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AI for Tech Teams

From periodic security review to every commit.

Your security team is the same size it was last year. Your codebase is not. This session shows how agents apply your existing security standard at every step of delivery, and where a named person still accepts the risk.

Wednesday, October 14th 2026 - 4:00 PM (WEST)

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About this event

We shipped a payments feature in a consumer app this year. Real users, real money, and agents wrote the code. To review it we ran an agentic scanner: one agent hunts for reachable vulnerabilities, and three independent agents try to refute every finding before it counts. Confirmed findings feed a tracker that gates the deploy.

That setup exists because the old cadence stopped working. A design review at kickoff, a pentest before launch, a scan report read when someone has time. That rhythm made sense when a small security team was the scarce resource and the volume of code was bounded. Agents changed the second half of that equation.

Making your security standard machine-readable is what closes that gap. Once it is written in a form agents can apply, it runs in the spec, at design time, and on every pull request, without adding a single person to the security team.

We will show the whole setup, including the parts that misfire: false positives when a tool cannot see the whole application, findings that change between runs, and agent identity, which nobody has solved yet.

What you'll learn:

  • Why security on a periodic cadence stops keeping up once agents multiply the code your team ships
  • How to turn the security standard you already have into something agents can apply, so requirements land in the spec before any code exists
  • Where to put the deep checks and where to put the light ones, so security runs at every step without slowing delivery down
  • What this looks like on a real feature: agents finding issues, other agents challenging those findings, and only the confirmed ones reaching your team
  • What it costs, where it gets things wrong, and a small first step you can try on your own codebase this week

Who should attend:

  • CTOs and VPs of Engineering
  • Security leads and application security engineers
  • Engineering managers and tech leads
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Why join us?

We run this on our own delivery

The scanner, the design-time skills and the pull request checks we will show are what reviewed a payments feature with real users and real money behind it.

Honest about the trade-offs

What runs today, alongside the false positives, the findings that move between runs, and the cost question you have to answer per repository before you roll this out.

Risk stays with a named person

Agents do the work, humans conduct it. We are specific about where the human gate sits and who accepts a finding when an agent raised it.

No fluff. Just signal.

Sixty minutes, with the last fifteen for your questions, and a working setup to judge your own against.

Can't make it live? Register anyway and we'll send you the recording.

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Past editions

Watch the recordings of the sessions we already ran. Leave your details and the video plays right here.

July 1st 2026

How to redesign a development process with AI

Adding AI tools makes developers faster. Redesigning the process around AI changes what the team can build. We show how we rebuild a development process with goals, loops, dynamic workflows, and agent swarms: the road to a code factory.

May 13th 2026

How we build, test and ship mobile apps with AI agents

A hands-on session covering the 4-layer blueprint Whitesmith's mobile team uses across iOS and Android. From giving agents real context to shipping production features where AI writes 100% of the code.

February 5th 2026

The AI multiplier: what we've learned from transforming dozens of engineering teams

Engineering leaders are under pressure to deliver more without growing headcount. What we've learned from applying AI inside our own organisation and in dozens of client teams: what works, what doesn't, and how to start.

Where's your next real AI gain? A short check reads where your organisation's AI momentum is building, where it's stalling, and the moves that matter most next.

Take the Momentum Check