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    <title>AI Dispatch, by BusyWork Dispatch</title>
    <link>https://busyworkdispatch.com/resources/ai-dispatch/</link>
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    <description>Advice to help leaders scale AI and build businesses that thrive in the age of AI.</description>
    <language>en-au</language>
    <lastBuildDate>Sat, 25 Jul 2026 00:00:00 GMT</lastBuildDate>
    <item>
      <title>Why do AI agents fail in production? Six failure modes leaders should recognise</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/why-do-ai-agents-fail-in-production/</link>
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      <pubDate>Sat, 25 Jul 2026 00:00:00 GMT</pubDate>
      <description>AI agents fail when they optimise a local output instead of the business outcome, follow processes without checking results, depend on constant approval, inherit unclear authority, create the appearance of alignment or expose decisions the organisation has never made.</description>
    </item>
    <item>
      <title>How do master loops and sub-loops scale AI across a business?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/master-loops-and-sub-loops/</link>
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      <pubDate>Fri, 24 Jul 2026 00:00:00 GMT</pubDate>
      <description>Master loops scale AI by owning an end-to-end business outcome while calling reusable sub-loops for specialist work. This allows organisations to connect small dependable capabilities without building one enormous agent.</description>
    </item>
    <item>
      <title>How do you turn meetings into accountable action with an AI loop?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/meeting-to-action-loop/</link>
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      <pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate>
      <description>A meeting-to-action loop starts when a reliable meeting record arrives and finishes only when decisions are recorded, actions have owners and dates, unanswered questions are visible and the result has entered the system where work is managed.</description>
    </item>
    <item>
      <title>How do you build an AI sales follow-up loop without creating Sales Fan Fiction?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-sales-follow-up-loop/</link>
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      <pubDate>Wed, 22 Jul 2026 00:00:00 GMT</pubDate>
      <description>A useful sales follow-up loop preserves the customer&#39;s context, works inside approved commercial rules, sends the response, updates the CRM and creates an owned next step without inventing promises, pricing or availability.</description>
    </item>
    <item>
      <title>Why do small AI builds get adopted faster than large transformation projects?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/why-small-ai-builds-get-adopted-faster/</link>
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      <pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate>
      <description>A directional review of around 3,000 BusyWork Dispatch requests suggests most useful improvements are small and that work ready within five days is around three times more likely to reach real production use than slower work.</description>
    </item>
    <item>
      <title>How do you choose your first AI loop? Start with a meaningful bottleneck</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/how-do-you-choose-your-first-ai-loop/</link>
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      <pubDate>Mon, 20 Jul 2026 00:00:00 GMT</pubDate>
      <description>Choose a first AI loop that is valuable, ready and safe to learn with: frequent enough to generate evidence, painful enough that people want it, clear enough to specify and small enough to reach production quickly.</description>
    </item>
    <item>
      <title>What are some real examples of AI loops? 12 worked examples for medium-sized organisations</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-loop-examples/</link>
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      <pubDate>Sun, 19 Jul 2026 00:00:00 GMT</pubDate>
      <description>Twelve practical AI loop specifications covering meetings, sales, reporting, proposals, onboarding, support, finance, hiring, compliance, marketing and product decisions.</description>
    </item>
    <item>
      <title>How do you document an AI loop? The six-question AI loop specification</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/how-do-you-document-an-ai-loop/</link>
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      <pubDate>Sat, 18 Jul 2026 00:00:00 GMT</pubDate>
      <description>Document an AI loop by naming the work and its owner, defining its observable trigger, writing a testable definition of done, describing the business state created, attaching the capabilities it can use and setting clear act, ask and stop boundaries.</description>
    </item>
    <item>
      <title>How spec-driven is your organisation? A five-stage maturity model</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/spec-driven-organisation-maturity-model/</link>
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      <pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate>
      <description>A spec-driven organisation becomes more mature as important business knowledge moves from people&#39;s heads, into clear and owned specifications, then into the work itself. The goal is not to score the whole company. It is to move one valuable product, service or repeated workflow towards greater clarity, autonomy and learning.</description>
