# Dazza Greenwood

Dazza Greenwood works on legal technology and computational law, including how organizations evaluate AI systems and govern their use in professional work. Their work includes consulting, research, teaching, writing, and community events.

- Profile: https://b2binfluencer.marketing/creators/dazza-greenwood/
- LinkedIn: https://www.linkedin.com/in/dazzagreenwood
- LinkedIn followers: 15,491
- Topics: artificial-intelligence, ai-governance
- Based on 13 dated posts, latest 2026-08-11

## Summary

Most useful for advising legal and professional services firms on internal AI evaluation and governance programs.

- Best for: Established legal software or professional services firms needing evaluation, governance, and practitioner sessions.
- Not for: Paid social endorsement campaigns promoting AI products with benchmark superiority claims or reach targets.
- Check first: Confirm audience includes employer type, job function, and seniority data, not only follower count.

### Takeaways

- Generic benchmarks miss an organization's edge cases, terminology, and own standards.
- An audit of 88 commercial AI products found roughly 40 percent with instructions against users.
- Professionals stay accountable when vendor system prompts are hidden and control instructions.

## Main ideas

- **Generic AI benchmarks can't tell you whether a tool works in your organization**: Greenwood argues that benchmark scores describe performance in abstract scenarios but miss an organization's edge cases, terminology, and quality standards. The gap between a benchmark score and real-world performance can damage trust. They propose systematically evaluating specific products and workflows, and treat the ability to define good output in objectively checkable terms as a core executive and governance function—not a technical specialty. In their view, anyone who can explain good work to a human employee can write a meaningful AI evaluation.
- **Professionals remain accountable when vendor instructions are hidden**: Greenwood argues that lawyers and other professionals remain responsible for their work, even when an AI vendor can insert higher-priority instructions—hidden system prompts that professionals cannot see, change, or know have changed. A carefully written user prompt may not control the answer, so customization alone offers no real assurance. They frame system-prompt assurance as a missing link between professional responsibility and vendor accountability: customization is not governance.
- **Learn to use legal AI agents within explicit authority boundaries**: Greenwood argues that practitioners should work through the transformation in legal work hands-on, not just hear about it. The teaching program they convene covers authority boundaries, legal research, agent skills, HTMLaw, AI-native professional services, and new forms of legal practice. It moves from talks and demonstrations to team sessions, where participants bring their own agents, form teams, and produce shared outputs in live human/agent collaboration rooms. Limits on agent authority lead the agenda.
- **Practitioner community and informal prompt-sharing are part of the method**: Greenwood's community work makes the case that legal professionals learn generative AI through recurring, agenda-free gatherings where people share prompts and hands-on applications over drinks. The low-stakes format is open to anyone, including the AI-curious, making it easier to compare real-world practice than to listen to a talk.

## Work to read

- [Beyond AI benchmarks: custom evals and Lake Merritt](https://www.linkedin.com/posts/dazzagreenwood_beyond-ai-benchmarks-activity-7369791778578702339-LSxF)
- [law.MIT.edu 2026 Summer Intensive on AI agents and law](https://www.linkedin.com/posts/dazzagreenwood_lawmitedu-2026-summer-intensive-computationallaworg-activity-7492738206619226113--HgF)
- [AISPA system-prompt audit and professional accountability](https://www.linkedin.com/posts/dazzagreenwood_aispa-user-centric-system-prompt-auditing-activity-7491344264958963712-nTDR)
- [Bay Area Legal Hackers Happy Hour](https://www.linkedin.com/posts/dazzagreenwood_legal-hackers-holiday-happy-hour-torch-activity-7391904132938440705-1tLx)

## Brand relationships

- **MIT** (employment)
- **CIVICS.Com** (owned_business)
- **Stanford CodeX** (mention)
- **Stanford HAI Digital Economy Lab** (mention)
- **Descrybe** (disclosed_partnership)
- **Lake Merritt** (owned_business)
- **AISPA** (disclosed_partnership)
- **Bay Area Legal Hackers** (disclosed_partnership)
- **Relativity Fest** (mention)
- **Harvey** (mention)

## Partnerships

No sponsorship packages, media kits, rate cards, or disclosed brand-partner placements appear in the material reviewed. Dazza Greenwood does state that their consulting service, CIVICS.Com, continues unchanged through the transition from MIT to Stanford, with work shifted toward evaluating whether AI applications meet quality, cost, and risk thresholds. They also offer free public teaching and community formats: the August 2026 law.MIT.edu Summer Intensive workshop and the Bay Area Legal Hackers happy hour were both open, free to attend, and framed as community and hands-on practice rather than sponsored placements. For a legal tech company, the practical starting point is an advisory, evaluation, or speaking engagement built around their current research agenda rather than a pre-published advertising slot. Their posts establish that the consulting service exists and has moved into evaluation work; ask directly about pricing, exclusivity, lead times, and a partnership contact.

## Alternatives

- Shakiva Pierre, Esq.: Worth switching to if the campaign shifts from AI governance to New York real estate law—residential and commercial landlord-tenant matters, transactions, and litigation—or to a session for real estate attorneys on building and running a practice. Pierre’s published work is squarely in that area: she describes launching the Law Office of Shakiva S. Pierre, Esq. PLLC after nearly a decade in New York real estate law and time at two New York City real estate firms, serving as a chair of the Real Estate Law Section of the Metropolitan Black Bar Association, and writing about development, networking, and community work as part of growing a firm. For buyers targeting small-firm and real estate practitioners with a session on practice-building rather than AI, she offers subject matter Greenwood does not cover.
- Tom McMakin: A better choice when the need is go-to-market and account-expansion training for the professionals who would carry an AI program forward, rather than the governance framework itself. McMakin’s writing covers exactly that: a business-development training proposal to a healthcare consulting firm focused on building key accounts and expanding work inside existing clients, and a candid account of a call where asking what a client was trying to get done—rather than pitching—surfaced a thought-leadership need. If the legal tech company’s problem is that its law-firm clients buy one product and never expand, this is the closest published match among the three alternatives.
- Misty Murray: Consider Murray when the buyer wants implementation inside law firms rather than an evaluation methodology—teaching legal teams to get more out of tools they already pay for. The posts make that concrete: a Copilot blog series arguing that Microsoft 365 (Planner, SharePoint, OneNote, Lists, Excel) should be used with intention to see how a team really works and where processes stall, and a case-autopsy tip using Planner, Excel, and Copilot to judge whether a contingency case was worth it and refine intake criteria. That covers the operational side of a campaign seeking measurable processes, adoption inside a firm, and process sustainability, at a more hands-on, tool-specific level than Greenwood’s published material.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/