII) who wants to point an agentic AI system at their overflowing email inbox.

The debate: should they be cloud-based, or reverse twenty years of industry momentum and go back to on-prem so they can hot-swap open-weight models without token costs and keep everything whitelisted?

Michael stopped the panel, brought the consultant to the front, declared the panelists a pop-up advisory board, and made them answer.

The responses split about how you’d expect from their backgrounds:

  • Alexei: Going on-prem relocates risk rather than eliminating it. It also means you’re now defending on two fronts: not just outsiders, but also insiders! You’re paying for infrastructure, security, and people. The “cheaper” assumption usually doesn’t survive contact with the invoice. When Microsoft ships patches every week, that’s a vendor doing work you’d otherwise be doing yourself, maybe badly.
  • Aaron: Go hybrid, on the grounds that nobody has a crystal ball about second- and third-order downstream constraints, and hybrid preserves optionality for next year.
  • Candace: Her world is mostly on-prem and air-gapped, so that’s where her instinct goes, insider threat and hiring burden included.
  • Paul: He’s a retired Rear Admiral, so he followed the Navy adage “A ship’s a fool to fight a fort” and declared the question outside his expertise and deferred to the other panelists. In my opinion, that earned him even more credibility.

Michael then asked for the consultant’s contact info so they can follow up in 60 days and report back to the room on what he actually decided. That’s the accountability loop conferences never close. I’ll keep tabs on this and let you know how it turned out.

After that, they did it again, this time with an attendee trying to break from defense-sector BDR work into commercial cybersecurity account management. They brought her to the front and gave her a live career consult.ation.

Candace’s advice was to stop being invisible on LinkedIn and start advertising the specific role she wants.

Aaron also had good cybersecurity-specific advice:

“Cybersecurity is one of the most arrogant professions on the planet. If you’re the one person they want to have a beer with afterward, you’ve already won.”

(I work in cyber. He’s right. In this field, being able to communicate humility is a cheat code.)

And finally, in a fit of audience participation, and after quickly consulting NetFoundry’s careers page (I work there and love it!), I stood up and asked her “How about starting with a Sales Development Rep role that works with Account Management? We have an opening at NetFoundry.”

She said “yes,” and Michael yelled “Joey’s got to get her the job!”

(She and I chatted afterward. Our conversation will be ongoing, and I guess I’ll have to follow up with Michael in 60 days…)

Tampa Bay resources you should know about

Paul’s whole reason for being there was to make people in the room aware of resources they might not have tapped:

  • The Florida High Tech Corridor spans 23 counties from Tampa Bay to the Space Coast, and deliberately plays Switzerland across all of them; there are no favorites among universities.
  • USF’s Bellini College of AI, Cybersecurity and Computing is teaching ethics at the beginning of the degree rather than bolting it on senior year, on the theory that security is fundamentally a judgment-call discipline, not a checklist one. Elizabeth Nelson is the Corridor’s point of contact at USF.
  • SBIR/STTR grants are available from eleven different federal agencies, it’s non-dilutive funding, and the Corridor can help you go after it and match on top of it.
  • Don’t forget places like Embarc Collective, Tampa Bay Wave, and spARK Labs!
  • Florida’s structural advantage is dual-use! The military and commercial sides are unusually well connected here, and the biggest buyer in the world is a short drive away.

Closing round: What’s the one thing you can’t get wrong?

Michael went down the line and asked each panelist for the single thing a founder walking out with one weekend and a small budget can’t afford to get wrong:

  • Paul: Take the first step. Just do something. Anything.
  • Candace: “Culture eats cyber strategy for breakfast.” If your people haven’t internalized cyber hygiene, none of the rest matters. Her running metaphor all afternoon was brushing your teeth: you don’t deliberate about it, you just do it. Security should feel like that.
  • Aaron: Get business insurance, make sure it has carve-outs for cybersecurity, and make sure those carve-outs cover AI-driven attacks. That’s the one I hadn’t heard before and the one I’d act on tomorrow.
  • Alexei: Hire the right people. (Michael made him clarify for the audio: right people.)

My four take-aways from this session

  1. Compliance is a snapshot, security is a movie. If your controls aren’t monitored continuously, your ATO or SOC 2 report describes a company that existed on one Tuesday.
  2. The framework question has an actual answer: SOC 2 Type 2 first, offload PCI to your payment processor, use a crosswalk so you’re not re-implementing the same control in four vocabularies.
  3. AI didn’t create new attacks; it created new attackers. The skill floor dropped. The people who couldn’t do this eighteen months ago can do it now, at scale, cheaply. Your threat model didn’t change; your threat volume did.