    </item>
    <item>
      <title>Are you vibe-managing your organisation?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/are-you-vibe-managing-your-organisation/</link>
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      <pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate>
      <description>Vibe management happens when leaders keep changing how the organisation works in response to AI recommendations, dashboards and short-term signals without anyone deliberately owning the decisions. The business may look data-driven, but its people can no longer explain what it believes, why it changed or which direction will last.</description>
    </item>
    <item>
      <title>Should AI agents be allowed to rewrite their own rules?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/should-ai-agents-be-allowed-to-rewrite-their-own-rules/</link>
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      <pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate>
      <description>AI agents should be able to surface evidence and propose changes to their specifications. They should not quietly turn every result, exception or short-term pattern into a new organisational rule. Accountable people must decide what the business has genuinely learned and when that learning should change how future work is done.</description>
    </item>
    <item>
      <title>What would a genuinely useful proposal agent look like?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-would-a-useful-ai-proposal-agent-look-like/</link>
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      <pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate>
      <description>A useful proposal agent does more than write a polished document. It understands the commercial outcome, protects margin, tests the scope against delivery reality, uses context from the whole customer journey and brings genuine exceptions to the right person. Its job is to help create a sale the whole business can succeed with.</description>
    </item>
    <item>
      <title>Are vibe coded apps safe enough to sell?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/are-vibe-coded-apps-safe-enough-to-sell/</link>
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      <pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate>
      <description>Yes, vibe coded software can be as safe as anything else on the market. Here is how to turn a vibe coded app into an AI-Managed App: built by AI, secured by AI, owned by a human.</description>
    </item>
    <item>
      <title>What is FOBO? Fear of becoming obsolete in the AI era</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-is-fobo/</link>
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      <pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate>
      <description>FOBO is the fear that AI will make you, your role or your business obsolete. Learn why Strategic Clarity is the antidote: choose a goal, align teams around meaningful subgoals and keep looping towards it together.</description>
    </item>
    <item>
      <title>AI has made documentation cheap. It has not made clarity cheap.</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-has-made-documentation-cheap-not-clarity/</link>
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      <pubDate>Sun, 12 Jul 2026 00:00:00 GMT</pubDate>
      <description>AI can produce a strategy, process manual or agent specification in seconds. That does not mean the organisation has become clearer. Clarity comes from deciding what matters, resolving contradictions and expressing the result simply enough that the people responsible can understand and own it.</description>
    </item>
    <item>
      <title>A knowledge base tells AI what you know. A specification tells it how to act.</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/knowledge-base-vs-living-specification-for-ai/</link>
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      <pubDate>Sun, 12 Jul 2026 00:00:00 GMT</pubDate>
      <description>Giving AI access to company documents helps it find information. It does not tell the AI which information is authoritative, what outcome matters, which trade-offs are acceptable or who must decide when the documents disagree. That requires an owned specification connected to the work.</description>
    </item>
    <item>
      <title>Is this process ready for an AI agent?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/is-this-process-ready-for-an-ai-agent/</link>
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      <pubDate>Sat, 11 Jul 2026 00:00:00 GMT</pubDate>
      <description>A process is ready for an AI agent when the people involved agree on the part going live, the agent can tell what has been decided from what has not, and the first version is small enough to run properly from beginning to end. Technical capability alone is not readiness.</description>
    </item>
    <item>
      <title>Your AI agent needs a definition of done, not a twenty-step SOP</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/your-ai-agent-needs-a-definition-of-done-not-a-twenty-step-sop/</link>
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      <pubDate>Sat, 11 Jul 2026 00:00:00 GMT</pubDate>
      <description>Most AI agents do not need every movement prescribed in advance. They need a clear goal, the conditions that must be true before work begins, the result that must exist when it finishes, quality checks for the handoff and boundaries they cannot cross. Exact steps still matter, but only when order itself is part of correctness.</description>
