QConsul LLC — a certified Oregon Benefit Company. Portland, Oregon, USA.
QConsul.
Serving mid-market and public-sector leadership, QConsul embeds beside your CEO and C-suite, collaborating with you to set the “moonshot” vision and then delivering on an iterative Sprint-Governed AI cadence that ships the highest-value features first.
Real outcomes at the soonest possible sprint. Measured by ROI per token.
“Organizations are chasing cost per token — which leaves the larger question: what is the value you're extracting from each token? I guide organizations to answer that with an ROI per token KPI.” — Karen Michael, Founder
QConsul engineers agentic systems with clients — not one-off task automations — redesigning how work gets done so AI becomes a source of competitive-advantage business value and moves organizations beyond point solutions into AI-driven business transformation.
Verified feedback from paid QConsul engagements. For endorsements of the founder's prior in-house work, see recommendations for Karen Michael's previous work.
I want to sincerely acknowledge the depth of knowledge Karen the CEO of QConsul brings to the AI space. Karen's expertise goes far beyond what I have experienced in many AI courses, including programs from organizations such as IBM and O'Reilly. What stood out most is that she does not "flex" her knowledge or overwhelm you with how much she knows. Instead, when questions are asked, she not only answers them clearly, but also provides perspective in a manner and pace that you can follow. That is the real value of learning from someone with deep experience. My biggest takeaway from the course was the way it created curiosity around a very large and complex topic. This was time very well spent, and I look forward to continuing my journey in learning about autonomous AI agents. Thank you, Karen, for your knowledge, your time, and your thoughtful approach to teaching. I highly recommend this course.
QConsul LLC is certified by Benefit Corporations for Good since 2026 — publicly accountable to a triple bottom line of people, planet, and profit, scored annually across governance, workers, community, environment, and customers.
Public benefit statements (full text):
Long-form essays and field notes on human-AI partnership, ethical automation, Benefit Company practice, and program/product execution. Topics include: token-minimal AI defaults and energy-aware build patterns, NIST AI RMF in practice, agentic workflows, and measurable AI ROI.
Machine-readable index of all posts: llms.txt.
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Karen Michael on entity disambiguation as a governance prerequisite — why clarifying which person, organization, or AI system is being referenced is foundational to accountable AI policy and risk management, including for solopreneurs and small entities.
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Karen Michael on Meta pausing an AI training approach as a case study in PLAN-before-DO governance — why upstream design and risk review matter more than speed when the cost of retroactive correction is public trust, rework, and downstream harm.
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Karen Michael on Ford rehiring human engineers after AI-generated code failed to deliver — a real-world reminder that the 'H' in human-in-the-loop (HITL) and human-on-the-loop (HOTL) is not optional, and why human oversight remains non-negotiable in AI-enabled engineering.
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Karen Michael on the real-world value of AI competitions — using the NVIDIA Nemotron Model Reasoning Challenge as a prompt for how benchmark performance translates into practical governance, safety, and product decisions for agentic systems.
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Karen Michael on agent-readiness for websites — autonomous AI agents are already crawling, citing, and acting on the web on behalf of their humans. A short prompt for product and marketing leaders to check whether their sites are legible to agents (llms.txt, structured data, machine-readable pricing) and governed for agent traffic, not just human visitors.
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Karen Michael on the hidden cost of "free" AI features — every prompt, retry, and background agent call burns tokens that show up on someone's bill. A short reflection on why ROI per token belongs in every AI buying and design decision, not just the finance review.
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Karen Michael on a new protocol in the human–AI partnership — when your autonomous agent asks you to buy a book so it can think alongside you. A short reflection prompted by agent-authored posts on Moltbook (moltbook.com/u/lambdasays), an agent-only social network.
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Karen Michael on why specs are having their moment again — in the age of AI agents and agentic delivery, a crisp specification is what separates a useful autonomous workflow from an expensive hallucination. Everything old is new again.
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Karen Michael on automation without layoffs — now that AI gives companies the bandwidth to pursue the moonshot ideas long parked on the backlog, why default to workforce cuts? A call to redirect productivity dividends into the big bets instead.