Take-away number four is so good that I wanted to separate it from the rest:

4. Turning a panel into a pop-up advisory board bit was brilliant! Michael took real attendee problems, put them in front of a panel of experts, made them answer in public, and asked them to follow up in 60 days. This moved what the panel said from the rhetorical to the practical.

Let’s see more of this, please, and nicely done, Michael!

Categories
Artificial Intelligence Security Video

Watched a Black Hat interview on AI supply chain security and it’s NetFoundry’s report’s findings, but from the opposite direction

Here’s a video that isn’t from the place where I work (NetFoundry), but from someone works in a different part of AI security. Yet somehow they ended up at the same question that we at NetFoundry ask: How confident are you that your current tools can defend against the new threats brought about by AI?

The video features an interview that took place at the recently-concluded Black Hat 2026 in Las Vegas, and the interviewee is Daniel Bardenstein, CEO of Manifest Cyber.

While NetFoundry focus on identity-based security, Manifest’s focus is on the AI supply chain:

  • Manifest’s approach to security is knowing what’s actually inside the models and software you build and buy. They’re paying particular attention to provenance: training data you didn’t source, open-weight models pulled from a public hub, what’s “under the hood” of your agents.
  • NetFoundry approaches AI security from the other end: what’s outside the models and software you build and buy, and what’s allowed to reach it. We’re about machine identity, service-to-service access, and attack surface.

Watch the video; it’s got some notable stuff, including:

  • Open-weight adoption is about to accelerate, and the reason is control. Bardenstein argues that with a frontier model you have zero control over the system prompt, the training data, or what some provider (or government) decides to change under you. With an open-weight model, you control the whole chain: prompt, data, deployment, guardrails. If you’re already self-hosting models behind OpenZiti, this is the security-side justification for it, from someone who isn’t us.
  • The Hugging Face incident he describes is darkly funny. A lot of people say that the risk with AI models is that they’re non-deterministic, but the HF situation happened because the sandboxing was weak and guardrails  (which really means “ordinary software security”) were missing. Then, when HF pointed its own AI at the forensics, its guardrails read the request as “too cyber” and refused to help,. HF had to fall back to an open-weight model.I’m going to start saying this regularly: AI fails like software because it is software!
  • “AI has its own supply chain and you inherit it.” Every model off a public hub and every third-party dataset is a dependency you didn’t build and can’t fully vet. Bardenstein notes public datasets have shipped with everything from PII to, in documented cases, outright illegal content nobody caught until after training. As the people on the Antiques Roadshow TV show will tell you, provenance is important.
  • The Log4Shell framing is the one I’d steal (in fact, I’m doing that right now). Bardenstein built Manifest after the Pentagon Log4Shell vulnerability (a.k.a. CVE-2021-44228) scramble. The issue boiled down to a simple, embarrassing question: “Where is this one piece of code running across everything I’ve built and bought?” Even having seen what happened five years ago, if you told a CISO a model or dataset was poisoned, they’d likely not be able to tell you where it’s deployed, who owns it, or which vendors are affected without a lot of phone calls, emails, spreadsheets, and gnashing of teeth.

Bardenstein’s observations are pretty much the mirror image of our recently-published 2026 State of Secure AI Access report, where we observe that:

  • 99% of CTOs/CISOs at orgs with 1,000+ employees admit they lack full visibility into their AI deployments.
  • 54% named new AI-specific services like MCP servers and LLM gateways as fresh attack surface.
  • 8% think their identity systems are sufficient for non-human workloads.

Pair our observations with Bardenstein’s supply-chain point and the full failure mode is bleak. An agent you can’t identify, running a model you didn’t vet, reaching services over credentials nobody rotates. That’s three unknowns stacked on top of each other.

My read (not Bardenstein’s or NetFoundry’s report’s) is that giving an agent its own OpenZiti identity solves the “reach” half of the problem. You know what the system or service can talk to and every log line means something.

What it doesn’t do is handle the composition half, or to put it another way, it doesn’t account for what’s inside the thing you just handed an identity to.

Two separate disciplines that happen to share a root cause: You can’t govern what you can’t see, whether “it” is a network path or a model’s provenance.