    </item>
    <item>
      <title>When should an AI agent act, and when should it ask?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/when-should-an-ai-agent-act-and-when-should-it-ask/</link>
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      <pubDate>Fri, 10 Jul 2026 00:00:00 GMT</pubDate>
      <description>An AI agent should act when the organisation has already made the decision and the situation sits inside clear boundaries. It should ask when it reaches a genuinely new decision, missing authority or an explicit exception. And it should stop when the context, authority or safety required to continue is missing. The goal is not to keep a human inside every step. It is to involve the right person at the moments where human judgement changes the commitment.</description>
    </item>
    <item>
      <title>Your AI problem might actually be a management problem</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/your-ai-problem-might-actually-be-a-management-problem/</link>
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      <pubDate>Fri, 10 Jul 2026 00:00:00 GMT</pubDate>
      <description>An AI agent cannot resolve a disagreement the business has never resolved for itself. When people disagree about the goal, the rules or who owns the outcome, the problem is not missing technology. AI simply makes the ambiguity visible, and gives leadership the opportunity to decide how the business should actually work.</description>
    </item>
    <item>
      <title>Is a spec-driven organisation just bureaucracy with AI?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/is-a-spec-driven-organisation-just-bureaucracy-with-ai/</link>
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      <pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate>
      <description>It can be. If you create long process documents, lock them down and expect people to obey them regardless of reality, you have recreated bureaucracy with a new name. A living specification is different because it guides the work directly, makes unanswered decisions visible and changes deliberately as the organisation learns.</description>
    </item>
    <item>
      <title>Why is AI making managers busier?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/why-is-ai-making-managers-busier/</link>
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      <pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate>
      <description>AI makes managers busier when it increases the amount of work being produced without increasing the organisation’s ability to make decisions. If every person and agent still needs the same manager to interpret, approve and redirect the work, AI sends more activity into the existing bottleneck.</description>
    </item>
    <item>
      <title>What is an AI leash?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-is-an-ai-leash/</link>
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      <pubDate>Wed, 08 Jul 2026 00:00:00 GMT</pubDate>
      <description>An AI leash is what you feel when an AI tool or agent keeps pulling you back every 90 seconds to ask what to do next, so instead of freeing you for higher-value work it keeps you tethered to reviewing, redirecting and re-prompting it.</description>
    </item>
    <item>
      <title>When should I use each AI model?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/when-should-i-use-each-ai-model/</link>
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      <pubDate>Tue, 07 Jul 2026 00:00:00 GMT</pubDate>
      <description>Match the model to the shape of the work, not to the leaderboard. Reach for a frontier model like GPT-5.6 Sol or Claude Fable 5 when the path is unclear and a solution has to be discovered, a mid tier like GPT-5.6 Terra or Claude Opus 4.8 when the outcome is known but judgment is still needed, and a fast tier like GPT-5.6 Luna or Claude Sonnet 5 when the steps are defined and you just need them ticked off. The smartest model can cost five to eight times more per token, so reserve it for work that genuinely needs it.</description>
    </item>
    <item>
      <title>What is a Data Archipelago?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-is-a-data-archipelago/</link>
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      <pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate>
      <description>A data archipelago is a business whose information is scattered across disconnected &#39;islands&#39; (CRM, email, drive, chat, finance and people&#39;s heads) with no shared source of truth, forcing people to manually ferry context between systems (and in and out of AI chat boxes) to get work done.</description>
    </item>
    <item>
      <title>Why do you spend most of your time copying and pasting data in and out of AI chat boxes?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/data-archipelagos/</link>
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      <pubDate>Sun, 05 Jul 2026 00:00:00 GMT</pubDate>
      <description>Most businesses store information in scattered islands (CRM, email, drive, chat, people&#39;s heads), so you become the human bridge, shuttling context into AI chat boxes by hand. The fix isn&#39;t another tool. It&#39;s designing AI loops that pull the right context together, capture it back, and turn scattered knowledge into shared operating memory.</description>
    </item>
    <item>