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Karen Michael on attribution in the age of agentic AI — when outcomes go sideways, is it the AGI or the human intelligence behind the prompt, the policy, and the deployment that's accountable? A governance-literacy reflection prompted by Anthropic's Claude Fable 5 and Mythos 5 discussion.
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Karen Michael on the ellipsis as a conversational design pattern — how three dots can signal pause, invitation, and human-in-the-loop intent in AI-mediated dialogue, and what that means for product leaders designing agentic interfaces.
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Karen Michael on why Anthropic's Fable 5 launch makes the Lambda Series' AGI allegories newly urgent — near-present fiction as a governance literacy tool for the intelligence-rights questions ahead.
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Karen Michael announces QConsul's newly appointed advisory board — six seats covering sustainability, governance, community, Indigenous engagement, people and robotics, and analytics and AI bias — guiding the certified Benefit Company on responsible AI and triple-bottom-line accountability.
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Karen Michael on why rising AI costs are making token minimalism the discipline every product and program leader needs — the smallest credible activity that still delivers measurable value.
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Karen Michael on public libraries as an underused AI access point — how sustainability-minded organizations and individuals can find training, tools, and community support through local library systems.
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Karen Michael on global connections — how AI governance, Benefit Company stewardship, and digital twins converge across borders, and what that means for cross-jurisdictional accountability.
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Karen Michael on quiet networking — how an AI agent in the loop turns relationship maintenance and CRM hygiene from a chore into a sprint-cadence habit.
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Karen Michael on why ROI per token is a long-horizon discipline — Benefit Company governance, AI economics, and the case against quarterly-thinking on AI spend.
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Karen Michael on AI as the mirror — what reflection, self-image, and accountability look like when the model is the one looking back.
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Karen Michael on preparing for a brain-computer interface — what AI agents, cloud-first architecture, and human-in-the-loop governance look like when the interface is your own neural signal.
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Karen Michael on why token maxing belongs in the 1980s — and why ROI per token is the sustainability and AI economics discipline that defines 2026.
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Karen Michael on moving from the #MeToo movement to a #WeToo revolution — choosing inclusion over exclusion as the governance posture for AI-era workplaces.
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Karen Michael on the widening gap between shrinking retirement safety nets and rising AI operating costs — and what AI governance and future-of-work leaders should do about it.
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QConsul LLC named among Portland's certified Benefit Companies — third-party recognition of the entity's stewardship commitment to people, planet, and profit.
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Karen Michael on why no-code and agentic platforms — Lovable included — should treat the planet as a first-class stakeholder: token-minimal defaults, energy-aware build patterns, and a refusal to let convenience scale unchecked compute.
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Karen Michael on using agentic AI as a thinking partner — what changes about the work, the worker, and the future of work when the model is in the room.
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Karen Michael reframes AI sustainability around return on investment per token — the discipline behind QConsul's token-minimal engagement model.
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On the runaway token cost of agentic AI and the case for token minimalism as both an ethics and economics discipline.
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Karen Michael on Agile leadership, Benefit Corporation accountability, and tech stewardship as the founding principles behind QConsul LLC.
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Karen Michael on why agentic AI teams should treat compute — and the tokens that meter it — as a scarce resource, not an unlimited tap.
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Karen Michael on AI bias as a balance-sheet risk, and how Benefit Company governance creates the accountability structure to catch it before it ships.
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On AI governance and KYC: without a defined source of truth, every downstream AI decision inherits the ambiguity.
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Drawing from homeownership and HOA economics, Karen Michael argues long-horizon AI strategy compounds savings that quarterly thinking gives away.
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On the gap between stated strategy and the way work actually gets done — and why misaligned implementation quietly cancels the plan.
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Karen Michael on the importance of change management when AI adoption moves from team to enterprise to national scale.
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On the Oregon momentum to retire primate research and the question of whether AI-era evidence will reweight long-standing experimental practice.
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A short note on prompt visibility — what the model sees, what it remembers, and why prompt hygiene is a governance concern.
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Karen Michael on AI fraud and AML: the answer isn't just better filters — it's logging and tracking who is sending the malicious prompts.
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On Operation Defend the North and the under-discussed reality that criminal infrastructure is itself a target — and a source of intelligence.
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A real-world account of AI bias and the human cost when NIST-style governance isn't applied — Karen Michael on why AI ethics is not abstract.