Categories
Artificial Intelligence Reading Material Security

Security leaders we surveyed feel pressure to secure their AI, and almost none of them feel ready

Here’s a fun little contradiction to start your week with: NetFoundry asked 200 CISOs and CTOs whether they feel pressure to secure the AI they’re deploying. Unsurprisingly, and to my considerable relief, every single one said “yes”.

We then asked how confident they are that their current tools can actually handle the new risks, and 15% said “very.” 15% is very slightly less that the odds for rolling six on a 1d6. More specifically, among the CISOs, whose entire job is to be the professional pessimist in the room, that figure dropped to 10%.

That’s the current situation: Universal pressure, near-universal doubt.

If you just want to get to the report, it’s here. But if you’d like to know more, read on…

Disclaimer and where the survey comes from

I work at NetFoundry as a developer advocate, and NetFoundry commissioned this report. So yes, this is a vendor survey, and you’re correct to raise an eyebrow. (I’d be worried if you didn’t).

In our defense, we did the thing you’re supposed to do: the survey itself was run by an independent research firm (Global Surveyz), the respondents were 200 US-based security and technology leaders at companies with 1,000+ employees, and it was fielded this past May and June.

I’m going to try and separate what the survey found from what I think it means. The first category is data. The second category is me, a guy on the internet, having opinions, which won’t always be the same as NetFoundry’s Marketign department (it happens). I’ll flag which is which.

The number that reframed the whole thing for me

Of everything in here, this is the one I keep coming back to:

Security leaders are nearly 10x more likely to worry about securing machine-to-machine workloads than human access to applications.

Specifically: 69% said machine workloads (service-to-service, API-to-API, agent-to-whatever) are where they’re least confident today. Just 7% said human user access. The remaining 24% said “both equally,” which I read as “please don’t make me pick.”

That tracks perfectly, and it’s a compliment to the last decade of security work. Think about what we spent the 2020s doing. COVID sent everyone home, remote access became the whole ballgame, and the industry poured an enormous amount of money and brainpower into VPNs,  Zero Trust access, and all sorts of security measures for a world that was suddenly more online that ever. It worked, and hman access to applications is, comparatively, a solved-ish problem. We got good at authenticating people. (I should know; it was during that time that I worked at Auth0!)

The issue of identity

The catch is that all of that machinery is built on one quiet assumption: that the thing connecting to your app is a human being with a unique identity. You authenticate the person, then you grant the access.

My late former coworker, Vittorio Bertocci, has forgotten more about identity than I will ever learn, and he was starting to look very deeply into identity in the age of AI.

Agents and models don’t work like that. They don’t have identities the way humans do. So the tooling we built for the last problem doesn’t cleanly transfer to this one, and the volume is going the wrong direction, fast. Machine traffic is now growing several times faster than human traffic year over year. We got really good at guarding a door that fewer and fewer of the visitors are actually using.

A few more stats worth your attention:

  • 100% agree their attack surface is growing. Not a plurality. Not a strong majority. Everyone. The average projected increase was 14% over the next 12 months, and that figure only counts AI deployments already underway or planned. 14% is probably the minimum.
  • 93% are concerned about the new risks AI introduces, but only 15% are highly confident their current tools can handle them. That’s the gap I opened with. When the level of concern and the level of confidence are that far apart, something structural is going on.
  • 99% admit they don’t have full visibility into their own AI deployments. That remaining 1%, which would have to be one respondent? I would like to buy that person a coffee (or beer! or bourbon!) and ask them a lot of questions.
  • 90% are worried about shadow AI, the unsanctioned tools employees adopt on their own because the approved options don’t cut it. This is not a technology problem, it’s a human-nature problem. I will neither confirm nor deny my own contributions to the shadow AI at previous organizations, but in my defense, I was getting things done! When a tool is genuinely useful, people use it, memo or no memo.
  • Only 8% call their current identity systems “very sufficient” for non-human workloads. 85% are now actively evaluating or exploring new approaches. That second number is the tell. When five out of six organizations are shopping for a new approach at the same time, that’s teh surest indicator that the industry is collectively coming to the realization that the existing tools weren’t built for this.
  • Oh, and it’s slow. 55% cited risk and compliance review as a top contributor to delays in the network changes AI deployments need, and those changes add an average of 8 days from request to implementation. And that’s now, while AI-specific scrutiny is still warming up.

