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Practical writing on AI agents, automation and the systems that make them useful in real work.
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01
AI Workflow Architecture
This guide explains the architectural choice between deterministic and fluid AI workflows. Deterministic workflows provide reliability and auditability for fixed processes, while fluid agentic workflows offer the adaptability needed for ambiguous, exception-heavy tasks.
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02
Enterprise AI Strategy
This blog post outlines the importance of data sovereignty and infrastructure ownership in AI strategy. By moving away from reliance on third-party pricing and platform limitations, businesses can achieve better cost predictability and architectural flexibility. Agent Crew advocates for building bespoke, owned AI workflows that integrate directly into a client's existing technology stack.
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03
AI Strategy
GitHub Copilot's move to token-based billing has caused massive bill shock for developers. This post uses the incident to caution Australian SMEs against adopting AI tools without understanding the underlying economic risks. Agent Crew highlights the importance of owning your AI infrastructure to ensure predictable costs and clear ROI, positioning the agency as a partner for sustainable AI implementation.
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04
Weekly AI Intelligence
From April 26 to May 2, 2026, the AI industry solidified its pivot toward 'Agentic AI' with OpenAI, Google, and Adobe launching persistent digital coworkers. Key highlights include Google's 'Deep Research' agents and the revelation that 75% of its code is AI-generated, alongside surging funding for autonomous coding tools. However, rising operational costs and severe infrastructure power shortages have emerged as significant bottlenecks for scaling these autonomous systems.
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05
Enterprise AI Strategy
While 62% of organisations are experimenting with agentic AI, 60% have yet to see an EBIT impact. To bridge this gap, leaders must adopt a five-layer measurement framework that links technical performance, user adoption, and operational KPIs to strategic outcomes and financial impact. By implementing disciplined governance with 'decision gates' and a shared evidence pack, enterprises can move beyond the pilot trap and ensure their AI investments deliver measurable, repeatable value.
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06
Enterprise AI Strategy
The enterprise focus has officially shifted from 'Generative AI' (writing content) to 'Agentic AI' (executing tasks), with 79% of companies now deploying autonomous digital operators. This new era prioritizes real-world outcomes in CRMs, audits, and logistics. Success in 2026 requires an architectural pivot toward API-first design and a leadership shift from managing prompts to orchestrating fleets of autonomous agents that move data and resolve complex workflows without human intervention.
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07
Weekly AI Intelligence
The second week of April 2026 was dominated by the transition toward autonomous agentic AI and heightened cybersecurity concerns. Anthropic restricted its 'Mythos' model due to its exploit-chaining capabilities, while Google and Meta released powerful new reasoning models (Gemma 4 and Muse Spark). The industry is grappling with a severe hardware shortage that is increasing consumer prices, alongside a flood of new agent-building tools like Sierra's Ghostwriter and Cursor 3.0. OpenAI released new policy proposals to address the economic impact of these technologies as it moves toward a $100/month Pro tier for power users.
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08
Agentic Commerce Strategy
As shopping shifts from manual browsing to AI-driven procurement, brands face an existential need for a 'Trust Layer' to prevent algorithmic hallucinations and data liability. Success in 2026 requires Generative Engine Optimization (GEO), transparent consent frameworks, and agentic observability to monitor brand representation within AI ecosystems. Brands that master agent-to-agent rapport while maintaining a human-centric 'safety valve' for recovery will dominate the delegated commerce era.
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09
AI Agent Implementation Strategy
The challenge of adopting agentic AI is primarily a management issue, not a technical one. With less than 10% of companies feeling prepared for human-machine interaction, organisations must integrate AI into existing HR processes. This 6-step framework advises executives to: 1) Give every agent a specific job description, 2) Focus agents on 'dull and deterministic' tasks to aid human colleagues, 3) Evaluate agents on a regular performance cycle, 4) Ensure every agent has a human supervisor, 5) Treat new agents as 'interns' who must earn full-time status, and 6) Name agents to make their roles and accountability clear within the team.
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