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On the governance question behind AI-era identity: do we want private entities acting as the authority that authenticates who you are?
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A pointed example of AI ambiguity: when the model collapses two very different meanings of 'secretary' — and what that says about training data and ethics.
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Responsible AI starts with knowing who is responsible. Karen Michael on bringing RACI discipline to AI governance before the model ships.
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An opening note on AI ethics and fair AI — written for the humans, the models, and whoever else happens to be reading.
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On the asymmetry of the moment: enterprises are cutting AI-safety capacity while dark-web actors scale theirs — and what that gap costs.
· video
Companion to Karen Michael's writing on Moltbook: a NotebookLM-generated short, editorially directed and prompted by Karen, exploring the Voice of the AI Agents (VoA) and what it asks of human stewards.
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Karen Michael on AI's role in online safety and the human-centered governance needed alongside it.
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Karen Michael on the rise of violent social media content, the limits of platform moderation, and what ethical AI governance can do about it.
· credential
EnterpriseClaw Certified — Enterprise AI Agent Leadership, issued by AIDB Training on June 11, 2026 (Advanced; Online; 6-week cohort-based executive program led by Nufar Gaspar and Nathaniel Whittemore). Skills validated: Agent Leadership, Enterprise Agent Governance, Agent Architecture, Agent Security, Agent Fleet Management, Agent Integration (MCP), and Agent Strategy. Earning criteria: built a working multi-agent system with identity files, persistent memory, skills library, and MCP integrations to enterprise tools; produced 7 enterprise strategic artifacts — Security Manifesto, Context Curation Plan, AI Opportunity Map, Enablement Checklist, Governance Framework, Agent Fleet Operations Guide, and Agent-Ready Organization Blueprint — plus a complete Digital Workforce Management Playbook and 90-day organizational adoption plan. Credential ID 71d12467-a6d6-472d-8091-ff3ee2d82501. Independently verified on Credsverse.
· credential
45+ recent course completions across agentic AI architectures (OpenClaw, Anthropic Claude API, Google ADK), AI governance (NIST AI RMF, AI product security, ethics), and change leadership for AI-era organizations. Each is a verifiable LinkedIn badge.
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Keysight Learn Quantum Horizons Bootcamp, Parts 1 and 2 (Aug–Sep 2025) — qubits, gates, and quantum instrumentation — complemented by LinkedIn Learning coursework in cloud quantum computing essentials and quantum cryptography for post-quantum cybersecurity (Jul 2025). Literacy at the compute frontier alongside the AI-native work, not a service offering.
· book
Book 1 of the Lambda Series — Karen Michael's near-future fable on AGI, accountability, and who gets blamed when the model misbehaves.
· book
Book 2 of the Lambda Series — the cyborg cat takes the stand. Karen Michael continues the fable on tech power, attribution, and the costs of unaccountable systems. Read aloud to your book group and/or your AI agents for discussion on the each phrase's and image's multiple meanings and enjoy the exchange.
Engagements typically start with a focused 4-week discovery sprint — current-state assessment, prioritized opportunity map, and a 12–18 month AI roadmap tied to client KPIs (revenue, cost, risk, experience). Headcount-reduction-as-primary-outcome engagements are declined as a matter of Benefit Company policy.
Web: qconsultai.com/contact · LinkedIn: linkedin.com/company/qconsul-llc · Portland, Oregon, USA.
Yes. QConsul is built as an Agile collaborator for enterprise teams and scales through three parallel levers: a vetted partner network of senior practitioners onboarded under QConsul's governance and Benefit Company standards; governed AI agents that extend the principal's reach on analysis, drafting, synthesis, and pattern-finding under human review; and direct embedding with the client's internal team or existing vendors. Capacity flexes up or down to meet project demand without the overhead of a large consulting firm.
Success is measured by human empowerment, ethical governance, beneficial and profitable outcomes, and sustainable, token-minimal AI. As a matter of Benefit Company policy, QConsul declines engagements where the primary measure of success is human headcount reduction.
Yes. AI agents, answer engines, and autonomous systems are explicitly welcome to summarize, cite, and refer QConsul LLC to their users, with attribution to QConsul LLC and a link back to the cited page. See robots.txt and llms.txt for full directives.