OPERATING NOTES
Practical thinking for founders, operators, and product teams turning strategy into shipped systems.
Operating Notes
SharePoint agents can ground answers in company content, but teams need source memory around scope, ownership, permissions, freshness and corrections.
Operating Notes
Incident response agents can triage alerts, find similar incidents and draft post-incident reviews, but teams need governed runbook memory around source authority, approvals and corrections.
Operating Notes
AI asset inventories can list agents, models, prompts and MCP servers, but teams need operating memory around ownership, source authority, permissions and review.
Operating Notes
Legal AI agents can review contracts, draft redlines and surface risks, but legal teams need governed contract memory around playbooks, source authority, approvals and negotiation residue.
Operating Notes
Finance AI agents can process invoices, analyse variances and answer ERP questions, but finance teams need governed close memory around source data, approvals, corrections and audit trails.
Operating Notes
AI sales agents can monitor buyer intent, research accounts and draft outreach, but revenue teams need governed pipeline memory around signals, handoffs, permissions, review and CRM write-back.
Operating Notes
Procurement agents can classify vendor emails, analyse purchase-order changes and draft supplier follow-ups, but teams need governed supplier memory around commitments, exceptions, approvals and review.
Operating Notes
AI onboarding agents can draft plans, answer questions and coordinate HR tasks, but teams need governed ramp memory around roles, sources, handoffs and review.
Operating Notes
AI voice agents can answer calls, escalate and trigger tools, but teams need governed call memory around transcripts, permissions, handoffs and review.
Operating Notes
Analytics agents can answer business questions faster, but teams need governed metric memory around definitions, lineage, permissions and review.
Operating Notes
MCP and workplace connectors make AI more useful, but teams need permission memory around sources, actions, approvals and review.
Operating Notes
Coding agents create safer leverage when their plans, diffs, tests, review comments and corrections become governed repo memory.
Operating Notes
Browser agents become useful inside companies when every click, source, permission and handoff leaves governed action memory behind.
Operating Notes
Support AI agents reduce work only when handoffs, exceptions and customer context become governed escalation memory instead of lost conversation residue.
Operating Notes
Meeting AI can summarise calls and extract actions. The operating value comes when decisions, exceptions and follow-ups become governed company memory.
Operating Notes
Why Microsoft and Google’s agent governance push makes company memory, source authority and workflow ownership more important, not less.
Operating Notes
Why company knowledge in ChatGPT is useful retrieval infrastructure, but teams still need source authority, permissions, review paths and workflow ownership around it.
Operating Notes
Why Slack and Teams AI agents need governed company memory, permissions, review paths and workflow ownership before they become trusted operational teammates.
Operating Notes
AI shopping agents are turning product data into commercial infrastructure. Brands need machine-readable product truth, live availability, clear policies and source ownership.
Operating Notes
Why internal AI needs company memory, governed context, workflow ownership, review loops, and interfaces inside Slack, Teams, calls, meetings and trusted systems.
Operating Notes
Anthropic shut down Fable 5 and Mythos 5. OpenAI staggered GPT-5.6 behind government-approved partners. Nadella's token capital argument lands harder: companies need owned company knowledge, not rented frontier access.
Operating Notes
Agent skills are not valuable because markdown is easy to edit. They matter when macro-evals turn repeated agent failures into operating memory.
Operating Notes
AI is changing the economics of software company-building. The model layer may become utility, while workflow infrastructure lets serious teams build multiple vertical bets from one operating layer.
Operating Notes
Tobi Lütke’s River argument shows why public AI agent work matters for product teams: visible reasoning, shared memory, faster judgement, and fewer private execution bubbles.
Operating Notes
Agentic AI creates leverage only when companies redesign context, workflows, permissions, evals, governance and team structures. Headcount-first AI transformation makes broken operating models more fragile.
Operating Notes
AI is stripping product management down to its real value: turning customer signal into coherent systems before fast execution becomes a feature factory.
Operating Notes
Why applied AI systems need ownership, evaluation, human review, and quality bars before automation creates durable operational leverage.
Operating Notes
Lessons from hands-on mobile app building across React Native, Expo, onboarding, tracking, paywalls, release cycles, and early growth loops.
Operating Notes
How event design, CRM logic, dashboards, funnel visibility, and acquisition feedback loops improve product and growth decisions before scale compounds the wrong behaviour.
Operating Notes
A practical argument for treating internal tooling as serious product work, especially when workflow design, automation, QA, and decision quality affect commercial output.
Operating Notes
A practical view of technical product management in AI-heavy teams: workflow design, evaluation, implementation trade-offs, instrumentation, and delivery quality.