My read (this part is me, not the data)

In this section, I’m switching from reporting to speculating.

I think almost every number above traces back to one root cause: machines don’t have real identities. They have internal names so that developers and devops people can talk about them, but when it comes to having reasonably canonical identities like we humans do (full name, usernames, an email address, a government-issued unique ID number), we haven’t really created these for machines.

In the absence of machine identities, we have workarounds. On the less secure end, we have IP addresses; on the (relatively) more secure end, there are shared secrets, API keys, long-lived service-account credentials. As with most workarounds, they quietly rot. The credentials we give machines tend to carry more permission than they need. They rarely get rotated. After a while nobody’s entirely sure which agent a given key even belongs to, or why it exists.

Once you’re in that world, everything downstream gets harder. Visibility is hard because you can’t tell one agent’s actions from another’s. Access control is hard because a secret isn’t an identity, it’s some piece of data that happens to belong to a robot (and all too easily duplicated). Auditing is hard for both of those reasons at once. The identity gap is the root problem of most of the other security problems in the AI age.

NetFoundry — who are made of some very smart people, a few of whom are literal greybeards! — obviously has opinions about how to close that gap, and the report gets into them. That’s the vendor part, and you can take it or leave it.

In case you saw the em-dashes in the paragraph above and thought “Aha! AI!’, I assure you that I typed them in myself, because this is my relationship with AI:

Entering em-dashes is dirt simple on macOS: option-shift-minus. On Windows it’s a little more work: alt+0151. On Linux: control-shift-U, then release and type 2014, then return/enter.

Let me have just a couple of em-dashes in my article. Please.

But strip the logo off and the underlying observation stands on its own: we spent a decade giving humans strong identities and largely ignored the machines, and now the machines are the fastest-growing thing on the network. That bill was always going to come due. It’s just arriving faster than most people planned for.

The stat I want ask you about

That 14% attack-surface increase feels low to me. If you’re actually running agents in production right now, watching them spawn sub-agents and reach across cloud boundaries and pick up new tool integrations every sprint, does 14% over a year match what you’re seeing, or is it wildly optimistic?

(That’s a genuine question, not a rhetorical one. I’d rather hear it from people living it than trust my own gut.)

Read the full 2026 State of Secure AI Access report!

Download it here. (You have to provide a little info to get it.)

Categories
Artificial Intelligence Process What I’m Up To

How I explain how I use AI in my presentations

Pictured above is my standard AI usage disclosure slide, which I include in all my slide presentations these days. It’s gives the audience a quick overview of how I prefer to use AI when putting a talk together.

Here’s the text:

This strategy presentation was developed using AI assistance (Claude, ChatGPT, and Gemini) for:

  • Research: Market trend analysis and competitive landscape review
  • Editing: Grammar, clarity, and flow optimization
  • Ideation assistance: Testing ideas and generating new ones, because no matter how creative you are, it’s impossible to come up with a list of things you’d never think of.

The main contents — including strategic insights, tactical recommendations, specific positioning, and any em-dashes (option-shift-minus on Mac, alt + 0151 on Windows, Google “em dash” and copy and paste it on Linux) — were developed based on analysis of the interview materials and 15+ years of experience in the industry.

I suppose I should also include something about being too much of an egomaniac to let a word prediction machine outshine me. My relationship with LLMs is sort of like the relationship between Dr. Niles “Chief” Caulder (who formed the Doom Patrol) and Batman, as pictured in Batman/Superman: World’s Finest (2022), issue 2:

Categories
Artificial Intelligence Security

Two doors an attacker loves, and one they can’t find

I drew the illustration above on the back of an actual envelope (one of my new “things” these days). It’s either the most or the least appropriate medium for a diagram about attack surface. Your call.

It’s here because my colleague Mark JaffeNetFoundry’s Chief Strategy and Marketing Officer — just published an article called MCP Is Spreading Through Your Enterprise at Developer Speed. Your Security Architecture Isn’t, and it makes a point that I think is worth more than a link-and-a-shrug. So I illustrated one of its key ideas the old-school engineer way, because you’ve probably seen enough AI-generated images and need to look at something a little more human.