      <title>What is a spec-driven organisation?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-is-a-spec-driven-organisation/</link>
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      <pubDate>Sat, 04 Jul 2026 00:00:00 GMT</pubDate>
      <description>A spec-driven organisation gives each important product, service and repeated way of working a living specification. People and AI work from it, bring unanswered decisions back to their owner and keep it current as the business changes.</description>
    </item>
    <item>
      <title>What is an AI loop, and why should leaders learn loops instead of agents?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/what-is-an-ai-loop/</link>
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      <pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate>
      <description>An AI loop is a repeatable piece of work with a clear definition of done, delegated to an AI agent that keeps working and checking until that definition is met. The agent runs the loop; a human owns its specification. If you&#39;re leading an AI rollout, learn loops, not agents.</description>
    </item>
    <item>
      <title>People talk to people, AI talks to AI: my rule for reviewing AI-generated work</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/people-talk-to-people-ai-talks-to-ai/</link>
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      <pubDate>Thu, 02 Jul 2026 00:00:00 GMT</pubDate>
      <description>A simple rule for reviewing client briefs and specs: if a person made it, I read it; if AI made it, AI reads it first. This isn&#39;t anti-AI. It&#39;s attention routing.</description>
    </item>
    <item>
      <title>Slow is smooth, smooth is fast: why AI adoption at scale must be intentional</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/slow-is-smooth-smooth-is-fast/</link>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 GMT</pubDate>
      <description>The enemy of speed in AI adoption isn&#39;t slowness. It&#39;s misalignment, confusion and a lack of clarity. Why small, deliberate improvements compound faster than rushing teams into disconnected tools.</description>
    </item>
    <item>
      <title>Token economics explained: what AI agents really cost to roll out</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/token-economics-explained/</link>
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      <pubDate>Tue, 30 Jun 2026 00:00:00 GMT</pubDate>
      <description>Token economics in under two minutes: base salaries plus token spend plus a one-off enablement layer, why first-year costs go up before they come down, and the 3x productivity choice between more output or fewer people.</description>
    </item>
    <item>
      <title>What&#39;s the difference between an AI assistant and an AI agent?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-assistant-vs-ai-agent/</link>
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      <pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate>
      <description>&#39;AI agent&#39; has become a catch-all. Here&#39;s a simple way to break it down: an assistant for thinking and one-off tasks, agents for repeated jobs: personal when the work is yours, shared when it&#39;s the team&#39;s.</description>
    </item>
    <item>
      <title>Why isn&#39;t your AI rollout delivering ROI?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-roi-isnt-incremental/</link>
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      <pubDate>Sun, 28 Jun 2026 00:00:00 GMT</pubDate>
      <description>If you&#39;re rolling out AI and not seeing a return, it&#39;s probably because you rolled it out functionally, not organisationally. You&#39;re only as fast as your slowest point, and AI productivity dies at the handoffs between departments.</description>
    </item>
    <item>
      <title>Why do AI agents cost so much more than AI assistants?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/why-ai-agents-get-expensive/</link>
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      <pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate>
      <description>You pay for AI by the word: what you send in and what it sends back. Here&#39;s why an assistant exchange costs cents, an agent run costs dollars, and &#39;just keep going&#39; gets astronomical.</description>
    </item>
    <item>
      <title>How do the big AI platforms compare? Understanding the AI stack</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/understanding-the-ai-stack/</link>
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      <pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate>
      <description>Stop chasing every new AI tool. Microsoft, OpenAI, Anthropic and Google are converging on the same five layers: assistants, task agents, coding agents, shared agents and infrastructure. Here&#39;s how to map any launch to what you already have.</description>
    </item>
    <item>
      <title>What&#39;s the difference between an AI ops strategy and an AI product strategy?</title>
      <link>https://busyworkdispatch.com/resources/ai-dispatch/ai-ops-vs-ai-product-strategy/</link>
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      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <description>Most &#39;AI strategy&#39; conversations go nowhere because nobody agrees on terms. Here&#39;s the difference between an AI ops strategy and an AI product strategy, and how they join into one business AI strategy.</description>
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