Concepts
Agentic Behaviour
A practical guide to agentic behaviour: how systems progress from chatbots to workflows, tool use, and goal-directed systems that need context, feedback, boundaries, and review.
Resources for building operating intelligence.
Practical notes on orchestration, ontology, review cadence, spend context, and practice-specific operating systems.
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Concepts
A relationship follow-through system for partner-led teams
An example Proximity system for a partner-led advisory practice tracking commitments, context, and follow-up without automating relationship judgment.
Industries
A site decision-support system for a project team
An example Proximity system for a 20-person architecture and project team coordinating drawings, RFIs, site notes, and client decisions without automating professional judgment.
Industries
A sensitive client follow-up system for advisory teams
An example Proximity system for a specialist advisory team preparing sensitive client follow-up without automating care, advice, or professional responsibility.
Industries
An analyst onboarding system for live client work
An example Proximity system for a consulting team onboarding analysts onto live client projects without automating professional judgment.
Methodology
How to decide whether AI is ready to act
An AI readiness checklist for deciding when agents or automation can act: context, source coverage, authority, confidence, reversibility, and review.
AI readiness and governance
How teams decide whether AI can answer, prepare, recommend, escalate, or act with accountability.
Methodology
How to decide whether AI is ready to act
An AI readiness checklist for deciding when agents or automation can act: context, source coverage, authority, confidence, reversibility, and review.
Concepts
What is human-in-the-loop AI?
A plain-English guide to human-in-the-loop AI, human oversight, review boundaries, and how accountable teams keep judgment over risky decisions.
Concepts
Why AI needs source grounding
Why grounded AI and RAG matter for professional work: source grounding shows evidence, freshness, missing context, provenance, and trust boundaries.
Methodology
The hidden work behind AI transformation
Why AI transformation is mostly operating work: mapping workflows, sources, permissions, ownership, review points, and automation boundaries.
Concepts
Agentic Behaviour
A practical guide to agentic behaviour: how systems progress from chatbots to workflows, tool use, and goal-directed systems that need context, feedback, boundaries, and review.
Methodology
The Everything Tool Misconception
A practical critique of the belief that AI should automate everything, and a decision rule for building governed systems that know what to automate, prepare, escalate, or leave human.
Operating intelligence and organisational context
The operating model behind useful AI: context, digital twins, shared memory, sources, cadence, and tools.
Concepts
What is operating intelligence?
A practical definition of operating intelligence, operational context, digital twins for business, and why agentic AI needs legible organisations.
Concepts
What is organisational context?
A practical definition of organisational context for AI: roles, history, priorities, obligations, evidence, relationships, standards, and timing.
Methodology
Saas, Platforms and the Forward-Deployed Model
A practical explanation of how Saas, MSPs, agencies, consultants, platforms, and forward-deployed engineering differ when companies modernise or enable the organisation with AI.
Concepts
What makes AI useful in professional work
A practical framework for useful AI in professional services: better judgment, preparation, coordination, source review, and follow-through.
Concepts
Why AI needs source grounding
Why grounded AI and RAG matter for professional work: source grounding shows evidence, freshness, missing context, provenance, and trust boundaries.
Concepts
A relationship follow-through system for partner-led teams
An example Proximity system for a partner-led advisory practice tracking commitments, context, and follow-up without automating relationship judgment.
Automation vs human judgment
Where AI should automate, prepare, delegate, escalate, or leave responsibility with people.
Concepts
Why professional work is hard to automate
Why professional services AI is hard: expert work depends on context, evidence, exceptions, relationships, risk, and accountability, not only repeatable tasks.
Methodology
The difference between automation and delegation
Automation vs delegation in AI systems: why fixed workflow execution differs from giving agents responsibility for outcomes.
Methodology
The Everything Tool Misconception
A practical critique of the belief that AI should automate everything, and a decision rule for building governed systems that know what to automate, prepare, escalate, or leave human.
Concepts
What is human-in-the-loop AI?
A plain-English guide to human-in-the-loop AI, human oversight, review boundaries, and how accountable teams keep judgment over risky decisions.
Methodology
How to decide whether AI is ready to act
An AI readiness checklist for deciding when agents or automation can act: context, source coverage, authority, confidence, reversibility, and review.
Concepts
Agentic Behaviour
A practical guide to agentic behaviour: how systems progress from chatbots to workflows, tool use, and goal-directed systems that need context, feedback, boundaries, and review.
Industry operating context
Example walkthroughs of Proximity systems for specific professional workflows, team sizes, and project contexts.
Applications
A matter review system for a disputes team
An example Proximity system for a 12-person disputes team that prepares weekly matter reviews without automating legal judgment or advice.
Applications
A renewal control system for finance and procurement
An example Proximity system for a 15-person finance and procurement team preparing vendor renewal reviews without automating spend judgment.
Industries
A site decision-support system for a project team
An example Proximity system for a 20-person architecture and project team coordinating drawings, RFIs, site notes, and client decisions without automating professional judgment.
Industries
A sensitive client follow-up system for advisory teams
An example Proximity system for a specialist advisory team preparing sensitive client follow-up without automating care, advice, or professional responsibility.
Industries
An analyst onboarding system for live client work
An example Proximity system for a consulting team onboarding analysts onto live client projects without automating professional judgment.
Concepts
A relationship follow-through system for partner-led teams
An example Proximity system for a partner-led advisory practice tracking commitments, context, and follow-up without automating relationship judgment.
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