Read the article: https://netfoundry.io/ai/mcp-is-spreading-through-your-enterprise-at-developer-speed-your-security-architecture-isnt/

You’re probably seeing this happening around you: teams are wiring AI agents up to their CRMs, databases, and internal APIs through Model Context Protocol servers, because MCP makes it easy. What almost nobody is asking, and what security teams usually can’t even see, is whether the way they’re connecting those servers is quietly creating a new attack vector. In most of the deployments NetFoundry runs into, it does.

The cartoon is Mark’s “before and after,” in three panels. The first two are how nearly everyone connects an MCP server today. The third is what he argues you should be doing instead.

1: Public MCP (a.k.a. “door open to anyone”)

You publish the MCP server on a public hostname, stick a load balancer in front of it, and rely on an API key or an OAuth token to authenticate the agent.

If that gives you déjà vu, it should. This is the exact pattern we all used for REST APIs back around 2012, and it carries the exact same flaw. The server is reachable by anyone on the internet who can enumerate the endpoint or get their hands on a credential. It has to be reachable, because the agent needs to find it. Which means so does everybody else.

That’s the evil bot in the corner going “poke poke.” He doesn’t need to be clever. He just needs the door to exist.

2: Jump host inside (a.k.a. “one session pivots to all”)

“Fine,” you say. “We’ll keep everything internal. Run the agent on a jump host or a dedicated VM inside the network, nothing exposed to the public internet, problem solved.”

Except now you’ve traded one problem for a subtler one. That agent is the thing that’s calling an external LLM, ingesting user-supplied prompts, and taking actions across a dozen connected tools. It’s also now sitting on a trusted internal segment with network-level reach to systems far beyond what it actually needs. Compromise a single agent session and you’ve got a pivot point. One hop to the CRM, one hop to the database, one hop to the internal APIs.

That’s the middle panel: the agent with arrows fanning out to everything. One session pivots to all of them.

3: Outbound only (a.k.a. “don’t call me, I’ll call you”)

Here’s the fix, and the almost annoying thing about it is that it isn’t new. It’s the same outbound-only, identity-bound, least-privilege model that zero trust has been asking for all along. What’s new is applying it to the one connection (agent to MCP server) where none of your existing controls (firewalls, WAFs, network segmentation) actually operate.

The MCP server lives on a private subnet with no inbound connectivity. Instead of the agent reaching in to find the server, the server dials out to meet the agent through an authenticated, encrypted tunnel. There’s no public address to enumerate, no port to probe, nothing sitting there waiting to be found.

Or, as my little pencil agent puts it: don’t call me, I’ll call you.

That line did more work in one speech bubble than a paragraph of my prose could, which is a humbling thing to learn from a robot you drew yourself.

The part that isn’t about doors at all

The panels are the fun part, but the argument I’d actually push you to sit with is why this isn’t just an API-gateway problem wearing a new hat. Mark lays out three things MCP changes that break the old assumptions:

The client is autonomous. An AI agent doesn’t just call an endpoint. It decides which endpoints to call, in what order, with what parameters, based on reasoning you can’t fully predict or constrain up front. So your attack surface isn’t “the MCP server.” It’s the full action space of every tool that agent can touch, across every session it runs.

The session context carries risk. MCP servers receive the agent’s reasoning context right alongside its tool requests. If an attacker can inject content into that context (prompt injection in a document the agent reads, a poisoned result from an earlier tool call, a malicious server the agent got pointed at) they can influence the next tool call in the same session. The MCP connection is the channel that influence travels down.

The inventory is invisible. Most organizations have no systematic way to know which MCP servers their teams have already stood up, which agents are connected to them, or what those servers can reach. If “shadow API” gave you a twitch a decade ago, meet shadow MCP. It’s the same problem, but building up considerably faster.

That speed is the whole thesis, really. The API security industry got the better part of ten years to retrofit controls around a pattern it shipped before it fully understood. MCP is running the same curve compressed into months. Nobody’s getting ten years this time.

So what do you do with this?

If AI-agent security is landing on your desk right now, the uncomfortable truth in Mark’s piece is that the architecture decisions your developers are making this quarter are the ones that’ll be expensive to unwind later. A dev who wires an MCP server to your production CRM through a public hostname isn’t making a temporary choice. They’re setting the pattern every future agent deployment quietly copies.

The good news is that the fix is boring and well-understood. Outbound-only. Identity bound to the connection. Every session governed and observable. Panel 3, basically.

Go read the whole thing! It’s about an eight-minute read and it’s sharper than my envelope.

