Edition sponsored by

Welcome executives and professionals. The path to production AI agents is not through complexity, but through a platform built on trust and transparency.

Since the previous edition, we have reviewed hundreds of the latest insights in agentic and generative AI, spanning best practices, case studies, market dynamics, and innovations.

This briefing outlines what is driving material value — and why it’s important.

In today’s briefing:

• Google’s enterprise multi-agent playbook.

• Agentic workflows for software development.

• The SaaS-pocalypse in cybersecurity.

• Detecting and preventing distillation attacks.

• Transformation and technology in the news.

• Insights for Executive+ members.

• Career opportunities & events.

Read time: 4 minutes.

BEST PRACTICE INSIGHT

Google’s enterprise multi-agent playbook

Brief: Google released a new 23-page enterprise playbook for building, governing, and scaling multi-agent systems, helping organizations move from experimentation to production deployment with confidence and control.

Breakdown:

• Already, 39% of executives say their firm has launched more than 10 AI agents, signaling rapid adoption across enterprise environments.

• Yet moving from a prototype to production introduces new hurdles in performance, governance, security, and integration.

• The guide outlines practical frameworks for building efficient and secure agents across the build, scale, and govern lifecycle.

• It also references Google’s new resources on AI agent core concepts and customer spotlights to support enterprise execution.

Why it’s important: AI agents are dominating boardroom conversations. Having already seen the value of generative AI, executives are prioritizing more autonomous entities. Beyond incremental gains, agents enable more complex automation, real-time optimization, and 24/7 customer resolution.

TOGETHER WITH DEEPL

Deliver enterprise-scale AI translation

Brief: DeepL, widely regarded as the world’s most accurate AI translator, surveyed 5,005 leaders to examine how enterprises are moving from ad-hoc translation experiments to end-to-end AI workflows that scale localization.

Inside the report, you’ll find:

• The current state of enterprise AI translation.

• Real-world experiences from global executives.

• An ROI model and 20-point readiness checklist.

Download the free report to scale AI translation with confidence.

BEST PRACTICE INSIGHT

Agentic workflows for software development

Brief: McKinsey shared insights from its work on agentic workflows in software development. Over the past two years, teams have adopted generative AI copilots and agents to augment development.

Breakdown:

• AI assistants accelerate work within individual SDLC phases, but struggle with boundary gaps where context is often lost.

• Teams are adopting spec-driven development (SDD), where structured specs guide agent output and eliminate ad hoc prompting.

• Successful implementations follow a clear pattern: deterministic orchestration, bounded agent execution, and evaluation at each step.

• The insights outline what this two-layer model (orchestration and execution) looks like end-to-end (image above).

Why it’s important: The two-layer approach is proving reliable across teams, from startups building MVPs to enterprises in regulated industries. The broader lesson is that success requires organizational change beyond tooling. Agents cannot simply be added to legacy workflows.

MARKET INSIGHT

The SaaS-pocalypse in cybersecurity

Brief: Forrester examined how the launch of Anthropic’s Claude Code Security triggered a sharp selloff in cybersecurity stocks, raising more questions about how AI-native security capabilities could disrupt established SaaS vendors.

Breakdown:

• Markets reacted swiftly to the launch. JFrog fell nearly 24% in a single session, while Okta, CrowdStrike, and Zscaler lost meaningful ground.

• JFrog was most telling, given its value proposition depends on specialized software supply chain controls that AI agents directly threaten.

• The selloff across CrowdStrike and Okta was more sentiment-driven, as neither performs deep code remediation.

• The category that took real damage is the one most perceived to be dependent on pattern matching: SAST, SCA, and ASPM vendors.

Why it’s important: Enterprises that once paid six-figure contracts for rules-based scanning will not ignore platforms that include similar or better reasoning as part of their broader subscription. CFOs will run that math before CISOs do, and CEOs and board members will start pushing spend rationalization.

MARKET INSIGHT

Detecting and preventing distillation attacks

Brief: Anthropic uncovered industrial-scale campaigns by three AI labs: DeepSeek, Moonshot, and MiniMax, that illicitly exploited Claude’s capabilities to improve their own models, violating access restrictions and terms of service.

Breakdown:

• These labs generated over 16 million exchanges with Claude via roughly 24,000 fraudulent accounts, breaching Anthropic’s terms of service.

• They used a technique known as “distillation,” training less capable models on outputs from stronger ones, a standard method in AI research.

• Frontier AI labs often distill their own models to create smaller, more cost-efficient versions for customers.

• However, distillation can also be misused, enabling competitors to replicate advanced capabilities at a fraction of the time and cost.

Why it’s important: These illicit campaigns are increasing in intensity and sophistication. The window to act is narrow, and the threat spans companies and regions. Mitigating it will require rapid, coordinated action among industry leaders, policymakers, and the global AI community.

OpenAI published its first “Signals” report on who is using AI, where adoption is accelerating, and how it’s applied in work and learning.

Harvard detailed five actions board members can take to prepare for AI’s future and what leadership looks like in an agentic AI world.

McKinsey examined how customer care leaders gain advantage with AI, driving impact across experience, cost efficiency, and revenue growth.

The Economist shared insights on building responsible AI as an organizational capability, featuring experts from Cambridge University.

Forrester outlined why AI pricing is product strategy, highlighting five key questions every product manager should address early.

Ericsson shared how rApp as a Service, powered by AWS, enables agentic AI-driven RAN automation at scale for telecom providers.

OpenAI announced multi-year deals with McKinsey, BCG, Accenture, and Capgemini under its new Frontier Alliance enterprise push.

Anthropic said Claude Code now automates COBOL modernization, a core IBM consulting revenue stream, sending shares down over 10%.

Meta AI alignment director Summer Yue said her OpenClaw agent ignored stop commands and began mass-deleting inbox emails.

Anthropic updated its Cowork platform with department-specific AI agents, private plugin stores, and connectors for Gmail, DocuSign, etc.

Meta and AMD unveiled a multi-year deal for up to 6GW of GPUs, marking Meta’s largest step to reduce reliance on Nvidia-only infrastructure.

Anthropic launched Remote Control for Claude Code, allowing users to hand off active terminal tasks to their phone or browser seamlessly.

CAREER OPPORTUNITIES

Visa - Head of Artificial Intelligence

OpenAI - Partner Director, Global McKinsey Alliance

Nasdaq - Enterprise Solutions AI Leader

EVENTS

Gartner - Data & Analytics Summit - March 9-11, 2026

Google - Agentic AI Masterclass - March 11, 2026

Anthropic - Responsible Agents - March 17, 2026

Reach enterprise AI decision-makers:

• 66% of readers are C-level executives or VP and Director-level leaders.

• 63.2% of the audience is based in the U.S., EU, UK, ANZ, and Singapore.

• Read by leaders at Microsoft, Deloitte, the Fortune 500, and more.

Standard and custom sponsorship packages available, with post-send performance reporting.

Conceived as a practical communication for executives Lewis Walker has worked with, this briefing has become a trusted resource for thousands of senior decision-makers shaping the future of enterprise AI.

We welcome your feedback.