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Scalability and Technology Consulting Advice for SaaS and Technology Companies

Technology Leadership and AI: Why the Human Element Remains the Ultimate Scale Factor

In a recent episode of the podcast Career Journeys Revealed, hosted by former AKF Partner Han Yuan and Hitesh Chudasama, AKF co-founder Marty Abbott shared profound insights into…

Dave Berardi

· 3 min read

Inside a High-Performing Center of Excellence: 5 Principles for Success

This post explains that high-performing Centers of Excellence succeed by being hands-on, embedded partners that lead by doing—actively building, rotating talent, serving teams, collaborating openly, and staying grounded in real delivery work. Rather than acting as gatekeepers or policy bodies, effective CoEs prove their value through measurable impact, continuous learning, and enabling excellence across the organization.

Heather Abbott

· 5 min read

AI at the Helm - Why Humans Still Matter in Project and Product Management

Have you ever wondered if AI is going to replace the role of Project and Product Managers? Before I became a Principal Consultant at AKF, I started my career as a Technology Project…

StephRene Forbes

· 7 min read

Three Active Regions to Mitigate a Regional Failure - and save Money

The following is an excerpt from the Art of Scalability as a design approach to mitigate the effects of a Data Center or Regional failure such as the AWS-East-1 outage…

Phillip Seawright

· 6 min read

Cloud Induced Paralysis - How Hidden Dependencies Turn Resilience into Risk

When the cloud fails, so does control. The AWS outage exposed how deeply modern companies depend on invisible third-party services. This post explores how hidden dependencies turn resilience into risk and what leaders can do to regain autonomy before the next outage.

David Blatherwick

· 2 min read

CTO vs. CIO: What's the Difference Between These Two Critical Tech Leadership Roles?

CTO vs. CIO: What's the Difference Between These Two Critical Tech Leadership Roles? In today’s technology-driven organizations, the roles of Chief Technology Officer (CTO) and…

Heather Abbott

· 10 min read

Engineering Team Sizes Are Evolving Rapidly With Agentic AI Platforms - The Limits, Challenges and Principles We Must Consider

Agentic AI tools are transforming software development by enabling smaller, leaner two-pizza teams, potentially as small as 2-3 humans, while maintaining cross-functional capabilities. AI agents can handle tasks like coding, testing, and project management, allowing these small teams to deliver products efficiently, especially for focused projects like MVPs. However, challenges such as complex projects, legacy code, and the need for human creativity and oversight suggest that slightly larger teams (4-6 humans) may be optimal for most scenarios. The blog emphasizes maintaining AKF’s principles of autonomy and end-to-end ownership, with humans guiding AI through effective prompts to ensure quality and alignment with business goals.

Dave Berardi

· 5 min read

Composable Agentic Patterns: The Building Blocks of Intelligent Interaction

Agentic interfaces are changing how software works, but most teams still lack a clear way to describe what agents actually do. This post introduces six composable patterns - like Ask + Confirm and Watch + Wait - that define core agent behaviors. These patterns help product, design, and engineering teams work faster, align better, and build more usable AI features. We also outline key design principles like scalability, persona-awareness, and governability. Up next: how to use these patterns in real-world product stories, plus full pattern definitions for reference.

David Blatherwick

· 2 min read

Agentic Pattern: Multi-Intent Fork

Multi-Intent Fork helps agents guide interactions when user input could mean several things. It clarifies ambiguity, presents clear next steps, and keeps users in control - ideal for fast triage and frictionless experiences.

David Blatherwick

· 2 min read

Agentic Pattern: Collect + Summarize

Collect + Summarize helps agents turn fragmented data into concise overviews. Ideal for busy workflows and async environments, this pattern reduces noise and supports faster, more confident decisions across roles.

David Blatherwick

· 2 min read

Agentic Pattern: Handoff + Resume

Handoff + Resume ensures the agent captures context and picks up workflows right where the user left off. It supports multi-session, multi-device, and multi-user journeys - reducing drop-off and boosting flow continuity.

David Blatherwick

· 2 min read

Agentic Pattern: Recommend + Explain

Recommend + Explain helps agents suggest actions while clearly stating why. By combining guidance with transparency, this pattern supports faster, smarter decisions and increases user confidence in AI-driven experiences.

David Blatherwick

· 2 min read

Agentic Pattern: Ask + Confirm

Ask + Confirm is a core agentic pattern that improves trust, reduces risk, and reinforces user agency by validating inputs before action. Ideal for sensitive, ambiguous, or irreversible tasks, this pattern guides product and engineering teams to implement deliberate, user-centered flows.

David Blatherwick

· 2 min read

Agentic Pattern: Watch + Wait

Watch + Wait enables agents to observe context and act only when needed. It’s ideal for asynchronous workflows, nudges, and low-friction support. This pattern helps systems stay helpful without being intrusive, boosting user trust and flow.

David Blatherwick

· 2 min read
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