Categories
Artificial Intelligence What I’m Up To

You can’t spell “airport” without “AI”

Yesterday, Anitra and I were flying back to Tampa from New York’s LaGuardia Airport, and I noticed that most of the ads flashing on the billboard screen overlooking our departure lounge were for AI companies or products.

There were two different ads for Codex (one pictured above, one below)…

…one for Devin

…and one for “Taika Waititi’s fascist twin from a parallel universe”’s company:

Categories
Artificial Intelligence Conferences Tampa Bay

Tampa Bay Tech Week presents 727 Tech Day!

Monday, 7/27, is the day when we celebrate the techies and tech companies in the 727 area code: 727 Tech Day!

727 Tech Day is a one-day, all-in celebration of the St. Pete / Clearwater / Pinellas tech community, presented by the folks behind Tampa Bay Tech Week (with HyLo Innovation and W3RTech). If TBTW is the five-day, five-neighborhood sprawl, then 727 Tech Day as the encore focused on a single Tampa Bay county, with everybody in the same few rooms.

If you’re anywhere near the 727 and you build systems or software for a living, this is the easiest “yes” on your calendar this week.

The essentials

  • When: Monday, July 27, 2026
  • Where: Clearwater and St. Pete. It’s a venue-hop (details below)!
  • Cost: Register on Luma → luma.com/567lh3c0
  • Vibe: Panels, hands-on workshops, a lot of open networking, and an evening that keeps going

727 Tech Day moves around the county!

This isn’t a sit-in-one-ballroom-until-4pm situation. The day migrates across Clearwater and St. Pete, which is either a feature or a step-count challenge depending on your mood:

  • Sunrise yoga on the rooftop at Station House to kick things off. Yes, yoga. At a tech event. Bring your own mat or grab one onsite. I’m told no other tech event in Florida opens like this, and I believe it.
  • Morning sessions at Collaborative Labs (over at St. Petersburg College).
  • Afternoon sessions at NOVA 535 in downtown St. Pete.
  • Happy Hour Networking at 4 PM at the St. Pete Athletic Club, with three hours of the good stuff (founders, operators, investors, community folks, all in one place).
  • Closing Night at 7 PM at The Estate, because “conversations to activations” apparently requires at least one iconic venue and a proper send-off.
Event name and location Group Time
Rooftop Yoga
Station House
Tampa Bay Tech Week – 727 Tech Day 7:00 AM to 8:00 AM EDT
Registration and check-in
Collaborative Labs
Tampa Bay Tech Week – 727 Tech Day 8:30 AM to 9:00 AM EDT
St. Pete’s Economic Development Discussion
Collaborative Labs
Tampa Bay Tech Week 9:00 AM to 10:00 PM EDT
Maritime and Defense Tech Panel Discussion
Collaborative Labs
Tampa Bay Tech Week – 727 Tech Day 10:00 AM to 11:30 AM EDT
Build Your AI Workflow Live Workshop
Nova 535
Tampa Bay Tech Week – 727 Tech Day 12:00 PM to 1:00 PM EDT
AI + Marketing What Actually Works In 2026
Nova 535
Tampa Bay Tech Week – 727 Tech Day 1:00 PM to 2:00 PM EDT
Using AI As a Revenue Engine
Nova 535
Tampa Bay Tech Week – 727 Tech Day 2:00 PM to 3:00 PM EDT
Raising Capital in 2026 For Your Business
Nova 535
Tampa Bay Tech Week – 727 Tech Day 3:00 PM to 4:00 PM EDT
727 Tech Day Networking
St. Pete Athletic
Tampa Bay Tech Week – 727 Tech Day 4:00 PM to 7:00 PM EDT
727 Tech Day Closing Celebration Sponsored by XUNA AI
The Estate
Tampa Bay Tech Week – 727 Tech Day 7:30 PM to 12:00 AM EDT

Why go?

Because this is our scene! It shows up best when we show up. 727 Tech Day is pitched as “no filler, no fluff”. The afternoon track alone, which is a build-something-real AI workshop plus three panels that all promise to separate signal from hype, is worth the trip. Add the networking window and the closing night, and you’ve got a full day of the people you actually want to run into.

I’ll be around. Come say hi! I’m the one with the accordion energy and strong opinions about zero-trust networking.

Grab your spot: luma.com/567lh3c0. For more info, check out 727techday.com

See you in the 727!